Microstructure and Properties of Plasma Sprayed and Sol-gel Modified Hydroxyapatite Coatings

Transcription

1 Microstructure and Properties of Plasma Sprayed and Sol-gel Modified Hydroxyapatite Coatings By Md. Fahad Hasan A thesis submitted in total fulfilment of the requirements of the degree of Doctor of Philosophy in the Faculty of Engineering and Industrial Sciences All rights reserved. This thesis may not be reproduced in whole or in part, by photocopy or other means, without the permission of the author. Md. Fahad Hasan, 2014 Swinburne University of Technology Hawthorn, Melbourne, VIC 3122

2 Abstract Abstract Hydroxyapatite (HA, Ca 10 (PO 4 ) 6 (OH) 2 ) has a calcium phosphate phase that exhibits a similar chemical structure to that of bone and teeth. For the deposition of HA coatings, plasma spray is the accepted technique that has been approved by the Food and Drug Administration (FDA). However, plasma spray is a complex deposition method, involving a myriad of process parameters, types of equipment, and powder characteristics that have a direct effect on the coating properties. The conventional trial and error optimization process is expensive and time consuming. Thus, there is a need to develop strong scientific correlations among the prime thermal spray parameters that permit the manufacture of quality coatings. In this research, prime plasma spray process parameters have been optimised with respect to several important coating properties. Plasma spray HA coatings have a vast range of applications in the area of biomedical engineering. For these applications, the coating quality is of prime importance and indentation test method is a suitable technique to determine the coating quality. Plasma spray coatings exhibit complex microstructures that consist of flat plate like lamellae, cracks, pores, unmelted particles, weak interfaces between splats, and oxides: features that all contribute to highly heterogeneous and anisotropic behaviour. The effects of applied load, measurement direction, and indent location on the microhardness are investigated in this thesis using Vickers and Knoop indentation methods. It is found that top surface microhardness is higher than the cross-section microhardness. It is seen that measuring the effect of lower applied loads (50 and 100 gf) and higher applied loads (300 and 500 gf) shows two distinct trends concerning microhardness, indent roughness, and Weibull modulus of microhardness throughout the dense areas of the coating thickness during Vickers indentation. The microhardness, elastic modulus, Weibull modulus of microhardness, and Weibull modulus of elastic modulus reach their maximum at central position (175 µm) on the cross-section of the coatings on application of the Knoop indentation technique. Also, dependence of the Knoop microhardness values on the indentation angle follows Pythagoras theorem. ii P age

3 Abstract Plasma spraying of HA offers superior osteoconductivity. However, plasma spray coatings contain cracks, pores and residual stress that reduce the durability, mechanical properties and also can cause partial or complete delamination of the coatings. In this research, sol-gel HA coatings are applied on the plasma sprayed HA coatings to improve the coating properties. It is found that the porosity, microhardness, and surface roughness are improved after sol-gel treatment on the plasma spray HA coatings. Also, phase structure and crystallinity show some improvement. The Ca/P ratio exhibits a higher value on the sol-gel modified thermal spray coatings for both top surface and cross-section compared to the typical thermal spray coatings. iii P age

4 Acknowledgements Acknowledgements I wish to express my deep sense of gratitude from the core of my heart to my supervisor Prof. Christopher C. Berndt for his invaluable guidance, motivation, instructions, untiring efforts, encouragement, and meticulous attention that launches my research and development skill as well as the ability to conduct research independently. It was only possible to reach at this stage, only for Prof. Berndt continuous feedback and input. I would also like to thank Dr. James Wang for being supportive and cooperative throughout this whole research. Thanks to Associate Professor Paul Stoddart for his advice during characterizing sample using Raman spectroscopy system. I must thank the senior technical officers Mr. Andrew Moore and Mr. Brian Dempster for their technical help throughout the progress of my project. I must acknowledge Dr. Deming Zhu for his advice during characterizing sample using Raman spectroscopy and 3D profiler system. I would also like to thank every member of Laser and Thermal Spray Technology (L-TST) Group at Swinburne for their support and help. I also acknowledge international experts in thermal spray technology during their visits to Swinburne University of Technology. Thanks to Prof. Sanjay Sampath from Stony Brook University, USA; Dr. Shrikant Joshi from ARCI, India; and Prof. Ghislain Montavon from LERMPS, France. Special thanks to Dr. Sylvia Mackie and Ruth Fluhr for their proof-reading help. I am also grateful to my family (Father, mother, brother, sister, brother-in-law) for their prayers, supports, and encouragements during my study. Thanks again; especially to my father and mother. iv P age

5 Author s Declaration Author s Declaration I hereby declare that this thesis presented for the degree of Doctor of Philosophy to the Faculty of Engineering and Industrial Sciences, Swinburne University of Technology. The candidate also declares that this thesis is solely candidate s own work and contains no material that has been accepted for the award of any other degree or diploma, except where due references is made in the text. This work has been carried out under the supervision of Prof. Christopher C. Berndt at Swinburne University of Technology, Melbourne, Australia. Md. Fahad Hasan v P age

6 Table of Contents Table of Contents 1. Introduction Objectives of the research project Structure of thesis Literature review Hydroxyapatite Structure and phase diagram Comparison of HA and bone Dissolution behaviour Thermal behaviour Hydroxyapatite powder Deposition of HA coatings Thermal spray process Plasma spray process High velocity oxygen fuel (HVOF) spray process Microstructure of the HA coatings Sol-gel process Advantages of sol-gel coatings Sol-gel chemistry Sol-gel coating techniques Sol-gel HA coatings Optimization of HA coatings Design of experiments (DOE) Importance of design of experiments Factorial and fractional factorial experiments Taguchi orthogonal arrays Response surface methodology DOE for plasma sprayed HA coatings Indentation techniques vi P age

7 Table of Contents Brinell hardness test Meyer hardness test Rockwell hardness test Vickers hardness test Knoop hardness test Leeb hardness test Microhardness study on thermal spray coatings Errors in microhardness testing for thermal spray coatings Summary Experimental equipment, procedure, and materials characterization Plasma spray system Feedstock morphology Preparation of substrate and coating cross-sections Substrate Grit blasting and substrate cleaning procedure Coating mounting, grinding and polishing Characterization of HA coatings Scanning electron microscopy (SEM) & energy dispersive X-ray spectroscopy (EDS) X-Ray diffraction (XRD) Raman spectroscopy Profilometer Analysis of coatings Porosity measurements Microhardness and elastic modulus measurements Deposition efficiency measurements Crystallinity measurements Surface roughness measurements Relationship between process parameters according to literature survey Introduction vii P age

8 Table of Contents 4.2. Methodology Results & discussions Relationship between power and stand-off distance Relationship between power and powder feed rate Relationship between power and powder particle size Relationship between powder feed rate and powder particle size Summary Taguchi design of experimental study on HA coatings Introduction Methodology Results & discussions Porosity Microhardness Deposition efficiency Crystallinity Surface roughness Numerical optimization of coating properties Summary Effect of power and stand-off distance on the HA coatings Introduction Methodology Results & discussions Morphology and microstructure of the coatings Porosity and deposition efficiency Physical properties: microhardness and roughness Phase structure and crystaliinity Summary Microhardness study using indentation techniques Introduction viii P age

9 Table of Contents 7.2. Methodology Microhardness study using Vickers indentation Effects of applied load on the microhardness and indenter tip roughness Effects of indenter location on the microhardness and indenter tip roughness Effects of testing direction Rule of mixture Weibull modulus analysis Microhardness study using Knoop indentation Effects of indentation angle on the microhardness and elastic modulus Effects of testing direction on the microhardness and elastic modulus Effects of indent location on the microhardness and elastic modulus Weibull modulus analysis for microhardness and elastic modulus Depth of indentation Frequency distribution Student s t-test Effects of indentation on the microstructure Summary Sol-gel modified thermal spray coatings Introduction Methodology Effects of sol-gel coatings on microstructure improvement Coating properties Porosity Microhardness Surface roughness Weibull modulus analysis for coating properties Phase structure and crystallinity Ca/P ratio Summary ix P age

10 Table of Contents 9. Conclusions, major contributions, and future work Conclusions Process parameter and DOE study Micromechanical study Study of the sol-gel modified thermal spray coatings Future work References Appendix x P age

11 List of Figures List of Figures Figure 2-1 Hexagonal hydroxyapatite crystal structure. Red = calcium, Light blue = phosphorous, Yellow = oxygen... 7 Figure 2-2 Phase diagram of the system CaO-P 2 O 5 at high temperature (a) with no water present (b) at a partial water pressure of 500 mmhg Figure 2-3 States of matter Figure 2-4 Plasma spray system Figure 2-5 High velocity oxygen fuel (HVOF) apparatus Figure 2-6 Typical thermal spray coatings with common features Figure 2-7 Typical structure of plasma sprayed hydroxyapatite coating (a) top surface, and (b) cross-section Figure 2-8 Grains within a HA coating splat Figure 2-9 Typical HA splat on metal surface with one big and several smaller pores Figure 2-10 Coating-development-model Figure 2-11 Splat-development-model dependent on plasma flame temperature Figure 2-12 Possible phase development in half melted HA powder particle Figure 2-13 Sol-gel process Figure 2-14 Stages of the dip coating process (a) dipping of the substrate into coating layer formation, (b) wet layer formation by withdrawing the substrate, and (c) gelation of the layer by solvent evaporation Figure 2-15 Stages of the spin coating process (a) placing small amount of solution on the substrate, (b) rotating the substrate at high speed, and (c) drying the film Figure 2-16 General model of a process/system Figure 2-17 Coatings build up Figure 2-18 Steps of design of experiment Figure 2-19 Central composite design with cube points, star points and centre points.. 40 Figure 2-20 Brinell hardness testing Figure 2-21 Rockwell working principle xi P age

12 List of Figures Figure 2-22 Vickers hardness testing Figure 2-23 Knoop hardness testing Figure 2-24 HVOF titania coatings (a) top surface, and (b) cross-section Figure 2-25 Comparison of Weibull plots of (a) conventional PSZ coatings, and (b) nanostructured PSZ coatings Figure 2-26 Cause-effect diagram of microhardness measurement for thermal spray coatings Figure 3-1 Plasma spray booth Figure 3-2 Plasma spray torch SG Figure 3-3 Control system Figure 3-4 Powder feeder unit Figure 3-5 Gas supply system Figure 3-6 HA powder (a) morphology, and (b) particle size distribution Figure 3-7 Automatic Struers cutter Figure 3-8 Metallographic preparation (a) grinding (P240-P1200), (b) coarse polishing (15 and 5 µm), and (c) smooth polishing (1 µm) Figure 3-9 Scanning electron microscopy (SEM) Figure 3-10 X-ray diffractometry (XRD) Figure 3-11 Raman spectroscopy system Figure 3-12 Two dimensional profilometer Figure 3-13 Three dimensional profilometer Figure 3-14 The R a parameter Figure 4-1 Relationship between power and stand-off distance (a) with all data, (b) with average data, and (c) with good data Figure 4-2 Relationship between power and powder feed rate Figure 4-3 Relationship between power and powder particle size Figure 4-4 Relationship between powder feed rate and powder particle size Figure 5-1 Plasma spray process parameters graph from literature survey a) power vs. stand-off distance, and b) power vs. powder feed rate Figure 5-2 Plasma spray process with factors and responses for Taguchi L 9 design xii P age

13 List of Figures Figure 5-3 Main effects plot generated by Minitab software Figure 5-4 Main effects plot generated by Minitab software Figure 5-5 Main effects plot generated by Minitab software Figure 5-6 Main effects plot generated by Minitab software Figure 5-7 Main effects plot generated by Minitab software Figure 6-1 SEM surface morphology a) sample 1: (20 kw, 8 cm), b) sample 4: (30kW, 11 cm), and c) sample 7: (40 kw, 16 cm) Figure 6-2 Cross-section of the coatings a) sample 1: (20 kw, 8 cm), b) sample 4: (30 kw, 11 cm), and c) sample 7: (40 kw, 16 cm) Figure 6-3 Influence of spraying parameters on the porosity of hydroxyapatite coatings (a) porosity, (b) deposition efficiency, (c) microhardness, and (d) surface roughness Figure 6-4 Influence of process parameters on the a) crystallinity, b) XRD pattern for i) sample 1: (20 kw, 8 cm), ii) sample 4: (30 kw, 11 cm), and iii) sample 7: (40 kw, 16 cm) of hydroxyapatite coatings Figure 7-1 Schematic of Vickers indentation at different indent location within a typical thermal spray coating microstructure Figure 7-2 SEM micrographs of plasma sprayed hydroxyapatite coating (a) top surface, and (b) cross-section Figure 7-3 Effects of applied load on the microhardness of the coating top section a) dense area, and b) porous area Figure 7-4 Effects of applied load and distance from the substrate-coating interface of the coating on the microhardness a) dense area, and b) porous area (indent location is presented in Fig. 7-1; 100 and 300 gf data are presented on the x-axis position of 77, 177, and 277 µm for clear visualisation) Figure 7-5 Effects of applied load on the surface roughness of indenter horizontal tip Figure 7-6 Effects of applied load and distance from the substrate-coating interface of coating on the indent roughness (indent location is presented in Fig. xiii P age

14 List of Figures 7-1; 100 and 300 gf data are presented on the x-axis position of 77, 177, and 277 µm for clear visualisation) Figure 7-7 Combined microhardness on the top surface using rule of mixture for 75% dense and 25% porous area, 50% dense and 50% porous area, 25% dense and 75% porous area microhardness Figure 7-8 Microhardness on the cross-section calculated using rule of mixture for a) 75% dense and 25% porous area, b) 50% dense and 50% porous area, and c) 25% dense and 75% porous area microhardness (100 and 300 gf data are presented on the x-axis position of 77, 177, and 277 µm for clear visualisation) Figure 7-9 Weibull modulus of microhardness on the top surface a) dense area, and b) porous area Figure 7-10 Weibull modulus of microhardness on the cross-section a) dense area, and b) porous area (indent location is presented in Fig. 7-1) Figure 7-11 Schematic of Knoop indentation at different indent location within typical thermal spray coatings microstructure Figure 7-12 Distributions of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) with change of indentation angle with the substrate-coating interface (indentation angle is presented in Fig. 7-11; 100 and 300 gf data are presented on the x-axis position at 2⁰, 47⁰,92⁰ for clear visualisation) Figure 7-13 Distributions of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) with change of testing directions and applied loads Figure 7-14 Distributions of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) at different locations on the cross-section (indent location is presented in Fig. 7-11; 100 and 300 gf data are xiv P age

15 List of Figures presented on the x-axis position of 77, 177, and 277 µm for clear visualisation) Figure 7-15 Weibull modulus of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) with different indentation angles (indentation angle is presented in Fig. 7-11) Figure 7-16 Weibull modulus of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) with change of testing directions Figure 7-17 Weibull modulus of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) on the cross-section (indent location is presented in Fig. 7-11) Figure 7-18 Depth of indentation variation with change of indentation angles (indentation angle is presented in Fig. 7-11) Figure 7-19 Depth of indentation variation with change of testing directions Figure 7-20 Depth of indentation variation with change of indent locations on the cross-section (indent location is presented in Fig. 7-11) Figure 7-21 Frequency distribution of microhardness on the cross-section at the centre (175 µm) of the coatings Figure 7-22 Frequency distribution of microhardness on the top surface Figure 7-23 Indentation on the cross-section of the coatings at the centre position (175 µm) with an applied load of 100 gf (a, b) without splat movement, and (c, d, e, f) with splat movement ( HK indicates Knoop microhardness value and a indicates major diagonal length of Knoop indentation) Figure 8-1 Sol-gel modified thermal spray coatings with active top layer Figure 8-2 Typical thermal spray coatings top surface Figure 8-3 Sol-gel modified thermal spray coating top surface morphology after 3 days from the sol-gel treatment day xv P age

16 List of Figures Figure 8-4 Sol-gel modified thermal spray coating top surface after 7 days from the sol-gel treatment day Figure 8-5 Typical thermal spray coating cross-section Figure 8-6 Sol-gel modified thermal spray coating cross-section Figure 8-7 Sol-gel modified thermal spray coating cross-section after using gold coatings by PVD technique on the top surface of the sample Figure 8-8 Porosity variation for typical thermal spray coatings and sol-gel modified thermal spray coatings throughout the coating s thickness Figure 8-9 Microhardness variation for typical thermal spray coatings and sol-gel modified thermal spray coatings throughout the coatings thickness with load of (a) 50 gf, (b) 100 gf, and (3) 300 gf (sol-gel modified coatings microhardness data are presented on the x-axis position of 77, 177, and 277 µm for clear visualisation) Figure 8-10 Comparison of Weibull modulus of microhardness on the cross-section of typical thermal spray coatings and sol-gel modified thermal spray coatings with applied loads of (a) 50 gf, (b) 100 gf, and (c) 300 gf Figure 8-11 Comparison of Weibull modulus of porosity for typical thermal spray coatings and sol-gel modified thermal spray coatings Figure 8-12 Comparison of XRD spectra for typical thermal spray coatings and solgel modified thermal spray coatings Figure 8-13 Raman spectra comparison for typical thermal spray coatings and solgel modified thermal spray coatings within a Raman frequency of (a) cm -1 (PO 4 band), and (b) cm -1 (OHˉ band) Figure 8-14 Comparison of Ca/P ratio on the top surface and cross-section Figure 8-15 Ca/P ratio variations throughout the coating thickness xvi P age

17 List of Tables List of Tables Table 2-1 Chemical composition of hydroxyapatite Table 2-2 Comparison of bone and hydroxyapatite ceramics... 9 Table 2-3 Mechanical properties of HA and bone... 9 Table 2-4 Thermal effects of HA Table 2-5 Comparison of different methods to deposit HA coatings Table 2-6 Primary and secondary parameters Table 2-7 A 3 factor, 2 level factorial experiments Table 2-8 A 5 factor, 2 level fractional factorial experiments Table 2-9 Summary of DOE studies done on plasma sprayed HA coatings Table 3-1 Parameters used for SEM analysis of HA coatings and HA powder Table 3-2 Parameters used for XRD analysis of HA coatings and HA powder Table 5-1 Plasma spray process parameters predicted from literature study Table 5-2 Process parameters used in Taguchi L 9 design Table 5-3 Coating properties Table 5-4 ANOVA table for coatings porosity Table 5-5 ANOVA table for coatings microhardness Table 5-6 ANOVA table for coatings deposition efficiency Table 5-7 ANOVA table for coatings crystallinity Table 5-8 ANOVA table for coatings surface roughness Table 5-9 HA optimisation criteria Table 5-10 Comparison of results between actual and estimated performance of coating properties Table 6-1 Plasma spray process parameters Table 6-2 Chemical composition of the coatings for samples Table 7-1 Plasma spray parameters Table 7-2 Comparison of microhardness data with Pythagoras theorem Table 7-3 Student s t-test for the microhardness on the top surface with original (n=20) and adjusted data (n=16) xvii P age

18 List of Tables Table 7-4 Student s t-test for the microhardness on the cross-section with original (n=20) and adjusted (n=16) data Table 8-1 Plasma spray parameters Table 8-2 Full width at half maximum (FWHM) comparison for typical thermal spray coatings and sol-gel modified thermal spray coatings with PO 4 band and OHˉ band Table 8-3 Comparison of chemical composition on the top surface and crosssection of typical thermal spray and sol-gel modified thermal spray coatings Table 8-4 Comparison of chemical composition throughout the thickness for typical thermal spray coatings and sol-gel modified thermal spray coatings Table 8-5 Chemical composition of the sol-gel coatings xviii P age

19 List of Terms and Abbreviations List of Terms and Abbreviations Al 2 O 3 Alumina ANOVA Analysis of variance APS ASTM Ba BSI CaO Cl CO 3 C 2 P CCD DD DE DOE EDS ENV F FDA FWHM HA HPO 4 HVOF Air plasma spray American standard for testing and materials Barium British standards institution Calcium oxide Chloride Carbonate Monetite Central composite design Draft documents Deposition efficiency Design of experiment Energy dispersive X-ray spectroscopy European pre-standard Fluoride Food and drug administration Full width at half maximum Hydroxyapatite Acid phosphate High velocity oxygen fuel ImageJ Image processing and analysis in Java ISO International organisation for standardization xix P age

20 List of Terms and Abbreviations K Mg Na NiAl NIH NIST OHA Pb PLC PSZ PVD SEM SOD SLPM Sr TCP TTCP VPS XRD YSZ Potassium Magnesium Sodium Cermet National Institutes of Health National Institute of Standards and Technology Oxyhydroxyapatite Lead Programmable logic controller Partially stabilized zirconia Physical vapour deposition Scanning electron microscopy Stand-off distance Standard litres per minute Strontium Tricalcium phosphate Tetracalcium phosphate Vacuum plasma spray X-ray diffraction Yttria-stabilised zirconia xx P age

21 Chapter 1 Introduction 1. Introduction Biomaterials are critical components in artificial organs, and they are used as scaffolds in tissue engineering to replace a part or a function of the body in a safe, reliable, economic and physiologically acceptable manner. The goal of using biomaterials is to improve human health by restoring the function of natural living tissues and organs in the body. Therefore, it is necessary to understand the properties, functions, and structures of biological materials. The success of a biomaterial used in an implant depends on the properties and biocompatibility of the implant, the health condition of the recipient, and the competence of the surgeon who monitors its progress. Biomaterials are a worldwide multi-billion dollar industry and it is increasing day by day. Biomaterials have helped to improve, support, and sustain the lives of over 20 million patients over the last decade and the number of patients has increased by 10% per year. The market for organ replacement and prostheses exceeds $300 billion US dollars per year and represents between 7-8% of total worldwide healthcare spending. The market for organ replacement and prostheses exceeds $300 billion US dollars per year and represents between 7-8% of total worldwide healthcare spending. In the United States alone, the cost of therapies enabled by organ replacement technology exceeds 1% of the gross national product [1]. These large expenses highlight the importance of biomaterial development. As a consequence, research in this area is essential to improve materials and reduce costs. This area of materials science is shaped by medical needs, material characterisation and design, basic research, advanced technological development, patient expectation, ethical considerations, industrial involvement, and federal regulation [2]. Such multidisciplinary research requires expertise and techniques used in a wide variety of subjects such as materials science, chemistry, molecular and cell biology, mathematics, engineering, biomechanics, computer modelling, manufacturing, medicine, and genetics. Biomaterial devices are available for joint and limb replacements; artificial arteries and skin; contact lenses; and dentures: all of which aim to replace damaged or diseased tissues. However, prostheses may 1 Page

22 Chapter 1 Introduction also be used for enhancement of the body, of which the most well-known is the breast implant. The applications of biomaterials are expanding daily. Biomaterials are widely used in orthopaedic applications, repair of skeletal tissues, hip, knee, ankle, shoulder, and elbow joint replacement. This current study is focussed on such orthopaedic applications. Metallic devices for orthopaedic applications have been very successful, and hundreds of thousands of them are implanted annually and applied to removable devices, such as those for stabilisation of fractures. The use of metals as biomaterials has been increasing in demand throughout the history of joint replacement. Only metals and some composite materials possess the mechanical strength required to withstand the high loads imposed in uniaxial directions in load bearing joints. Metals and alloys differ in comparison to bone in terms of their properties and their biological response. Disadvantages in selecting metals include harmful ion release [3] and a lower quality of biological response than other types of materials. Thus, to provide protection, a biocompatible coating on metals is preferred. Hydroxyapatite (HA), Ca 10 (PO 4 ) 6 (OH) 2, is well accepted as a bioactive and biocompatible coating closely resembling the mineral phase in bone, and able to form a strong implant-bone interfacial bond to improve prosthesis fixation [4, 5]. Several methods and techniques [6-15] have been introduced to coat hydroxyapatite on metal. Among several deposition techniques, thermal spray, in particular plasma spraying, is the most commonly used method for the application of HA coatings, and it is also the only Food and Drug Administration (FDA) approved method. However, plasma spray has as many as 50 variable process parameters that make it challenging to understand process-structure-property relationships and to optimise parameters. Other challenges include understanding the micromechanical properties of thermal spray HA coatings. It is necessary to understand microhardness and elastic modulus distributions throughout the coatings to properly understand thermal spray HA coatings. 2 Page

23 Chapter 1 Introduction Thermal spray HA coatings contain pores and cracks that may have a detrimental effect on micromechanical properties, resulting in partial or complete delamination of the coatings. However, pores and cracks are beneficial for initial bone growth. Thus, a novel approach is needed to fulfil these two conflicting requirements Objectives of the research project The main objectives of this research project are presented below: a) The first goal of this research was to understand and optimise plasma spray process parameters for hydroxyapatite coatings in order to obtain optimum coating properties. The investigation also includes the effects of process parameters on the coating properties and microstructure. b) The second goal was to analyse and understand thermal spray micromechanical properties (microhardness, elastic modulus) using the Vickers and Knoop indentation technique with respect to the change of applied load, indent location, and indentation angle. Then, statistical analysis was carried out to understand the microhardness and elastic modulus data. c) The third goal of this research was to modify the plasma spray coatings using the sol-gel technique to improve the properties of the coatings Structure of thesis The thesis is divided into nine chapters. Chapter 1 was the introduction of this thesis which described the importance of this work, and goal of this research project. Chapter 2 contains an extensive literature review. The review encompasses an overview of the properties of HA, thermal spray process, sol-gel process, design of experiment (DOE), and indentation techniques. The experimental procedure and equipment are presented in Chapter 3. A detailed description of plasma spray equipment and feedstock description are included. Also, the characterization and analysis of coatings using different equipment are described. 3 Page

24 Chapter 1 Introduction Chapter 4 provides information related to the relationship between plasma spray process parameters. The process parameters collected from the available published literature are employed to establish the relationships. Chapter 5 includes a description of the optimisation of HA coatings using Taguchi DOE technique. Three factors and five responses were considered for the DOE design. The process parameters are optimized in this chapter with respect to optimum coating properties. Chapter 6 emphasises the effect of power and stand-off distance on the HA coating properties and microstructure. Power and stand-off distance are coupled and the effect of these coupled factors on both the properties of the coatings and the microstructures are investigated. Microhardness and elastic modulus study results are presented in Chapter 7. Vickers microhardness results and Knoop microhardness results with respect to applied load, indent location, testing direction, and indent angle are discussed in this chapter. Statistical analysis results are also presented in this chapter. Chapter 8 discusses comparison of typical thermal spray coatings and sol-gel modified thermal spray coatings. Typical thermal spray coatings are modified using sol-gel coatings to improve the coating properties. 4 Page

25 Chapter 2 Literature review 2. Literature review Materials from this section (Section 2.1, 2.2, 2.4) have been accepted in the following book as a book chapter: Berndt, C.C.; Hasan, Md. Fahad; Tietz, U.; Schmitz, K.-P.; Book Chapter title: A review of hydroxyapatite coatings manufactured by thermal spray, Book title: Advances in calcium phosphate biomaterials, Series title: Springer Series in Biomaterials Science & Engineering, Editor: Ben Nissan, B., Vols. 2, pp , Hydroxyapatite In the current era of nanotechnology, hydroxyapatite (HA) coatings have a great importance in the biological and biomedical coating fields. Since hydroxyapatite coatings fulfil the requirement of choice of a material, i.e., proper specification, an accurate characterization, length of the time to function, and safe for humans. HA can be applied to bioinactive implants to make their surface bioactive, and enable faster healing and recovery [16]. Hydroxyapatite is a hydrated calcium phosphate mineral. In 1788, Proust and Klaprota were the first researchers who recognised the similarity between calcium phosphate bioceramics and the mineral component of bone [17]. The development of many commercial and non-commercial calcium phosphate materials, including ceramic HA, non-ceramic HA, β-tcp, coralline HA, and biphasic calcium phosphates was based on this similarity. In 1920, Albee was the first scientist who successfully repaired a bony defect with a calcium phosphate reagent, identified as triple calcium phosphate compound [18]. The production of ceramic materials for use in dental and medical applications was developed by Levitt and Monroe in the late sixties and early seventies [19]. The research was continued in the mid-seventies and scientists worked simultaneously, but independently on the development and commercialization of hydroxyapatite in the USA, Europe, and Japan [19]. Calcium phosphate ceramics have been used for dental implants, orthopaedics, maxillofacial surgery, periodontal treatment, alveolar ridge augmentation, and otolaryngology for about thirty years [20]. They are used as a coating material 5 Page

26 Chapter 2 Literature review applied onto a tougher substrate because of their inherent brittleness in the case of load bearing applications. HA coatings and HA composite coatings are used commercially for hip and knee replacements [21] Structure and phase diagram Werner [17] was the first scientist who, in 1786, named hydroxyapatite as a mineral. The name was derived from the Greek word to deceive [17]. The chemical formula of HA is Ca 10 (PO 4 ) 6 (OH) 2 and it has a Ca/P ratio of 1.67 [22]. Beevers and Mclntyre first reported the structure of HA and it was later refined by Kay et al. [19]. HA is the most abundant naturally occurring phosphate on earth. It provides a major source of phosphorus to the global phosphorus cycle. Sometimes, it is also referred to as hydroxylapatite [23, 24], calcium hydroxyapatite or apatite and it has a similar composition to bone. It is a brittle ceramic with a calculated density of 3.22 g/cm 3. Synthetic HA is considered to be a stoichiometric material, whereas biological apatites are generally considered non-stoichiometric due to vacancies or substitutions that can commonly occur. HA is monoclinic with lattice parameters of a = Å, b = 2a, c = Å, γ = 120 and a lattice volume of Å 3. Figure 2-1 shows the crystal structure of HA. The unit cell contains Ca, PO 4, and OHˉ ions closely packed together to represent the apatite structure. HA, like all apatites, has a hexagonal system with the space group P6 3 /m; thus defining it as a material family [19, 25]. The acceptance of a hexagonal P6 3 structure is limited because this structure gives a poor least squares fit to XRD diffraction. To achieve better fit to diffraction patterns, two monoclinic models have been suggested, P21/b [26] and P21 [27] and also more energetically favourable models of the structure of HA. Their chemical composition and Ca/P ratio are summarised in Table 2-1. The hydroxyapatite phase changes to various other phases upon heat treatment. A phase diagram presents the various phases of a substance under a particular condition. A phase diagram for hydroxyapatite is important because it can describe the formation of different phases with respect to temperature. Figure 2-2 shows the phase diagram of hydroxyapatite (a) with no water present and (b) at a partial water pressure of 500 mmhg. 6 Page

27 Chapter 2 Literature review Figure 2-1 Hexagonal hydroxyapatite crystal structure [28]. Red = calcium, Light blue = phosphorous, Yellow = oxygen Table 2-1 Chemical composition of hydroxyapatite [29, 30]. Symbol Chemical formula Chemical definition Ca/P MCP Ca(H 2 PO 4 ) 2 Monocalcium Phosphate hydrate 0.50 DCPA CaHPO 4 Dicalcium Phosphate Anhydrous 1.00 DCPD CaHPO.2H 2 O Dicalcium Phosphate Dihydrate 1.00 OCP Ca 8 H 2 (PO4) 6.5H 2 O Octocalcium Phosphate 1.33 α-tcp α-ca 3 (PO 4 ) 2 α-tricalcium Phosphate 1.50 Β-TCP β- Ca 3 (PO 4 ) 2 β-tricalcium Phosphate 1.50 TTCP Ca 4 (PO 4 ) 2 O Tetracalcium phosphate 2.00 OHA Ca 10 (PO 4 ) 6 (OH) 2-2x O x Oxyhydroxyapatite 1.67 OA Ca 10 (PO 4 ) 6 O Oxyapatite 1.67 HA Ca 10 (PO 4 ) 6 (OH) 2 Hydroxyapatite Page

28 Chapter 2 Literature review Figure 2-2 Phase diagram of the system CaO-P 2 O 5 at high temperature (a) with no water present (b) at a partial water pressure of 500 mmhg [22, 31]. From Fig. 2-2 (a) it can be seen that hydroxyapatite is not stable under these conditions. It can decompose into other calcium phosphates such as tetracalcium phosphate (TTCP), tricalcium phosphate (TCP), monetite (C 2 P) and mixtures of calcium oxide (CaO) and C 4 P. Figure 2-2 (b) shows that HA is stable up to 1,550 ºC. HA powder is influenced by the partial pressure of water in the surrounding atmosphere and the stoichiometry changes when it is heated. Fang et al. [32] reported the effect of stoichiometry on the thermal stability of HA from experiments where the Ca/P ratios of HA powder samples remained within 1.52 to 1.68 when heated to 1,100 ºC Comparison of HA and bone HA, due to its apatite structure, contains many impurities that allow substitutions of other ions. For example, if there is a deficiency in either calcium or carbonate species, then sodium (Na + ), magnesium (Mg 2+ ), acid phosphate (HPO 4 ), potassium (K + ), carbonate (CO 2-3 ), fluoride (F - ), and chloride (Cl - ) ions may be substituted as minor elements. The trace elements of strontium (Sr 2+ ), barium (Ba 2+ ), and lead (Pb 2+ ) may also be observed. Synthetic HA and the main constituents of bone are compared in Table Page

29 Chapter 2 Literature review Table 2-2 Comparison of bone and hydroxyapatite ceramics [33]. Constituents (wt.%) Bone HA Ca P Ca/P ratio Na 0.7 Trace K 0.03 Trace Mg 0.55 Trace 2- CO There are different methods available to deposit calcium phosphate, and the mechanical properties of calcium phosphate vary depending on their deposition technique. HA powder differs in grain size and in composition because of the difference in preparation methods of the HA scaffold materials. Small grain sizes lead to greater fracture toughness. Table 2-3 shows the comparison of mechanical properties of cortical bone, cancellous bone, and HA scaffolds. Table 2-3 Mechanical properties of HA and bone [34, 35]. Properties Cortical bone Cancellous bone HA scaffolds Compressive strength (MPa) Tensile strength (MPa) Young s modulus (GPa) Dissolution behaviour Hydroxyapatite is stable in body fluids. However, the dissolution rates of other phases formed due to high temperature of the plasma spray may be variable. The dissolution of a material is dictated by its free energy corresponding to a lower solubility product. The new phases appearing in the HA coating are tri-calcium phase [Ca 3 (PO 4 ) 2, TCP; i.e., α-tcp and/or β-tcp], tetra-calcium phosphate (Ca 4 P 2 O 9 ; i.e., TTCP), calcium oxide (CaO), oxyhydroxyapatite (OHA) and oxyapatite (OA). The dissolution order is as follows [19, 36]: CaO >> TCP>ACP>TTCP >OHA/OA >> HA Among all these phases, CaO has no biocompatibility and dissolves significantly faster than TCP, so it is necessary to avoid this detrimental phase. The dissolution of HA coating increases with an increase in porosity and surface area, and a decrease 9 Page

30 Chapter 2 Literature review in particle size and crystallinity. The dissolution decreases as the crystallinity of the coating increases. Sun et al. [37] reported that coatings sprayed at lower power (27.5 kw) demonstrated a pattern of crystalline HA; whereas coatings sprayed at higher power (42 kw) exhibited a pattern of bone apatite. The dissolution of unstable phases in the coating led to an undesirable reduction of the mechanical strength. However, these dissolved phases have been shown to enhance bone tissue growth, as reported by Ducheyne et al. [38] and Porter et al. [39]. Ducheyne et al. [38] compared the performance of three calcium phosphate coatings (polylactic acid /calcium deficient HA, calcium deficient HA and oxyhydroxyapatite/α-tcp/β-tcp) with an uncoated implant in vivo. The calcium phosphate coated implants allowed a greater degree of bone growth than the uncoated implant Thermal behaviour The plasma spray process involves melting of particles by a plasma flame at high temperature (up to 16,600 ºC) that causes thermal decomposition and changes the balance of phases of each particle [40]. Since plasma sprayed HA coatings form with a significantly different crystal structure, phase composition, and morphology than the original starting powder; the changes occurring within the plasma flame need to be understood to ensure that the coating produced has the required composition. There are various processes involved in the thermal decomposition of HA. The heating of HA leads to three processes in particular [22]: Evaporation of water Dehydroxylation and Decomposition Evaporation of water The hydroxyapatite structure has the capacity to absorb water. This water can be present both on the surface of the powder and trapped within pores [41]. The absorbed water begins to evaporate when heated and lattice water starts to evaporate on further heating [42]. 10 Page

31 Chapter 2 Literature review Dehydroxylation The dehydroxylation reaction has been reported by several authors [42, 43], and is as follows: Ca 10 (PO 4 ) 6 (OH) 2 Ca 10 (PO 4 ) 6 (OH) 2-2x O x V x + xh 2 O (1) (Hydroxyapatite) (Oxyhydroxyapatite) Ca 10 (PO 4 ) 6 (OH) 2-2x O x V x Ca 10 (PO 4 ) 6 O x V x + (1-x)H 2 O (2) (Oxyhydroxyapatite) (Oxyapatite) where V represents vacancy and x < 1 In the first step, there is a formation of a hydroxyl ion deficient product, known as oxyhydroxyapatite (OHA). OHA has a large number of vacancies in its structure, a bivalent oxygen ion and a vacancy substitute for two monovalent OHˉ ions of HA [42]. In the second step, dehydroxylation leads to the formation of oxyapatite. In the presence of water, oxyhydroxyapatite and oxyapatite readily transform back to hydroxyapatite [36]. Decomposition Hydroxyapatite decomposes into another phase at high temperature. There is agreement between researchers about the processes that occur during the thermal decomposition of HA. HA retains its crystal structure up to a critical point. When the critical point is exceeded, complete and irreversible decomposition occurs. During decomposition, HA converts into other calcium phosphate phases such as β-tricalcium phosphate (β-tcp) and tetra-calcium phosphate (TTCP). Firstly, oxyapatite transforms into tricalcium phosphate and tetracalium phosphate. In the next step, tricalcium phosphate and tetracalcium phosphate convert into calcium oxide [42, 44, 45]. Ca 10 (PO 4 ) 6 O x ٱ x 2Ca 3 (PO 4 ) 2 (β) + Ca 4 (PO 4 ) 2 O (3) (oxyapatite) (tricalcium phosphate) + (tetracalcium phosphate) Ca 3 (PO 4 ) 2 3CaO + P 2 O 5 (4) (tricalcium phosphate) (calcium oxide) + (phosphorus pentoxide) 11 Page

32 Chapter 2 Literature review Ca 4 (PO 4 ) 2 O 4CaO + P 2 O 5 (5) (tetracalcium phosphate) (calcium oxide) + (phosphorus pentoxide) It is difficult to predict the exact temperatures at which reactions occur. The reactions do not occur instantly, but over a range of temperatures, depending on a number of factors related to the environment and the composition of the HA. Table 2-4 shows the temperature range in which reactions occur as HA is heated from room temperature to 1,730 ºC. Table 2-4 Thermal effects of HA [22]. Temperature (ºC) Reaction(s) Evaporation of absorbed water Evaporation of lattice water Decarbonation Dehydroxylation of HA forming partially or completely dehydroxylated oxyhydroxyapatite 1,050-1,400 HA decomposes to form β-tcp and TTCP <1,120 β-tcp is stable 1,120-1,470 β-tcp is converted to α-tcp 1,550 Melting temperature of HA 1,630 Melting temperature of TTCP, leaving behind CaO 1,730 Melting of TCP Hydroxyapatite powder HA feedstock is the foundation for the thermal spray coating process. The ASTM standard F1609 [46], which is comparable with other standards from FDA or ISO, provides limitations for feedstock concerning crystallinity, particle form and in vivo and in vitro behaviour. Therefore, several common parameters for the feedstock have become accepted. Usually, a fully crystalline pure HA powder is the basis, which is generally manufactured using phosphate-containing and calcium-ioncontaining ingredients. After mixing both components, calcination leads to the HA feedstock [47]. The ASTM Standard Specification (ASTM F [48]) states that surgical implants require a minimum of 95% of HA content, established by a quantitative X- ray diffraction (XRD) analysis, while the concentration of trace elements should be 12 Page

33 Chapter 2 Literature review limited; e.g., arsenic 3 ppm, cadmium 5 ppm, mercury 5 ppm, and lead 30 ppm. The HA phase is required by the International Organisation for Standardization (ISO : 2000, Implants for surgery, Hydroxyapatite Part 1: Ceramic hydroxyapatite) [49] to exhibit a crystallinity of at least 45%. The maximum allowable total limit of all heavy metals is 50 ppm. The Ca/P ratio for HA used for surgical implants must be between 1.65 and 1.82 [48]. The quality of coating depends on the shape of HA powders for plasma spray deposition. The particles are melted or partly melted in the plasma flame; thus the morphology of the powder particles relate directly to the heating rate. Irregularly shaped particles exhibit a higher degree of particle heating within the plasma flame due to their greater surface area to volume ratio than spherical particles. Spherical particles have better flow properties than angular particles and can be more reliably transported to the plasma flame. Powder with a narrow range of particle sizes will result in more consistent coatings. The particles must also be capable of withstanding the spray environment. For example, Cheang et al. [50] observed that weakly agglomerated HA powders fragment within the plasma stream giving a new distribution of smaller particles that influences the coating microstructure Deposition of HA coatings Several techniques are available to deposit HA coatings, such as thermal spray[6, 7], physical vapour deposition [8], electrophoretic deposition [9, 10, 51], biomimetry [12, 52], sol-gel methods [13, 53, 54], and pulsed laser deposition [15]. The comparisons of all the techniques are drawn in Table Page

34 Chapter 2 Literature review Table 2-5 Comparison of different methods to deposit HA coatings [16, 47]. Technique Thickness (µm) Advantages Disadvantages Thermal spray High deposition rate; Low cost; Line-of-sight technique; High temperature; Rapid cooling produces amorphous coating; Physical vapour deposition Uniform thickness; Dense coating; Line-of-sight technique; Time consuming; Produces amorphous coating; Electrophoretic deposition Uniform thickness; High deposition rate; Can coat complex shapes; High sintering temperature; Difficult to produce crack free coatings; Biomimetry <30 Sol-gel Bone-like apatite formation; Can coat complex substrates; Inexpensive; Can coat complex shapes; Homogenous coatings; Time consuming; Requires replacement and constant conditions; High sintering temperature; Thermal expansion mismatch; 14 Page

35 Chapter 2 Literature review The selection of a particular process depends on several factors, such as: Process cost. Process energy. Requirement and availability of the apparatus. Limitation imposed by the substrate. Mechanical compatibility of the coatings with the substrate. Adhesion of the deposited material with the substrate. Requirement of the deposition rate. Purity of the target material. Among all the available deposition techniques, thermal spray, in particular plasma spray, has been approved by the Food and Drug Administration (FDA) for the deposition of hydroxyapatite coatings [55]. The sol-gel coating method is also used for depositing HA coatings since it is economical and provides homogenous coatings Thermal spray process Thermal spray basically employs high temperature and velocity to melt the powder or wire as a feedstock and deposit the surface of one material on another. Thermal spray methods can be divided into two types: (i) chemical energy of the combustion gases that power the flame spray torch, and (ii) electric currents providing energy for plasma generators. Thermal spray can be further classified as: (i) Flame spray, (ii) Plasma spray, (iii) High velocity oxygen fuel (HVOF) spray, (iv) Electric arc spray, and (v) Cold spray. Among these, plasma and HVOF spray are widely used for spraying HA coatings. The plasma spray method offers the possibility of preparing large scale coatings that exhibit excellent adhesion to substrates with complex shapes [47, 56]. Plasma spraying has the ability to produce specialised coatings with functional properties 15 Page

36 Chapter 2 Literature review that are beneficial to the field of biomedical engineering, such as biocompatibility, fixation, corrosion, and wear resistance [57-59] Plasma spray process Plasma spray is regarded as the most versatile of all the thermal spray processes; i.e., flame spraying, arc spraying and HVOF. The plasma spraying process uses the latent heat of two ionised inert gases to create the heat source. The most common gases used to create plasma are argon, as the primary, and hydrogen or helium as the secondary gases. However, the gas usage depends on the type of material to be sprayed and the method of application. A plasma is a complex process environment and phenomenon. When the gases are heated to a particular temperature, the atoms collide with each other due to the excitation and knock their electrons off in the process to form a plasma flame. Plasmas are used in many processing techniques; for example, for the modification and activation of surfaces. There is currently much research being carried out to understand and control plasma. Figure 2-3 shows the different states of matter. Figure 2-3 States of matter [60]. Figure 2-4 shows a typical torch and plasma spray coating process. The advantages of plasma spray have been widely recognised in many industries. The unique features that characterise plasma spray processing are listed below: 16 Page

37 Chapter 2 Literature review The process is simple and flexible. can control coating parameters by the appropriate setting of process parameters. produces uniform coating. can melt any metals, ceramics or composites. has a high deposition rate. The plasma spray system consists of an electronically controlled power supply, a Programmable Logic Controller (PLC)-based operator control station, a gas mass flow system, a closed-loop water chilling system, a powder feeder, and a plasma torch [61]. A primary inert gas, such as argon, is injected between two water-cooled electrodes (the anode and cathode) in the gun, where it is ionised to form a plasma jet when ignited. Any powders injected into the plasma flame will melt and subsequently be deposited onto the substrate to form a coating [62]. The particle velocities of plasma spraying are higher than flame and arc spraying, and therefore, it produces denser coatings and less rough surfaces. Figure 2-4 Plasma spray system [63]. 17 Page

38 Chapter 2 Literature review Since the implant material is not heated during the process, plasma spraying is termed as a cold method, which has the advantage of avoiding metallurgical change or damage to the implant metal [64]. Furthermore, plasma spraying produces coatings with good density and strength, and minimized contamination by other elements during the manufacturing process [64]. Plasma Spray Process Parameters The properties of plasma spray coatings are affected by as many as 50 process parameters [65]. These parameters relate to various parts of the spray process. The major parts are the powder, the powder injector, the plasma torch, the plasma flame itself and the substrate. Among these processing parameters, there are some that can be controlled directly, called primary parameters, and others called secondary parameters which cannot be controlled directly and depend on the primary parameters. The most important primary and secondary parameters are listed in Table 2-6. Table 2-6 Primary and secondary parameters [22]. Primary parameters Powder particle morphology Powder particle composition Powder injection angle Plasma forming gas Plasma forming gas flow rate Current Power Carrier gas Carrier gas flow rate Stand-off distance Substrate material Substrate surface properties Substrate pre-heating Traverse velocity Secondary parameters Plasma flame temperature Plasma flame velocity Dwell time in plasma flame Particle velocity Particle melting Substrate temperature Particle quench rate Residual stress development Coating thickness In order to produce the desired coatings, it is necessary to understand the process parameters because these affect the resultant coatings. The main 18 Page

39 Chapter 2 Literature review parameters of the plasma spray process are: power, plasma forming gas, carrier gas, powder feed rate, stand-off distance, and torch traverse velocity. Power Plasma power has major effects on the coatings. To obtain the appropriate coating, the power of the plasma spray process needs to be appropriate so that it can melt the powder properly. Power is equal to current multiplied by voltage and so current is proportional to power. The typical current values used for spraying HA coatings are in the range of 350 A to 1,000 A. Cizek et al. [66] and Guessama et al. [67] studied the effect of power on the temperature of the plasma flame velocity of the particle. They reported that a high current or power level caused an increase in particle temperature and velocity. Cizek et al. [66] found that high power levels result in an increased flame temperature that causes a greater degree of particle melting. Increasing the power level was also found to cause an increase in the velocity of the plasma flame. A net power increase of 10 kw was observed to cause an increase of 80 ºC in particle temperature and an increase of 60 ms -1 in particle velocity. Increased power lead to a decrease in the purity and crystallinity of HA coatings, as demonstrated by Tsui et al. [68] and Sun et al. [69]. The findings of Yang et al. [70] contradicted these findings [68, 69] where crystallinity increased with increasing current. Tsui et al. [68] reported that the porosity level and extent of microcracking decreased with an increase in power. Quek et al. [71] demonstrated that dense, less porous coatings evolved when high currents were employed. Plasma forming gas The plasma forming gas has a major role in the coating properties. The major component of the gas mixture is known as primary gas and the minor component is known as secondary gas. There are four main gases used in plasma spray processes: argon, helium, hydrogen, and nitrogen. The choice of the plasma gas depends on many factors, such as the design features of the torch, in particular the electrode materials [72]. However, argon is used as the primary gas because it is cheap, easily ionised and has inert properties. Argon, when used in the plasma flame increases the 19 Page

40 Chapter 2 Literature review velocity from 600 ms -1 to 2,200 ms -1 as reported by Fauchais et al. [73]. Helium is used only in special cases because it is an expensive gas, but it produces a high temperature plasma flame, density and enthalpy. Nitrogen and hydrogen are diatomic gases that result in a plasma jet with higher thermal conductivity than monatomic argon and helium plasma gases. Leung et al. [74] reported that the size and shape of the jet and the momentum that the carrier gas imparts on the powder particles vary depending on the gases used. Plasma gas flow rate and power to the plasma torch must be balanced or optimised to obtain a stable plasma flame. Gas flow rate has a direct effect on particle velocity, since increasing the gas flow rate during spraying leads to an increase in particle velocity, as reported by Guessasma et al. [67]. The latter [67] also demonstrated that increasing the gas flow rate from 30 to 50 standard litres per minute (slpm) resulted in an increase in the average particle velocity from 186 to 269ms -1 and also a slight increase in particle temperature from 2,516±131 ºC to 2,526±203 ºC. These results differ from the Cizek et al. [66] who reported no significant change in particle temperature with an increase in gas flow rate. Carrier gas The carrier gas carries the powder into the plasma torch and the powder leaving the torch should pass through the centre of the plasma jet as much as possible because this is the hottest part of the plasma. When selecting the powder carrier gas, it is necessary to consider the chemical reactivity of the powder; an inert gas will prevent chemical changes in the powder particles. The velocity of the powder carrier gas is also important, particularly when the powder injector is radial to the plasma flame. A very low flow rate fails to convey the powder effectively to the plasma jet and a high flow rate may cause the powders to escape from the hottest region of the jet. In a radial injected plasma torch, the powder particles are forced into the plasma flame perpendicular to the direction of the flame. This guides most particles to attain their maximum velocity by being passed through the hottest part of the plasma that is in the centre of the jet. The ideal carrier gas flow rate would inject particles into the plasma jet at a momentum similar to that of the plasma jet. 20 Page

41 Chapter 2 Literature review Different carrier gases have different particle flow into the plasma jet. Argon is most commonly used as the carrier gas [75]. Leung et al. [74] found that nitrogen has a gas momentum value that is 37% greater than that of argon, and for helium the value was 10% less for the flow rates used compared to argon. The nitrogen carrier gas achieved the highest radial distance between the trajectory centre of the particles and the torch axis because it had the highest momentum. Mawdsley et al. [76] demonstrated that carrier gas flow rate influences the thickness of plasma sprayed coatings; i.e., high carrier gas flow rates increase coating thickness. Powder feed rate To reach the powder in a plasma flame, there is a need for a powder flow rate. The powder feed rate has two main effects. Firstly, the powder feed rate affects the coating thickness. If the flow rate increases, that ultimately increases the quantity of particles and increases the coating thickness. However, a very high flow rate may give rise to an incomplete melting, resulting in a high amount of porosity in the coatings. Incomplete melting increases the amount of the unmelted powders that may bounce off from the substrate surface and keep the deposition efficiency (DE) low. Secondly, the feed rate affects the temperature of the plasma flame. When the feed rate increases, it introduces a greater number of particles into the flame, which reduces flame temperature [22]. According to Cizek et al. [66], the effect of the powder feed rate on the velocity and temperature of the plasma flame is small. Stand-off distance (SOD) The distance between the torch and the substrate is called the spray distance or stand-off distance (SOD). SOD affects the velocity of the particle and the length of time that the particles are exposed to the heating effect of the plasma flame; thus affecting the degree of particle melting that occurs. A longer SOD may cause a reduction in the velocity of the droplets during spraying due to the frictional forces from air molecules. A shorter SOD suggests that the substrate experiences more of the heating effects of the plasma flame. Thus, SOD affects the substrate temperature [22]. Kweh et al. [77] demonstrated that coating properties deteriorate with increasing spray distance. 21 Page

42 Chapter 2 Literature review Sun et al. [69] studied the effects of varying stand-off distance from 80 mm to 160mm and reported that longer spray distances were observed to cause increased particle melting, lower porosity and a greater number of microcracks. Lu et al. [78] investigated spray distances of mm. They suggested that, at longer spray distances, the particles begin to cool and resolidify; thereby allowing a coating with increased crystallinity to be formed. Cizek et al. [66] measured the change in temperature and velocities as the spray distance increased from 50 to 150 mm. A decrease in particle temperature of 220 ºC and a decrease in velocity of 90 ms -1 were found over this range. Traverse velocity The velocity at which the plasma torch travels is called torch traverse velocity. Traverse velocity has an effect on cooling, thickness, recrystallization and residual stress development [22]. Traverse speeds used for spraying vary greatly; values ranging from 75 mm/s 750 mm/s [71, 79] have been reported High velocity oxygen fuel (HVOF) spray process For HA processing, high velocity oxygen fuel (HVOF) spray has been investigated [80, 81]. This works on the principle of using kinetic and thermal energy for accelerating powder particles at a nearly supersonic speed with a low flame temperature of almost 3,000 ºC before their impact onto the substrate [82]. Figure 2-5 shows a schematic of a typical HVOF gun design. Figure 2-5 High velocity oxygen fuel (HVOF) apparatus [83]. 22 Page

43 Chapter 2 Literature review This process uses only powder as feedstock, instead of wire or rod. The feedstock powder is injected into a water cooled high pressure combustion chamber that has a long barrel ( mm) [84]. HVOF systems have internal combustion that combust a mixture of fuel (gas or liquid) and oxygen. The fuel gas can be propane, propylene, acetylene or hydrogen. The gas temperature depends on the ratio of fuel and oxygen gas flow rate and the choice of fuel gas. The combustion products are forwarded through a nozzle where they attain supersonic speeds that can be observed as shock diamonds at the exit of the barrel. Powder is fed into the hot and expanding gas where it is heated and accelerated towards the substrate. Coatings produced with the HVOF process exhibit dense coatings, excellent bonding, minimal metallurgical changes, and minimal temperature effects [85] Microstructure of the HA coatings The microstructure of a thermal spray coating depends on the spray parameters and feedstock particle quality [86]. Coatings are created by several layers of overlapping splats that are formed from fully or partially molten feedstock particles. A typical thermal spray microstructure consists of pores, cracks, unmelted particles, voids, oxides, impurities, intra splat cracks, and horizontal cracks as shown in Fig The structure of HA coatings deposited by the plasma spray method are shown in Fig Figure 2-6 Typical thermal spray coatings with common features [87]. 23 Page

44 Chapter 2 Literature review Figure 2-7 Typical structure of plasma sprayed hydroxyapatite coating (a) top surface, and (b) cross-section [88, 89]. Splats are the basic building block of thermal spray coatings. The flat, round shaped splats are approximately µm in diameter and 5 µm thick [90]. The splats consist of grains, which are smaller at the fringe and larger in the centre (up to 5 µm) [90]. Figure 2-8 demonstrates the nano-grained structure of a HA splat. A disc shaped HA splat with pores is shown in Fig Figure 2-8 Grains within a HA coating splat [90]. 24 Page

45 Chapter 2 Literature review Figure 2-9 Typical HA splat on metal surface with one big and several smaller pores[90]. Porosity that forms between splats may be correlated directly to the crystalline HA phase; i.e., the porosity of HA coatings increases with a larger amount of crystalline HA phase [91]. This phase differentiation arises because the crystalline HA splats are less viscous, and therefore flatten less and are slow to cool. Hence, voids between these splats are not filled by viscous material, which may be differentiated from the case of an amorphous phase [91]. Furthermore, it was found that the increase in the less viscous amorphous phase decreases the surface roughness and hence the coating is more smooth. A larger amount of amorphous phase, therefore, is responsible for decreasing the coating porosity. Several authors [92-94] have developed models that describe the manner in which a single splat may consist of diverse phases. Sun et al. [92] developed a model concerning the coating formation and the recrystallization of the amorphous phase, Figure This model suggests that during the solidification of the splat some regions of the amorphous and stoichiometric phase (in between core and shell) recrystallize due to longer cooling times on the coating surface. Furthermore, this model considers that subsequent droplets influence the previous layers. That is, heat from the plasma flame and from the overlapping new droplets melt the outer sections of the prior-formed splats. This process may lead to recrystallization since the new splats decrease the cooling rate of the already-deposited splats. Secondly, while the first-formed splats recrystallize, new OHˉ groups have time to infiltrate these regions and generate a crystalline phase out of a former amorphous phase. 25 Page

46 Chapter 2 Literature review Figure 2-10 Coating-development-model [92]. Gross et al. [93] developed a model that indicates that splat phases depend on the plasma flame temperature, Figure 2-11, since this parameter regulates the viscosity of the splats and the degree of dehydroxylation. Following this model, crystalline, not dehydroxylated, hydroxyapatite can be found in the core of droplets and splats. The amorphous, highly dehydroxylated and fast cooling phase develops at the metal surface; while oxyapatite, which cools down more slowly, is located near the outer splat surface. Higher temperatures lead to tri-calcium and tetra-calcium phosphates, as well as to calcium oxide. Calcium oxide is not desirable due to its bio-incompatible properties. Possible phase development inside a lamellae was developed by Deram et al. [94], Figure There are six possible calcium containing compounds known in the calcium-phosphate system: hydroxyapatite, tri-calcium phosphate, tetra-calcium phosphate, calcium oxide, calcium pyrophosphate and oxyapatite. 26 Page

47 Chapter 2 Literature review Figure 2-11 Splat-development-model dependent on plasma flame temperature [93]. Figure 2-12 Possible phase development in half melted HA powder particle [94]. Not every compound appears in HA coatings, since these are controlled by the spray process and its parameters. The amorphous and the crystalline phases of HA are dominant, with alpha and/or beta phases of tri-calcium phosphate and tetracalcium phosphate often also present. The amorphous HA phase may develop instead of a crystalline phase due to the rapid solidification conditions during the 27 Page

48 Chapter 2 Literature review splat quenching process, where cooling rates of 1x10 6 degrees per second may exist. Thus, the HA does not have adequate time to crystallize [95, 96] Sol-gel process The sol-gel process is a wet chemical process employed in the manufacture of ceramic and glass materials. The sol-gel technique allows preparation of ceramic or glass materials in a wide variety of forms: ultra-fine or spherical shaped powders, thin film coatings, ceramic fibres, micro porous inorganic membranes, and monolithic or extremely porous aerogels [97-99]. An overview of the sol-gel process is illustrated in Fig A sol is a stable suspension of colloidal solid particles or polymers in a liquid; and gel is a porous, three-dimensional, continuous solid network surrounding a continuous liquid phase [97, 100, 101]. Hence, sol differs from a solution, as a solution is a single-phase system, whereas a sol is a two-phase, solid-liquid system. The colloidal solid particles have a size range of approximately nm. The gravitational forces on these particles are negligible and interactions are dominated by short-range forces such as van der Waals and surface charges [97]. Figure 2-13 Sol-gel process [102]. 28 Page

49 Chapter 2 Literature review Advantages of sol-gel coatings Sol-gel is a unique process that can produce powders, platelets, coatings, fibers and monoliths of the same composition by varying chemistry, viscosity and other factors of a given solution. The sol-gel process allows the manufacture of thin coatings (<10 µm) [103]. The advantages of sol-gel coatings are [101, 104, 105]: Low process temperature. Low cost. Ability to control the composition on molecular scale. Homogeneous coatings. Possibility to synthesize composition materials. High purity products. Ability to coat complex shapes. Ability to use various chemical routes. Shrinkage up to a certain number of coatings. Rapid drying of coatings without cracking Sol-gel chemistry The sol-gel process involves the controlled hydrolysis of dissolved metal organic precursors followed by a polycondensation reaction, resulting in the formation of a three dimensional network of particles [106, 107]. The hydrolysis takes place using a small amount of water. In the hydrolysis reaction, the alkoxide groups are replaced stepwise by hydroxyl groups (OH): Polycondensation reactions occur simultaneously with the hydrolysis [106]. M OR + HOH M OH + ROH (6) M OH+ M OH M O M + HOH (7) 29 Page

50 Chapter 2 Literature review M OH + M OR M O M + ROH (8) Sol-gel coating techniques There are two main types of sol-gel coating techniques [101, 106]. Dip coating and Spin coating Dip Coating The dip coating is an inexpensive and rapid method for producing thin homogenous coatings. The dip-coating technique can be described as a film deposition process. In this technique, the substrate to be coated is immersed in a liquid and then withdrawn at a well-defined speed under controlled temperature and atmospheric conditions [101, 106]. The schematics of the dip coating process are shown in Fig The dip coating thickness depends on the solid content, the withdrawal speed, and the viscosity of the liquid [106, 108]. If the withdrawal speed is chosen such that the sheer rates keep the system in the Newtonian regime, then the coating thickness can be calculated by the Landau-Levich equation [109]: h = 0.94 ( ηv) γ ( ρg) 2/3 1/6 1/2 LV where, h = coating thickness η = viscosity v = substrate speed γ LV = liquid vapour surface tension ρ = density g = gravity (9) 30 Page

51 Chapter 2 Literature review Figure 2-14 Stages of the dip coating process (a) dipping of the substrate into coating layer formation, (b) wet layer formation by withdrawing the substrate, and (c) gelation of the layer by solvent evaporation [110]. Spin coating Spin coating has been used for several decades for the application of thin films. Spin coating is a process suited to flat shapes, such as disks, plates and lenses. In this technique, a small amount of solution needs to be placed onto the centre of the substrate and then the substrate is spun at high speed (typically around 3000 rpm) in order to spread the fluid by centrifugal force. The rotation is continued while the fluid spins off the edges of the substrate, until the desired thickness of the coating is achieved. A separate drying step is added after the high speed spin to dry the coating without substantially thinning it. The thickness of the coating depends on the nature of the fluid and the parameters chosen for the spin process. The coating thickness varies between several hundreds of nanometres to ten micrometres. The schematics of the spin coating process are shown in Fig Page

52 Chapter 2 Literature review Figure 2-15 Stages of the spin coating process (a) placing small amount of solution on the substrate, (b) rotating the substrate at high speed, and (c) drying the film[111] Sol-gel HA coatings Sol-gel processing is widely used for depositing HA due to its low cost and convenient technique. Weng et al. [112] prepared sol-gel HA coatings on an alumina substrate and reported that the coating obtained at 500 ºC showed good crystallinity, adhesive strength, and dense morphology. Hsieh et al. [113] deposited HA coatings onto a Ti-6Al-4V substrate using sol-gel processing with rapid heating. A porous structure was reported on the outermost coating surface, with a pore size of 10-20µm. This structure, which is beneficial for the in-growth of living cells, arose due to the fast decomposition during rapid heating. Dense HA coatings were deposited onto a stainless steel substrate using sol-gel processing upon heat treatment of ºC by Liu et al. [114]. Zhang et al. [115] prepared uniform HA coatings on NiTi alloy via dip coating using a sol-gel procedure. They reported that sol-gel HA coatings formed on the surface of a porous NiTi alloy substrate, as well as inside the pores Optimization of HA coatings The plasma spray process has many variable parameters and it is important to optimise parameters to obtain quality coatings. Plasma spray process parameters may be optimised in a trial and error method, which is time consuming and inefficient use of resources. However, for superior coatings, it is necessary to understand the 32 Page

53 Chapter 2 Literature review scientific phenomena involved in the plasma spray process. Design of experiment (DOE) methods are a suitable technique that provides a maximum amount of information with the minimum number of experiments. The benefits of statistical design of experiments have been demonstrated by researchers in studies of plasma sprayed coatings for various materials such as zirconia [116], titanium nitride [117], alumina [76] and alumina-titania [118]. Recently, statistical design of experiments has been employed used by Dyshlovenko et al. [119, 120], Cizek et al. [66] and Tanay et al. [22] for plasma sprayed hydroxyapatite coatings Design of experiments (DOE) The statistical experiment approach is usually called design of experiment (DOE). The DOE method was introduced by Sir R. A. Fisher in the early 1920 s[121]. Fisher developed a method to carry out agricultural experiments in which the effects of properties, such as fertiliser, sunshine, and rain on a crop were determined. Further improvements in the DOE technique were brought about by Dr. Genechi Taguchi in the 1940 s [121]. A number of special orthogonal arrays were introduced that made the implementation of DOE easier. The DOE method has been applied across a wide range of disciplines since the 1920 s [22]. In the DOE technique, the parameters to be changed in the experiment are termed factors or variables [122]. The different possibilities for a factor are called the levels. Levels can be either qualitative or quantitative. The measured output from the experiment is termed the response. Once the experiment has been run, the effect of each factor can be evaluated by comparing the average response change with the factor changed. Responses can then be represented as a polynomial regression equation of the following form: (10) y= b + bx + b XX + b XXX 0 j j ij i j ijk i j k where i, j and k vary from 1 to the number of variables; coefficient b 0 is the mean of the responses of all the experiment; the b coefficient represents the effect of the j variable X j and b ij and b ijk are the coefficients of regression that represent the effects of the interactions of variable XX and i j XXX respectively [22]. i j k 33 Page

54 Chapter 2 Literature review In performing a designed experiment, there is a need for input process or machine variables to observe corresponding changes in the output process. The information gained from such experiments can be used to improve the performance of products. Figure 2-16 shows the general model of a process/system. Figure 2-16 General model of a process/system [123]. In every process there are some variables or factors that can be controlled easily, and some that are hard to control during normal production or standard conditions. In Fig outputs are performance characteristics that are measured to assess the process/product performance. During an experiment controllable variables can be varied easily and such variables have key roles to play in the process characterization. Uncontrollable variables, with small effects on process characterization, are difficult to control during an experiment. It is important to determine optimal settings of controllable variables to minimize the effect of uncontrollable variables [123]. Factors, levels and responses represent three aspects of design analysed by a design of experiment, as shown in Fig Factors (such as power, powder feed rate, stand-off distance) can be either controllable or uncontrollable variables. Levels include the settings of parameters. In this case, coatings are potentially influenced by the factors and their respective levels. Experiments are often designed in such a way as to avoid optimizing the process for one response at the expense of another. Based on this, the design of experiment technique can be shown as a flowchart as shown in Fig Page

55 Chapter 2 Literature review Figure 2-17 Coatings build up. Figure 2-18 Steps of design of experiment [124]. A number of different DOE methods have been developed, including factorial experiments and fractional factorial experiments, response surface methodology techniques, such as the central composite design and the Box-Behnken design, and Taguchi orthogonal arrays. The method selected for a particular experiment depends on considerations such as the objectives of the experiment, the number of factors being investigated and the resources available. The potential application of DOE in manufacturing processes includes [120]: 35 Page

56 Chapter 2 Literature review Improved process yield, stability and capability. Improved process net profits and return on investment. Reduced process variability and improved product performance. Reduced process design and development time that will ultimately reduce the manufacturing costs. Development of a relationship between key process inputs and output(s). Industrial experiments involve a sequence of activities [123], such as: Hypothesis: An assumption of responses and factors that motivates the experiment. Experiment: Identification required number of tests to investigate the hypothesis. Carrying out a number of identification tests to investigate the hypothesis. Analysis: Understanding the nature of data and performing statistical analysis of the data collected. Interpretation: Understanding the results of the experimental analysis. Conclusion: Determining, whether or not the originally set hypothesis is true or false Importance of design of experiments A conventional way to optimise a process is to change one factor at a time and check the response. This process consumes time and needs many experiments. Thus, there is a need for a process that can evaluate the effect of each factor on the resultant response with only a few experiments. Design of experiment fulfils this requirement. It can give much more information from a small number of experiments Factorial and fractional factorial experiments In a full factorial experiment, factors and levels are first identified and then all possible combinations of the levels of the factors are investigated. There can be a 36 Page

57 Chapter 2 Literature review wide range of factors, but limited factors are preferable, because a large number of factors increases the number of experiments to be conducted which is undesirable. Two-level full factorial experiments are the most common. In this type of experiment, factors are set at a low level (coded -1) and a high level (coded +1). A two level experiment with k factors is called a 2 k experiment. For example, a 2 3 experiment is used to study three factors at two levels and consists of 8 experiments. The design for a 2 3 experiment is shown in Table 2-7. Table 2-7 A 3 factor, 2 level factorial experiments [123]. Run X 1 X 2 X When carrying out experiments, there are some factors that have very little effect on the results and these types of factors need to be excluded from the experiment. Also, some factors may exist that are not of primary interest but still affect the results; these factors need to be eliminated. The effect of these factors can be eliminated from the overall results by organising the experiment into blocks. The effects of uncontrolled factors and unblocked factors can be eliminated by running the experiments in random order. Centre points are also usually added to factorial designs. These points are the centre value between the high (+1) and low (-1) values selected for each factor and are coded 0. The purpose of centre points is to allow process stability to be determined. Generally, between 3 and 6 centre points are added to an experiment design [22]. 37 Page

58 Chapter 2 Literature review Full factorial experiments are very efficient for a small number of factors. For a large number of factors, a fractional factorial is more efficient than a full series because it reduces the number of experiments. The reduction of experiments can be achieved by confounding the effects of some of the factors. However, due to the high order, interactions between factors cannot be estimated. This type of experiment is used to obtain information on the main effects as well as on low-order interactions and is also often used for screening designs [22, 123]. Fractional factorial design involves fewer experiments than the full 2 k run of experiments. A fraction of the number of runs is required for such an experiment; such as 1/2, 1/4, 1/6, 1/8 etc. The general term used for a fractional factorial design is 2 k-m, a 1/2 fractional factorial experiment is termed a 2 k-1 experiment, and a ¼ is a 2 k-2. A 2 5-2, i.e., 1/4 fractional factorial matrix is given in Table 2-8. Table 2-8 A 5 factor, 2 level fractional factorial experiments [22, 123]. Confounding Run X 1 X 2 X 3 X 4 = X 1 X 2 X 5 = X 1 X Taguchi orthogonal arrays Orthogonal arrays are used to study combinations of factors in the presence of noise factors. Signal to noise (S/N) ratios are calculated and used to make decisions about optimal parameter settings for each combination. Orthogonal arrays are helpful to minimize the number of runs needed for the experiment. Orthogonal arrays are optimized based on the signal to noise ratio. Signal to noise ratio is a metric term used to determine the magnitude of true output after making some adjustment for uncontrollable variation [125]. The S/N ratio is the ratio of energy that is transformed into the intended output to transform it into the unintended output. 38 Page

59 Chapter 2 Literature review S Ratio = N Power of Signal Power of Noise (11) There are 3 types of signal to noise ratio used in orthogonal arrays. (a) Type 1. Smaller the better: the response is continuous and positive. The most desired value is zero [126]. S 1 = -10log( y ) n N 2 i n i=1 (12) where y i is represented by a set of characteristic of y 1, y 2, y 3, y n. (b) Type 2. Nominal the best: the response is continuous and it has a non-extreme target response [126]. 2 y S = 10log( ) N V (13) where y is the average of a set of characteristics y 1, y 2, y 3, y n and V is the variance of data. (c) Type 3. Larger the better: this is the case for a continuous response, where the response needs to be maximum [126]. n 1 1 S = 10log( ) N (14) n y i= 1 2 i where y i is represented by a set of characteristics of y 1, y 2, y 3, y n Response surface methodology Response surface methodology is a statistical technique used for developing, optimizing and improving complex processes. It is a useful technique to minimize or maximise a response in a certain region. The two most popular response surface methodologies are a central composite design and the Box-Behnken design. 39 Page

60 Chapter 2 Literature review Central composite design (CCD): A central composite design (CCD) is a technique for factorial or fractional factorial design. Figure 2-19 shows the central composite design. Figure 2-19 Central composite design with cube points, star points and centre points[22]. A CCD design consists of three types of experiments [22]: Cube samples: these are the experiments that cross lower and upper levels of the design variables. They are the factorial or fractional part of the design. Centre samples: these are the replicates of the experiment that cross the mid-levels of all design variables. They are usually used to determine the experimental error of the design. Star (or axial) samples: these are used to make the design region spherical and are located at the midpoints of the faces of the factorial part of the design that are specific to CCD designs. The design matrix of a central composite design can be shown as follows [22]: B A = C D (15) B is either a 2 k factorial or 2 k-m fractional factorial experiment, where k is the number of factors and m is the number of factors that are confounded. C is a matrix with 2k rows, where all of the factors are set to 0, except one factor, which is placed 40 Page

61 Chapter 2 Literature review at the star point or axial point. The distance from the centre of the design space to the star point is ±α. The value of α depends on the type of centre composite design being used and also on the number of factors under investigation. The value of α can be calculated as follows [22]: 1 4 α = (2K) (16) DOE for plasma sprayed HA coatings Heimann et al. [36] studied the DOE method for optimum surface roughness, porosity, and tensile adhesion strength. Dyshlovenko et al. [119] used the DOE technique to examine the plasma spray preoaration of HA, and, later, a laser post spray treatment process. In another study, Dyshlovenko et al. [120] used a factorial design to investigate the relationship between plasma spray parameters and the microstructure of HA coatings. In their study, three responses were examined: (i) the fraction of HA, (ii) the fraction of decomposition phases, and (iii) the amorphous content of the coatings. Dyshlovenko et al. [119, 120] used the DOE technique for a small number of factors. Levingstone et al. [22] used response surface methodology to study the effect of five plasma spray process parameters (current, gas flow rate, carrier gas flow rate, powder feed rate, and stand-off distance) to optimise the coatings with respect to responses such as crystallinity, purity, surface roughness, and porosity. Table 2-9 shows previous DOE studies that concern in plasma sprayed hydroxyapatite coatings. 41 Page

62 Chapter 2 Literature review Table 2-9 Summary of DOE studies done on plasma sprayed HA coatings. Author Type of DOE Description Factors Responses Cizek [66] Taguchi 6 factors; 3 levels; 2 responses; 18 experiments; Power input; Primary gas flow rate; Secondary gas flow rate; Carrier gas flow rate; Powder feed rate; Stand-off distance; Temperature; Velocity; Dyshlovenko [120] 2 4 factorial design of experiment 4 factors; 2 levels; 3 responses; 16 experiments; Ar content of main gas flow; H 2 content of gas flow; Power; Spray distance; Fraction of HA phase; Fraction decomposition phase; Fraction amorphous phase; Dyshlovenko [119] 2 4 factorial design of experiment 4 factors; 2 levels; 3 responses; 16 experiments; Electric power; Ar content of main gas flow; Carrier gas flow; Laser power density; %HA; %α-tcp; %TTCP; Depth of Laser melt zone; 42 Page

63 Chapter 2 Literature review Levingstone [22] Response surface methodology 5 factors; 2 levels; 5 responses; 31 experiments; Current; Gas flow rate; Powder feed rate; Stand-off distance; Carrier gas flow rate; Crystallinity; Porosity; Roughness; Thickness; Purity; Heimann [36] Response surface methodology 5 factors; 2 levels; 4 responses; 28 experiments; Power; Primary gas flow rate; Secondary gas flow rate; Carrier gas flow rate; Spray distance; Thickness; Adhesion strength; Porosity; Roughness; 2.5. Indentation techniques Indentation techniques are used to determine hardness. Hardness is defined as the ratio of applied force to contact surface area or alternatively it is defined as the resistance to indentation. Hardness is a characteristic of materials, not a fundamental physical property. A smaller indentation indicates that the material is hard. A hardness value is obtained by measuring the area of indentation or depth of indentation. Researchers have proposed some modified microhardness techniques but the principle of the technique has remained the same. There are three main approaches for measuring hardness: scratch, rebound or dynamic, and indentation techniques. Among all these techniques, indentation is the most widely used method for measuring microhardness. In this technique, an indenter is pressed into the desired sample surface to be tested with a desired load and a microhardness measurement is made based on the size of indent area or depth of indent area. Typically, the indenter is made of hard steel, tungsten carbide, 43 Page

64 Chapter 2 Literature review or diamond in the shape of a sphere, cone or pyramid. The Brinell, Meyer, Rockwell, Vickers and Knoop hardness tests are examples of the indentation method Brinell hardness test In 1900, Dr. Johan August Brinell, a Swedish engineer, invented the Brinell hardness test, which is the oldest hardness technique. It is commonly used for materials that have too coarse a structure or too rough a surface; e.g., castings and forgings. It is mostly used on large parts. Brinell hardness results are measured by the permanent width of indentation created by the carbide or tool steel indenter with a specific load and time period onto a test specimen. An indentation is typically made with a Brinell hardness testing machine and then the indentation diameter is measured using an optical microscope. The measurement is converted to a Brinell value using the following formula [127]: 2P BH = (17) πd(d- D -d ) 2 2 where D is the ball diameter in mm, d is the impression diameter in mm, P is the load in kgf, and BH is the Brinell hardness number. Figure 2-20 shows the Brinell hardness testing technique. Figure 2-20 Brinell hardness testing [127]. The Brinell test typically uses a load of 3000 kgf and a ball with diameter of 10mm. Test loads can vary in the range of 500 kgf to 1 kgf. Ball diameter can vary in 44 Page

65 Chapter 2 Literature review the range of 10 mm to 1 mm. For a soft material such as aluminium, the test is performed with a 500 kgf load or 1500 kgf and a 10 mm ball is used to avoid excessive indentation [128]. Lower loads and ball diameters are normally used for convenience in combination testers. Brinell tests are defined in ASTM E10 [129] and ISO [130] standards. The test standard suggests a dwell time of s. The specimen should be about 4 times wider than the diameter of the impression. Also, the thickness of the specimen should be at least 15 times the depth of the indentation for softer metals and 10 times the depth of the indentation for hard metals [131]. A Brinell hardness number is expressed as 75 BH 10/3000/15, which indicates that a Brinell hardness of 75 was obtained with a 10 mm diameter ball using a 3000 kgf applied load for a period of 15 seconds. Brinell hardness tests are less influenced by surface scratches and roughness. The main source of error in Brinell testing is the measurement of indentation. The results may vary under perfect conditions due to operator errors and inconsistencies [127] Meyer hardness test In 1908, Meyer proposed that hardness should be expressed in terms of mean pressure between the surface of the indenter and the indentation [132]. His proposal can be explained as the load divided by the projected area of the indentation. Meyer Hardness can be expressed using the following formula [132]: 4P MH = (18) πd 2 where d is the diameter of resultant indentation in mm, and P is the applied load in kgf. The sensitivity of the Meyer hardness test is less compared to the Brinell hardness test. Meyer hardness follows a more fundamental measure of indentation hardness but its uses in practical fields are rare Rockwell hardness test The Rockwell hardness test was invented by Stanley P. Rockwell in It is the most popular method for a hardness test since it overcomes the limitations of 45 Page

66 Chapter 2 Literature review previous methods. In this method, indentations are made on the test material with a diamond cone or hardened steel ball indenter. Figure 2-21 shows the working principle of the Rockwell hardness test. A preliminary minor load (F0), usually 10 kgf, is applied to all the test material using an indenter. This load represents the reference or zero position. An additional load, named the major load (F1), is applied with the preload or minor load (F0), to reach the total required test load (F). These loads are held for a certain dwell time to allow for elastic recovery. Then, the additional major load is removed but the preload is still retained. Then, the Rockwell hardness (HR) number is calculated using the equation below [133]: HR = E-e (19) where e is the indentation depth created by the minor load and E is indentation depth created by the major load. Figure 2-21 Rockwell working principle [133]. Rockwell hardness has no units and is normally expressed in 30 different scales (A, B, C, D etc). The most widely used scales are B and C scales for testing brass, steel and other metals. Rockwell hardness is expressed as 60 HRB which indicates that the specimen has a hardness reading of 60 on the B scale. The hardness of hard plastics (nylon, polycarbonate, polystyrene, and acetal) is most commonly measured using the Rockwell hardness test [134]. The following standards are defined by the Rockwell hardness test: ASTM D785 plastics [135], ASTM E18 metals [136], and ISO metals [137]. 46 Page

67 Chapter 2 Literature review Vickers hardness test In 1925, the Vickers test was developed in England by Vickers Ltd [138]. It is also known as the Diamond Pyramid Hardness Test. This method is the most commonly used technique. In this method, tested materials are indented using a diamond indenter in the form of a right pyramid with a square base and an angle of 136º angle between opposite faces, Figure It covers force ranges of micro load (10 gf to 1000 gf) and macro load (1 kgf to 100kgf) using the same indenter shape for both of these ranges. It is useful for testing many materials as long as the samples are prepared carefully. It is useful for a variety of applications, such as: testing small parts or small areas, measuring the surface of a part, testing thin materials such as foils, measuring individual microstructures, measuring the depth of case hardening by sectioning a part, and making a series of indentations to describe a change of hardness. Figure 2-22 Vickers hardness testing [139]. The Vickers testing method is similar to the Brinell test. It uses a penetrator that is square in shape, but tipped in one corner, so that it has the appearance of a playing card diamond rather than using the Brinell steel ball-type indenter and calculating the hemispherical area of impression in the Brinell hardness test. The indenter was suggested by Smith et al. [140]. 47 Page

68 Chapter 2 Literature review Sample preparation is important for this test to provide a small sample that can fit into the tester. The sample tested surface needs to be smooth since the measurement system is optically based. The indentation should be large enough to maximize the measurement resolution. Error percentages decrease with an increase in indentation sizes. In this test, vertical and horizontal axes are measured after indentation. Then, this measurement is converted to a Vickers hardness number, using the following formula [141, 142]: P VH = (20) d 2 where d is the arithmetic mean of two diagonals d 1 and d 2 in mm, P is the applied force in kgf, and VHN is the Vickers hardness number. The Vickers test is a non-destructive technique; however, the test is slow. The Vickers test methods are defined in the following standards: ASTM E384 (micro force ranges: 10 g to 1 kg) [143], ASTM E92 (macro force ranges: 1 kg to 100 kg) [144] and ISO (micro and macro ranges) [138, 145] Knoop hardness test The Knoop hardness test was developed by the National Bureau of Standards (NIST) in The test load varies from 10 g to 1000 g. It is mostly used for sections, small parts, and case depth work. Figure 2-23 shows Knoop hardness testing with a pyramid-shaped indenter, which is more elongated than the indenter used on the Vickers test. The long side faces are set at a 172º30ˊ angle to one another. The short side faces are set at a 130º angle to one another. In this test, only the long axis is measured, rather than measuring the vertical and horizontal axes, as in the Vickers test. Then, this measurement is converted to a Knoop hardness number using the following formula [146, 147]: P KH = (21) L 2 where L is the measured length of the long diagonal of the indentation in mm, and P is the applied load in kgf. 48 Page

69 Chapter 2 Literature review For a given material and load, the Knoop indenter may penetrate approximately half as much, and the diagonal dimension may be 3 times higher as that achieved by the Vickers indenter [148]. A high magnification is required in the Knoop test to dictate and measure the Knoop indents on a highly polished surface. Samples are normally mounted and polished to achieve this surface. Therefore, the Knoop test can be considered as a destructive test. The Knoop test allows the hardness testing of brittle materials such as ceramics and glass. The test values are mostly load independent over 100 gf. The hardness testing can take 30 seconds. This test method is well defined in ASTM E384 [143] and ASTM D1474 (hardness of organic coatings) standards [149, 150]. Figure 2-23 Knoop hardness testing [149] Leeb hardness test The Leeb is the modern electronic version of the Scleroscope. It is also known as an Equotip. A carbide ball hammer with a spring is used in this test. The velocity of the hammer is measured by an electronic sensor. The hammer travels towards and away from the surface of the sample. The Leeb value can be expressed as follows[151]: 49 Page

70 Chapter 2 Literature review Hammer rebound velocity Leeb value = Impact velocity 1000 (22) The Leeb hardness values are in the range of 0 to 1000 and can be converted to other hardness scales such as Rockwell and Vickers numbers. A wide range of materials can be tested using this hardness test. However, the tested parts must have a good finish and a minimum weight of 5 kg. It is portable and can be used at different angles as long as they are perpendicular to the test surface. The Leeb test methods are well defined by ASTM A956 standard [152] Microhardness study on thermal spray coatings Thermal spray coatings are widely used in various industrial sectors, such as in agricultural implements; automotive; aerospace; primary metals; mining; chemicals and plastics; paper; oil and gas production; and biomedical applications [ ]. For these applications, the quality of the coatings is of prime importance. Also microhardness techniques are the key and most suitable technique to determine the quality of coatings for a certain application [156]. Microhardness is the major qualitative technique used for characterizing thermal spray coatings. It has also been used for optimizing spray parameters [ ]. It has provided a convenient means for clients to compare the coatings sprayed with different techniques. It is also useful for quick estimations for the strength of coatings [160]. Lin et al. [142] reported microhardness variations in thermal spray coatings with respect to applied load and measurement direction, using Vickers indentation to understand and delineate the hardness and its relationship with the microstructure of the coatings. They reported a bimodal distribution for small loads in coatings of metal-metal mixtures. Their studies indicated that the large load reflected small average microhardness and large Weibull modulus. Lima et al. [161] analysed the distribution of hardness for HVOF sprayed titania coatings using Vickers indentation. They reported near-isotropic behaviour for a plasma sprayed titania coating, and that the origin of this near isotropy could be due to the characteristics of the HVOF process. Their investigations also summarised a high Weibull modulus for titania coatings compared to other coatings, due to the following factors: narrow particle size distribution selection, the HVOF process, 50 Page

71 Chapter 2 Literature review uniform particle temperature, non-lamellar uniform microstructure, and a near singlephase coating. Their results indicated that top surface microhardness is higher compared to the cross-section. These differences arise since thermal spray coatings are formed by a successive overlapping of splats, and the resulting complex microstructure is expected to have different features when examined in top surface and cross-section orientations. The recommendation of engineering literature on thermal spray coatings is that the hardness values measured on the cross-section should not be compared with the top surface values, due to the anisotropic characteristics of the coatings [61]. Figure 2-24 shows the homogeneous structure of the top surface and crosssection of HVOF titania coatings. Buchman et al. [162] investigated the microstructure of HVOF and air plasma spray (APS) titania coatings and concluded that the top surface and cross-section of HVOF coatings exhibited a homogeneous microstructure, whereas APS titania coatings revealed a heterogeneous microstructure. Figure 2-24 HVOF titania coatings (a) top surface, and (b) cross-section [162]. Microhardness variation of alumina coatings with the change of indent location, measurement direction, and applied loads were studied and analysed statistically by Yin et al. [163]. They examined the hardness distribution with change of indent location throughout the coating cross-section under an applied load of 50 gf. Their results showed that microhardness data varied within the coatings and the measured microhardness data set follows Weibull distributions. Microhardness values were higher on the cross-section than the top surface. The decrease of microhardness value with the increase of applied load was explained in terms of the Kick s law and 51 Page

72 Chapter 2 Literature review the Meyer s index k of The Weibull modulus value indicates that microhardness data are less variable on the cross-section of a coating at higher load. To assess the engineering reliability of a coating system, statistical analysis is a very popular technique. Valente et al. [156] used statistical analysis (Student s t-test, Fisher s test, Gaussian distributions, Weibull distributions, and Meyer s theory) to assess the heterogeneity of thermal sprayed ceramic (WC-12%Co) and metallic (Ti- 6Al-4V, CoNiCrAlY) coatings under three different loads (100, 300, and 500 gf). They reported that ceramic coatings show load-hardness dependence due to their brittle nature; whereas metallic coatings show a bimodal distribution at small loads. Lin et al. [164] also used statistical analysis (Gaussian and Weibull distributions) to characterize thermal spray coatings of NiCoCrAlY bond coat and cerium-stabilised zirconia. Vickers hardness distribution on WC-12%Co thermal spray coatings was analysed by Factor et al. [165]. They analysed the microhardness data using Gaussian and Weibull statistical models. They concluded that Weibull statistics are more generally appropriate than Gaussian distributions for the heterogeneous thermal spray coatings. They concluded that a true population average is required for the microhardness data, since microhardness data show wide scatter that are difficult to assess on the basis of the mean microhardness value. Therefore, they suggested a Student s t-test and analysis of variance (ANOVA) test for the comparison of microhardness data sets. In another study, Factor et al. [166] examined the between-operator reproducibility of microhardness statistics using Vickers indentation. They used eight different personnel to check the between-operator reproducibility. They summarised microhardness readings performed by different operators by means of ANOVA analysis and concluded that there is a consistent, statistically significant variation. To overcome operator caused repeatability, they suggested the methods listed below: Measuring hardness under increased load. Addition of correction factor. Measurement based on automated system image analysis. 52 Page

73 Chapter 2 Literature review Use of near-field microscopy, confocal microscopy and atomic force microscopy. Measurement using scanning electron microscopy (SEM) with high magnification. Use of Knoop indentation under increased load. Ultrasonic microhardness testing. Scanning microhardness (depth analysis). Other technique such as superficial Rockwell A indentation, Hardel s large spherical probe-minimal penetration indentation procedure, instrumented scratch testing. The Knoop indentation technique is used widely to investigate microhardness as well as the elastic modulus of thermal spray coatings. Lima et al. [167] examined the Knoop microhardness distributions for nanostructured partially stabilized zirconia (PSZ) coatings, and analysed the distributions using Weibull statistics. The microhardness data of the nanostructured PSZ coating presents bimodal distributions in Weibull plots, whereas conventional PSZ coatings exhibit monomodal distributions, as shown in Fig Figure 2-25 Comparison of Weibull plots of (a) conventional PSZ coatings, and (b) nanostructured PSZ coatings [167]. 53 Page

74 Chapter 2 Literature review Bimodal distributions for nanostructured PSZ coatings indicates two phases that could be molten and non-molten. These two phases arise due to the nucleation rates and rapid cooling rates of molten thermal spray particles [168, 169]. Microhardness data were measured on the molten region and non-molten region. The predicted microhardness shows good agreement with the measured microhardness. The microhardness was predicted from the following rule of mixtures formula: Predicted Microhardness = H11 f + H2f 2 (23) where f 1 and f 2 are the percentages (fractions) of the non-molten and molten region in the overall coating microstructure; and H 1 and H 2 are the microhardness values of the non-molten and molten regions. Knoop microhardness and elastic modulus were examined by Li et al. [170] for plasma sprayed Cr 3 C 2 -NiCr coatings. The effects of the coating process, indenter loads, and measurement directions were considered for investigation; and statistical analyses were carried out to describe the results. Their results indicated that Knoop microhardness values were lower when the major diagonal of the indenter was parallel to the interlamellar boundary of the coatings, compared to the vertical position of the major diagonal. Their elastic modulus data were much more scattered compared to the microhardness data since the elastic modulus measurement contained systematic errors. Elastic modulus was also examined by Leigh et al. [147] using Knoop indentation for a variety of thermal spray coatings such as (i) alumina (Al 2 O 3 ), (ii) yttria-stabilised zirconia (YSZ), and (iii) metallic, intermatilcs, and cermet (NiAl) coatings. They reported that the elastic modulus of thermal spray deposits was in the range of 12-78% of the comparable bulk materials and revealed the anisotropic character of thermal spray deposits. The APS-processed deposits exhibited much lower elastic modulus values than the vacuum plasma spray (VPS)-processed deposits, due to the lower porosity, a lower oxidation (for metallic deposits), and the relatively denser intersplat boundaries of VPS-processed coatings. The elastic modulus values were changed after heat treatments that were associated with microstructural changes in porosity, pore morphology, and interlamellar structures. 54 Page

75 Chapter 2 Literature review Errors in microhardness testing for thermal spray coatings The accuracy of the microhardness test depends on many factors, such as flatness, surface finish, specimen dimension, operator error, and calibration error. Among these, flatness is the most important factor and a maximum angle of approximately ±1 would be regarded as acceptable. Surface grinding and machining may be necessary to achieve the required flatness. There should not be any friction in the loading system since it can produce a smaller impression than the expected impression. The condition of the indenter is also important. The duration of applied load is important and must be controlled. Regular maintenance and calibration of the machine is, therefore, essential. The dimension of the specimen is also important since a test specimen that is too thin would influence the microhardness values. According to the rule of thumb, the specimen thickness should be twice than that of the Vickers diagonal. Also the specimen table should be tightly fixed to the machine. Figure 2-26 shows the factor that influences the microhardness results for thermal spray coatings Summary HA is well accepted as a bioactive, biocompatible and bioresorbable material closely resembling the mineral phase of bone and hard tissues in the human skeleton. Thus, HA can form a strong implant-bone interfacial bond to improve the prosthesis fixation. HA also has the ability to avoid releasing metal ions, a feature that has further increased interest. This literature survey has shown that plasma spray power, stand-off distance, and powder feed rate are important factors that influence coating properties. Many studies have been performed to understand the effects of these process parameters on coating properties. However, very few have considered the mechanical properties of the coating in terms of responses such as microhardness, and other important responses, such as deposition efficiency. It is necessary to understand the microhardness distribution to fully understand the thermal spray microstructure. In the literature, several studies were conducted to understand microhardness distribution using the indentation technique and statistical 55 Page

76 Chapter 2 Literature review Figure 2-26 Cause-effect diagram of microhardness measurement for thermal spray coatings (based on Erne et al. [171]). 56 Page

77 Chapter 2 Literature review analysis. However, more studies are necessary to understand the effects of applied load throughout the coating thickness. There is also a need to understand indenter tip roughness variation within the coatings. Coatings prepared by sol-gel techniques are usually uniform, while plasma sprayed coatings are full of pores and cracks. Therefore, it may be possible to fill in the pores and cracks of the plasma sprayed HA coatings using sol-gel dip coatings. The microstructures and mechanical properties of the plasma sprayed HA coatings could be enhanced through surface modification by employing sol-gel dip coatings in conjunction with plasma sprayed coatings. 57 Page

78 Chapter 3 Experimental equipment, procedure, and materials characterization 3. Experimental equipment, procedure, and materials characterization 3.1. Plasma spray system The plasma spray equipment used in this work was an atmospheric plasma spray system installed in United Surface Technology (UST) Pty Ltd, Australia. The booth with plasma spray equipment is shown in Fig Figure 3-1 Plasma spray booth. There are four main components in the booth: Plasma torch Control and instrumentation system Powder feeder unit and Gas supply system 58 Page

79 Chapter 3 Experimental equipment, procedure, and materials characterization Plasma torch The plasma torch used in this research was the SG 100 (Praxair, USA) with an internal powder injection mode, Figure 3-2. The torch is attached with a machine mountable base that allows the torch to move frequently. Figure 3-2 Plasma spray torch SG 100. Control and instrumentation system The control system shown in Fig. 3-3 was the Plasmadyne 3600 (California). This unit controls the plasma voltage, current, primary gas flow rate, secondary gas flow rate, and carrier gas flow rate. 59 Page

80 Chapter 3 Experimental equipment, procedure, and materials characterization Figure 3-3 Control system. Powder feeder unit The powder feeder used was the 3MP Plasmadyne dual rotating powder hopper 1275 (California), Figure 3-4. This unit controls the powder feed rate. The powders for spraying are stored in the powder hopper are transported to the torch by a carrier gas. Gas supply system The gas supply system with argon and helium cylinder are shown in Figure 3-5. Primary and secondary gases are stored in composed cylinders outside the main factory. 60 Page

81 Chapter 3 Experimental equipment, procedure, and materials characterization Figure 3-4 Powder feeder unit. Figure 3-5 Gas supply system. 61 Page

82 Chapter 3 Experimental equipment, procedure, and materials characterization 3.2. Feedstock morphology Captal 60/1, thermal spraying hydroxyapatite powder supplied by Plasma Biotal Ltd (UK), was used in this study. This HA powder was produced for thermal spray applications. The powders have a mean particle size of 45±10 µm, d(10) of 20±5 µm, d(90) of 80±10 µm. Figure 3-6 shows hydroxyapatite powder morphology and particle size distribution. Powders are composed of spherical and angular morphologies Preparation of substrate and coating cross-sections Substrate Mild steel substrates were used for plasma spraying of HA. The substrate was flat with a size of mm Grit blasting and substrate cleaning procedure Substrate surface condition plays a major role in depositing thermal spray coatings. The substrate was kept in an ultrasonic cleaner with acetone solution for 15 minutes. The substrates were grit blasted prior to spray coating. The grit blasting procedure was carried out using 500 mesh pure alumina (Al 2 O 3 ) at a blast pressure of 0.5 MPa until the surface was uniformly roughened. The stand-off distance of the blasting was varied between mm. Plasma spray coating was performed immediately after completion of grit blasting Coating mounting, grinding and polishing The HA coated samples were sectioned by an automatic cutter to allow their cross-section to be examined. A high speed precision cutting machine (Secotom 50, Struers, Australia) was used for sectioning samples, Figure 3-7. Then, the samples were mounted in epoxy resin for firm holding during grinding and polishing. The resin used was Buehler epoxide resin and Buehler epoxide hardener that were mixed at a ratio of 5:1. The samples were placed in moulds with a clip to make the sample stable. Then, the moulds were filled with the resin slowly and care taken to maintain the desired sample orientation. They were cured at least 24 hours prior to removal from the moulds. 62 Page

83 Chapter 3 Experimental equipment, procedure, and materials characterization Volume frequency (%) b % (Volume) % (Cumulative) Cumulative frequency (%) Particle diameter (um) Figure 3-6 HA powder (a) morphology, and (b) particle size distribution. 63 Page

84 Chapter 3 Experimental equipment, procedure, and materials characterization Specimens were ground using a Buehler grinder by P240, P320, P400, P600, P800, and P1200 grit SiC papers, followed by polishing on the Buehler Microcloth polisher with 15, 5, and 1 µm diamond pastes. Grinding was carried out using each sand paper until the damage caused by the sectioning of the HA coated samples was completely removed; with the sample being planar and exhibiting polishing makes in the same direction. When a change of paper or cloth occurred, the sample was rotated to 90º and then polished until uniform scratches were visible. The speed of the grinding and polishing machine was varied in the range of rpm. The grinding machine used in this study was the Leco VP 150. The polishing machines used were the Leco GP 25 (coarse polishing 15 and 5 µm) and the Leco VP 160 (smooth polishing 1 µm). The grinding and polishing machines are shown in Fig. 3-8 for reference and archival purposes. Figure 3-7 Automatic Struers cutter. 64 Page

85 Chapter 3 Experimental equipment, procedure, and materials characterization Figure 3-8 Metallographic preparation (a) grinding (P240-P1200), (b) coarse polishing (15 and 5 µm), and (c) smooth polishing (1 µm) Characterization of HA coatings Scanning electron microscopy (SEM) & energy dispersive X-ray spectroscopy (EDS) Plasma spray coated specimens, polished cross sections, and powder morphology were observed using a field emission scanning electron microscope (FESEM or SEM, ZEISS Supra 40 VP), Figure 3-9. The samples tested for SEM should be appropriate to fit inside the SEM specimen vacuum chamber. HA is a nonconducting material. Thus, surface of the sample must be electrically conductive otherwise charging effects may arise during scanning. Thin gold coatings are widely used to make the surface conductive. All samples studied in this research were gold coated with a DYNAVAC (CS 300) deposition system prior to the SEM analysis. 65 Page

86 Chapter 3 Experimental equipment, procedure, and materials characterization Figure 3-9 Scanning electron microscopy (SEM). The sample was mounted on a sample holder using a carbon tape that made a connection between the sample holder and thin gold coating. After completion of gold sputtering, the sample was placed under the SEM observation as quickly as possible. The sample was kept in a vacuum between the gold sputtering and SEM observation. The scanning parameters used in this study are shown in Table 3-1. Table 3-1 Parameters used for SEM analysis of HA coatings and HA powder. Parameters Value Accelerating voltage (kv) 3-15 Magnification (x) Working distance (mm) Energy dispersive X-ray spectroscopy (EDS) is an analytical technique. It is also referred to as EDX analysis. The elemental composition of a specimen can be analysed using EDX. The EDX analysis system used in this study worked as an integrated feature of the SEM X-Ray diffraction (XRD) The phase components in the HA coatings were determined by X-ray diffractometry (XRD, Bruker D8 Advance Diffractometer), Figure The obtained 66 Page

87 Chapter 3 Experimental equipment, procedure, and materials characterization d-values were compared with the characteristic d-values taken from JCPDS cards to identify various X-ray peaks. In order to carry out the scan, samples were mounted on a sample holder using double-sided tape. The sample holder was then placed on the XRD slot. ASTM F2024 [172] was followed to carry out the scan of HA coatings and powder. Parameters used for the XRD scan are shown in Table 3-2. Figure 3-10 X-ray diffractometry (XRD). Table 3-2 Parameters used for XRD analysis of HA coatings and HA powder. Parameters Value Range 20-60º Increment 0.02 Scan speed 1º/min Voltage 40 kv Current 40 ma 67 Page

88 Chapter 3 Experimental equipment, procedure, and materials characterization Raman spectroscopy Raman spectroscopy is a non-destructive method. The sample preparation for this method is minimal. The composition, chemistry, and structure can be obtained from the spectra generated from the specimens. Micro-Raman scattering experiments were performed via the Raman spectrometer (Renishaw plc, UK) shown in Fig The analyses were conducted with an excitation wavelength of 514 nm over a spectrum of range cm -1 with cosmic ray removal. The resolution was 1 cm -1 and 10% power was used for 10 seconds. Figure 3-11 Raman spectroscopy system Profilometer A profilometer allows the measurement of surface roughness. Surface roughness of the coatings was measured using the Surtroic 25 (Taylor Hobson, UK) profilometer, Figure This is a 2D profilometer that has a stylus that is run over the surface of the coating. Accuracy of the roughness tester was checked prior to the measurement with a calibration sample. After indentation using a Vickers indenter, the indenter tip roughness was measured using a 3D profilometer (Bruker AXS ContourGT-K) with Vision 64 analysis software, Figure Page

89 Chapter 3 Experimental equipment, procedure, and materials characterization Figure 3-12 Two dimensional profilometer Analysis of coatings Figure 3-13 Three dimensional profilometer Porosity measurements The porosity of a coating is an important factor that describes the inherent characteristics of the coating. Porosity is most important for orthopaedic applications. The level of porosity required depends on the application. There is no required level of porosity specified by the Food and Drug Administration (FDA). To obtain good mechanical properties, a porosity of less than 5% is preferable. Sun et al. [69] stated 69 Page

90 Chapter 3 Experimental equipment, procedure, and materials characterization that the porosity of commercially available plasma sprayed HA coatings can be as high as 50%. The porosity of HA coatings can be calculated from high resolution microscope images of the cross-section of the coated sample. The pore area fraction can be calculated manually by drawing a calibrated grid on the microscope image. The following equation is then used to calculate the pore area fraction [22]: 1 (x + x ) A = (24) y where A is the area fraction, x is the number of intersections of the grid that fall within a pore, x 1 is half the number of intersections of the grid that fall on a pore boundary, and y is the total number of grid intersections in the field of view. Image processing and analysis in Java (ImageJ) v1.46p software from the National Institutes of Health (NIH) was used to calculate the pore area fraction. This software allows the pores in the coating to be highlighted and the pore fraction of the coating can then be calculated by the software. First of all, it is necessary to set up the scale of the image. Secondly, the threshold value needs to be adjusted so that all the pores are highlighted. The image then needs to be smoothed to resolve the pores. After that, particles are analysed to measure the area fraction or porosity of the coatings. The British standards institution (BSI) standard testing method for the determination of the porosity of ceramics coatings is outlined in draft documents (DD) European pre-standard (ENV) :1995 [173] Microhardness and elastic modulus measurements Hardness is defined as the ratio of applied force to contact surface area. Vickers and Knoop hardness testers are very popular for microhardness measurements. The Vickers test is a non-destructive test. Micro force ranges from 10 g to 1000 g. The test point is highly finished to allow a clear image for accurate measurement. The test is very slow and the indent size is optically measured. The Vickers hardness number can be calculated using the following formula: P VH = (25) d 2 70 Page

91 Chapter 3 Experimental equipment, procedure, and materials characterization where P is the force applied to the indenter in kgf and d is the mean diagonal of the indentation in mm. The Knoop microhardness and elastic modulus were determined following the theory proposed by Marshall et al. [146] and Leigh et al. [147]. The Knoop microhardness measurement can be obtained from the following formula: P KHN = a 2 (26) where P is the applied load in grams, a is the major diagonal length of the Knoop indentation given in micrometres, and KHN is the microhardness number. The elastic modulus can be calculated by the following formula: b b b ' αkhn = - (27) a a ' a ' E where α is a constant and is taken as 0.45; a and b are the major and minor diagonals of the Knoop indentation; a' and b' are the major and minor diagonal of ideal Knoop indentation, b' 0.14 a' = ; and E is the elastic modulus and KHN is the microhardness number Deposition efficiency measurements Deposition efficiency (DE) of the coatings has been measured by the following equation: Mass of the coatings DE = Powder feed rate Time required during the spray process (28) The substrate weight was measured before and after the coatings to measure the mass Crystallinity measurements Crystallinity of a coating is important. According to the ISO standard specification (ISO [49]), the crystalline content should be greater than 45% for a HA coating to have sufficient mechanical properties in vivo. For medical applications, the required crystallinity is more than 95%. In general, the crystallinity of HA plasma 71 Page

92 Chapter 3 Experimental equipment, procedure, and materials characterization spray coatings vary from 65% to 70% for biomedical use [79]. Dalton and Cook [174] found crystallinity varied between 57% and 61% by comparing four commercially available plasma spray coatings. There are three methods used to measure the crystallinity of a coating achieved by X-ray diffraction: The Relative intensity method [70] The Rietveld method [175, 176] The Rutland method [68, 69, 71] In this study, the Rutland method was used since it is a commonly used method for determining crystallinity. According to this method, crystallinity is defined as the ratio of crystalline area to the total area; i.e., summation of crystalline ( A ) and amorphous ( A ) areas under diffraction pattern, which can be presented in the following form: a c c Crystallinity (%) = 100% c A A+ A a (29) Surface roughness measurements The roughness of a coating is important because bone growth depends on this physical characteristic. Osteoblast cell attachment is affected by the surface roughness of the HA coatings. The bone growth on the coating is affected by the surface roughness once it is implanted into the body. Powder particles used in the coating affects the coating roughness and coating thickness also influences the roughness. Gross and Babovic [177] demonstrated that partially melted particles were not able to flatten on the coating surface, giving rise to large undulations and thus higher coating roughness. Osteoblast cells attach and proliferate better on rough surfaces, whereas fibroblasts and epithelial cells prefer smooth surfaces [178, 179]. The 72 Page

93 Chapter 3 Experimental equipment, procedure, and materials characterization roughness [180] of the surface of HA coating can be calculated using the following formula: 1 y dx 0 R= a L (30) where R a = average surface roughness The R a parameter is the average distance between the surface of the coating and the mean line, as shown in Fig Y R a X Figure 3-14 The R a parameter. 73 Page

94 Chapter 4 Relationship between process parameters according to literature survey 4. Relationship between process parameters according to literature survey 4.1. Introduction Thermal spraying is a well-established technology for the production of overlay protective coatings and is used extensively for metallic and ceramic coatings in industry to operate under extreme conditions of wear, corrosion and hightemperature exposure. More recently, multilayer coatings have been considered for functional surfaces. Atmospheric plasma spraying is one of these processes. Plasma spraying, a complex deposition method, involves a myriad of process parameters, equipment, and powder parameters, which have a direct effect on the coating properties [181, 182]. To develop new functional and reproducible coatings, an empirical approach is often adopted to identify those processing parameters that have significant effect on the coating properties. This process is expensive and time consuming. The requirement in industry is the reliability and reproducibility of the coatings, as well as the establishment of a knowledge base of their intrinsic material properties and behaviour [ ]. Thus, there is a need to develop strong scientific correlations among these parameters to accomplish the requirement of prime reliant coatings. This requires a concerted, integrated interdisciplinary approach, and this chapter demonstrates such an approach for a specific spray system and material, and focuses on establishing the relationships between process parameters, such as power, powder feed rate, stand-off distance and powder particle size Methodology Data were collected from the available published literature [3, 7, 22, 55, 66, 68, 78, 92, 119, 120, 175, ]. 74 Page

95 Chapter 4 Relationship between process parameters according to literature survey 4.3. Results & discussions Relationship between power and stand-off distance To prepare a relationship between power and stand-off distance 89 data [3, 66, 69, 78, 119, 120, 175, 186, 187, 192, 195, 197, 198, , 205, 208, 209, , , 220, 223, 225, 228, , 236, 237, , , 251, 252, 260, 262, 263] have been collected and used to plot the graph shown in Figure 4-1. Figure 4-1 (a) indicates that, for hydroxyapatite, as the power increases, stand-off distance needs to increase. The fitted equation shows an adjusted R squared value 0.22 due to the scattered data. To improve the R squared value, the averaged data was used. Figure 4-1 (b) shows the graph with average SOD vs. power. However, this approach does not improve the R squared value. The third analysis removed the outlier points that were considered unrepresentative of the data sets. For instance, some of the literature values demonstrated poor microstructures that would gave rise to poor performance. After excluding outlier points and poor data, Fig. 4-1 (c) indicates an improved R squared value of From Fig. 4-1 (c), it can be seen that the fitted equation suggests a power range of 5-43 kw and a stand-off distance of 5-23 cm for hydroxyapatite coatings. This provides a guideline for selecting appropriate process parameters to achieve high quality hydroxyapatite coatings Relationship between power and powder feed rate Figure 4-2 shows the relationship between power and powder feed rate for hydroxyapatite coatings. Fifty data [78, 119, 186, 189, 190, 192, 195, 197, 201, 202, , 208, 209, 211, 212, 222, 223, , 237, 239, , 248, 249, , ] were collected from the literature. This graph shows a range of power of kw and a powder feed rate of 8-43 g/min. The fitted equation shows a good match with these 50 data points with a R squared value of Page

96 Chapter 4 Relationship between process parameters according to literature survey Figure 4-1 Relationship between power and stand-off distance (a) with all data, (b) with average data, and (c) with good data. Figure 4-2 Relationship between power and powder feed rate. 76 Page

97 Chapter 4 Relationship between process parameters according to literature survey Relationship between power and powder particle size Figure 4-3 shows the relationship between power and powder particle size with 38 data [66, 119, 175, , 190, 193, 197, 198, 201, , 208, , 225, 229, 231, , 239, 243, 246, 247, 249, 259, 260, 265]. In this study, data from the literature relating to powder particle sizes were divided into the following three categories: Fine particles (<45 µm) scaled as 1 Medium particles (45-75 µm) scaled as 2 and Coarse particles (>75 µm) scaled as 3 Figure 4-3 Relationship between power and powder particle size. This graph shows increasing particle size initially requires an increase in power level. A maxima appears at a power of 31 kw for coarse particles. It is noteworthy that low power (~10-15 kw) and high power (~35-40 kw) levels have been used for fine HA feed stocks. 77 Page

98 Chapter 4 Relationship between process parameters according to literature survey Relationship between powder feed rate and powder particle size Figure 4-4 shows the relationship between powder feed rate and powder particle size with 27 data [22, 186, 188, 191, 192, 196, 197, 199, 201, , 224, , 237, 239, 245, 254, 255, 257, 259]. An increase in powder feed rate can be used as the powder particle size increases initially. A maximum feed rate of 33 g/min has been achieved for coarse particles; whereas medium particles may be feed at rates of up to 45 g/min. Figure 4-4 Relationship between powder feed rate and powder particle size Summary A relationship between plasma spray process parameters has been developed. These relationships enable selection of appropriate process parameters rather than a trial and error approach. The relationships developed in this critical analysis of the literature were used in this current study to implement the plasma spray protocol. 78 Page

99 Chapter 5 Taguchi design of experimental study on HA coatings 5. Taguchi design of experimental study on HA coatings Materials from this chapter have been accepted in the following journal: Hasan, Md. Fahad; Wang, James; Berndt, C.C.; 2014, A Taguchi design study of plasma sprayed hydroxyapatite coatings. Materials Science Forum, vols , pp (In press) 5.1. Introduction Plasma spraying, a complex deposition method, involves a myriad of process parameters, equipment, and powder parameters that have a direct effect on the coating properties [181, 182]. An empirical approach is often adopted to identify those process parameters that have a significant influence on the coating properties. The conventional trial and error optimization process is expensive and time consuming. Thus, there is a need to develop strong scientific correlations among the prime thermal spray parameters that permit the manufacture of quality coatings. Statistical design of experiment methods has been demonstrated to be a costeffective and time-efficient technique, with the means to systematically investigate process parameters. Researchers [22, 66, 119, 120, 266] have used Taguchi, response surface methodology, and factorial design to optimize plasma sprayed hydroxyapatite coating properties in terms of porosity, crystallinity, purity, adhesion strength, roughness, and thickness. There have been a limited number of studies that have focused on deposition efficiency and mechanical properties such as the microhardness of plasma sprayed HA coatings: the focus of this current investigation. High deposition efficiency is related to the economic manufacture of thick and large-scale coatings under shorter process times [267]. Microhardness is important since it is a material property that is related to coating performance and reliability. The Taguchi design of experiment method is an effective and time saving procedure that employs a smaller number of experiments for process optimization. In this study, a Taguchi L 9 (3 4 ) design has been used that allows to understand the influence up to 4 different independent variables with each variable having 3 set of values. Among many process parameters of plasma spray; the power, powder feed rate, and stand-off distance have been identified as parameters that strongly 79 Page

100 Chapter 5 Taguchi design of experimental study on HA coatings influence the coating properties. Secondary gas flow rate is related to power, and carrier gas flow rate is related to powder feed rate; thus, these related parameters have been combined as one factor in order to indicate a co-dependence Methodology Taguchi L 9 design of experiments (DOE) was used in this study, as this design needs a small number of experiments compared to other designs for 3 factors with 3 levels each to optimise coating properties. The literature study reveals that power, powder feed rate, and stand-off distance are the most influential factors in terms of altering the coating properties. Process parameters were selected based on the literature review. Power was selected as an independent variable, while stand-off distance and powder feed rate were corresponding dependent variables. All data collected from the literature (shown in Sections and 4.3.2) were used to plot a graph, fit them, and establish a relationship using Origin v9 software (OriginLab, Northampton, MA), as shown in Fig From the graphs, different levels of power of 20, 30 and 40 kw, and their corresponding values of stand-off distances, and powder feed rates were selected and used for plasma spraying, as shown in Table 5-1. These selected process parameters are indicated as a red circle on these graphs. A Taguchi L 9 table with 3 factors (power, powder feed rate, and stand-off distance) and 3 levels for each factor is shown in Table 5-2. In the rest of the chapter, for simplicity, factor power and secondary gas flow rate will be named as power and factor powder feed rate, and carrier gas flow rate will be named as powder feed rate. Figure 5-2 indicates the factors and responses considered for the optimisation of the coatings. 80 Page

101 Chapter 5 Taguchi design of experimental study on HA coatings Figure 5-1 Plasma spray process parameters graph from literature survey a) power vs. stand-off distance, and b) power vs. powder feed rate. 81 Page

102 Chapter 5 Taguchi design of experimental study on HA coatings Table 5-1 Plasma spray process parameters predicted from literature study. Power (kw) Stand-off distance (cm) Powder feed rate (g/min) Figure 5-2 Plasma spray process with factors and responses for Taguchi L 9 design. Sample Power (kw) Table 5-2 Process parameters used in Taguchi L 9 design. Primary gas flow rate, Argon (slpm) Secondary gas flow rate, Helium (slpm) Carrier gas flow rate, Argon (slpm) Powder feed rate (g/min) Stand-off distance (cm) Page

103 Chapter 5 Taguchi design of experimental study on HA coatings 5.3. Results & discussions The coating characterization results for experimental samples 1 to 9 are provided in Table 5-3. Sample Porosity % (n=10) Table 5-3 Coating properties. Microhardness HV (n=20) Deposition efficiency % (n=5) Crystallinity % Surface roughness µm (n=10) ±4.1* 172±43* 25.0±7.2 73* 10.9±1.4* ± ± ± ± ± ± ±1.5* ±0.5* 4 5.3± ± ± ± ± ± ± ± ± ± ± ± ±0.9* 278± ± ± ± ± ±3.6* 28* 8.7± ± ±40* 58.4± ±0.9 * indicates maximum and minimum values Porosity Porosity was determined via SEM image analysis of the coating cross-sections. Ten fields were selected arbitrarily for measuring porosity. Table 5-3 indicates that porosity varied from 3.8% to 16%. Run 1 exhibited the highest porosity and run 7 the lowest. The high porosity was obtained at lower power and shorter stand-off distances due to a poor melting status [69]. Greater power levels reduced the porosity. Figure 5-3 shows the plot of the main effects on the porosity generated by Minitab v16 software (Minitab, Inc.). The porosity has been reported to 1/10 th of a percentage point, since this represents the numerical average of 10 measurements. Note, however, that traditional measurements of porosity report values to the nearest integer, since this is considered more appropriate considering the variable nature of the microstructure. Thus, the higher resolution data reported here should not be used to imply that changes on 1/10 th of a percentage point can influence the material properties of thermal spray coatings. After plotting this porosity data in the response table of Design of Expert v8 software (Stat-Ease, Inc.), an ANOVA (analysis of variance) table was generated, 83 Page

104 Chapter 5 Taguchi design of experimental study on HA coatings which is shown in Table 5-4. In this table, the F value determines whether the variances between two independent samples are equal and the p-value is the probability, ranging from zero to one, that the results observed in a study have occurred by chance. A p-value of 0.05 or below is desired as being statistically significant. From this table it can be seen that power and secondary gas flow rate (X1) have major effects (87.2%) on the porosity. ANOVA analysis indicates that the porosity results are significant. The ANOVA table shows a p-value of 0.04 and implies that the model is significant. Terms Figure 5-3 Main effects plot generated by Minitab software. Table 5-4 ANOVA table for coatings porosity. Sum of squares Degrees of freedom (df) Mean square F value p-value Prob>F Model Power and secondary gas flow rate (X1) Powder feed rate and carrier gas flow rate (X2) Stand-off distance (X3) % Contribution Residuals Core total Page

105 Chapter 5 Taguchi design of experimental study on HA coatings Microhardness Table 5-3 shows that microhardness data are the average of twenty measurements and were found to lie between 172 HV and 329 HV. Higher power and secondary gas flow rate increased the microhardness because of better particle melting [69]. High microhardness was found at run 9 with 40 kw power and low microhardness was found at run 1 with 20 kw power. Figure 5-4 demonstrates the plot of the main effects on the microhardness generated by Minitab software. Figure 5-4 Main effects plot generated by Minitab software. Design of Expert software generates an ANOVA table after plotting all the microhardness data. Table 5-5 indicates that power has a major effect (77.9%) on the microhardness. ANOVA analysis shows that the microhardness results are significant. The ANOVA table shows that the p-value is 0.04, which implies that the model is significant Deposition efficiency The deposition efficiency data presented in Table 5-3 are the average of five measurements and they ranged from 10.9% to 59%. The high deposition efficiency obtained at run 8 arose due to a higher power, centre powder feed rate, and lower stand-off distance. The ANOVA table demonstrates that power and secondary gas 85 Page

106 Chapter 5 Taguchi design of experimental study on HA coatings flow rate (X1) influenced the deposition efficiency with a contribution ratio of 90.1%. Although the deposition efficiency has been reported to 1/10 th of a percentage point it is more realistic, in commercial practice, that the accuracy of this measurement is within several percentage points. Terms Table 5-5 ANOVA table for coatings microhardness. Sum of squares Degrees of freedom (df) Mean square F value p-value Prob>F Model Power and secondary gas flow rate (X1) Powder feed rate and carrier gas flow rate (X2) % Contribution Stand-off distance (X3) Residuals Core total Figure 5-5 illustrates the plot of the main effects on the deposition efficiency generated by Minitab software. Powder feed rate and stand-off distance do not have any significant effects on coating deposition efficiency. However, by comparing deposition efficiency data of experimental runs 1, 2, 3, it can be concluded that an increase of powder feed rate and stand-off distance reduces the deposition efficiency. It is likely that the higher powder feed rate and stand-off distance (i) increases the amount of powder loss, or (ii) fewer particles of optimum melting characteristics are available for deposition onto the substrate. The ANOVA table shown in Table 5-6 was created by Design of Expert software after plotting all the deposition efficiency data in the response table. From this table, it can be seen that power has a major effect (90.10%) on the deposition efficiency. ANOVA analysis proves that the deposition efficiency results are significant. It shows that the p-value is 0.01, which implies that the model is significant. 86 Page

107 Chapter 5 Taguchi design of experimental study on HA coatings Terms Figure 5-5 Main effects plot generated by Minitab software. Table 5-6 ANOVA table for coatings deposition efficiency. Sum of squares Degrees of freedom (df) Mean square F value p-value Prob>F Model Power and secondary gas flow rate (X1) Powder feed rate and carrier gas flow rate (X2) Stand-off distance (X3) % Contribution Residuals Core total Crystallinity Crystallinity data, Table 5-3, varied from 28% to 73%. Figure 5-6 demonstrates the plot of the main effects on the microhardness generated by the Minitab software. In general, higher power produces higher heat input to the particles as well as higher flame velocities, resulting in more particles in a molten state, which produces an amorphous phase [268]. Thus, higher power reduces the crystallinity of the coatings Page

108 Chapter 5 Taguchi design of experimental study on HA coatings On the other hand, higher stand-off distance provides more time for particles to cool and resolidify, and thus, exhibit a crystalline character [78, 269]. Also, powder feed rate has an effect on the coating crystallinity. An increase in powder feed rate reduces the flame temperature and therefore decreases the number of molten particles; thereby increasing the proportion of the crystalline phase. As a result, all these three factors (X1, X2, and X3) have an effect on the crystallinity, which is reflected in the contribution ratio of crystallinity in the ANOVA table. The p-value in the Table 5-7 indicates that no single factor has a significant influence on the crystallinity. Figure 5-6 Main effects plot generated by Minitab software Surface roughness Surface roughness data presented in Table 5-3 are the average of ten measurements and vary between 7.02 and µm. Figure 5-7 depicts the plot of the main effects on surface roughness. The ANOVA table shows that powder feed rate and carrier gas flow rate (X2) have an effect on surface roughness with a contribution ratio of 66.4%. The p-value in the Table 5-8 confirmed that no single factor significantly influenced the surface roughness. 88 Page

109 Chapter 5 Taguchi design of experimental study on HA coatings Terms Table 5-7 ANOVA table for coatings crystallinity. Sum of squares Degrees of freedom (df) Mean square F value p-value Prob>F % Contribution Model Power and secondary gas flow rate (X1) Powder feed rate and carrier gas flow rate (X2) Stand-off distance (X3) Residuals Core total Figure 5-7 Main effects plot generated by Minitab software Numerical optimization of coating properties Design of Expert numerical optimization was used in this study to optimise the coating properties all. It is necessary to set up criteria for each response to optimise the process parameters. The criteria for the coating properties were chosen as shown in Table 5-9. Addition of + indicates more importance; i.e., +++ indicates lowest importance and indicates highest importance in the table. 89 Page

110 Chapter 5 Taguchi design of experimental study on HA coatings Terms Table 5-8 ANOVA table for coatings surface roughness. Sum of squares Degrees of freedom (df) Mean square F value p-value Prob>F Model Power and secondary gas flow rate (X1) Powder feed rate and carrier gas flow rate (X2) Stand-off distance (X3) % Contribution Residuals Core total After selecting these criteria in Design of Expert software, it was possible to optimise process parameters by considering all optimisation criteria. Design of Expert software produces the best solution for these entire criteria with a desirability of 0.7. The solutions suggest that the optimal process parameters are power 40 kw, powder feed rate 16 g/min, and stand-off distance 11 cm. The solution also predicts coating properties for these optimum settings. It predicts porosity (%), microhardness (HV), deposition efficiency (%), crystallinity (%), and surface roughness (µm) of 4.4%, 290 HV, 64%, 49%, 9.4 µm, respectively, for the optimum settings of process parameters. Table 5-10 comprises results between actual and predicted coating properties. Table 5-9 HA optimisation criteria. Properties name Goal Importance Porosity (%) Minimise ++++ Microhardness (HV) Maximise Deposition efficiency (%) Maximise Crystallinity (%) Maximise Surface roughness (µm) Maximise Page

111 Chapter 5 Taguchi design of experimental study on HA coatings Table 5-10 Comparison of results between actual and estimated performance of Porosity % (n=10) coating properties. Microhardness HV (n=20) Deposition efficiency % (n=5) Crystallinity % Surface roughness µm (n=10) Predicted 4.4± ± ± ±1.0 Experimental 4.2± ± ± ±0.7 Mean difference Mean percentage difference (%) Summary A Taguchi L 9 design of experiment was used to study and optimize hydroxyapatite coatings manufactured by the plasma spray process. The study determined the effects of (i) power and secondary gas flow rate (X1); (ii) powder feed rate and carrier gas flow rate (X2); and (iii) stand-off distance (X3) on the coating responses of porosity, deposition efficiency, microhardness, crystallinity, and surface roughness. The Taguchi design allowed the following observations to be made concerning hydroxyapatite coatings. 1. Power and secondary gas flow rate (X1) influences the porosity, deposition efficiency, and microhardness. Powder feed rate and carrier gas flow rate (X2) has a major effect on surface roughness, but the effect is not significant. No single factor has a major influence on the crystallinity alone, due to the distribution of effects among the three factors. 2. Higher power and secondary gas flow rate (X1) reduces porosity and increases microhardness due to better particle melting. 3. Powder feed rate and stand-off distance do not have a significant effect on coating deposition efficiency. However, higher power feed rate and standoff distance reduces deposition efficiency because they may increase the amount of powder loss. 91 Page

112 Chapter 5 Taguchi design of experimental study on HA coatings 4. Optimum coating properties with desired attributes were obtained in nine experiments. Optimum experimental coating properties exhibit a porosity of 4%, a deposition efficiency of 61%, a microhardness of 285 HV, crystallinity of 47%, and surface roughness of 9 µm. There is good agreement between optimum and predicted values with less than 5% difference. 5. Optimum process parameters were predicted by Design of Expert software with a desirability of 0.7. Optimum process parameters are power of 40 kw, secondary gas flow rate of 12 slpm, powder feed rate of 16 g/min, carrier gas flow rate of 3 slpm, and stand-off distance of 11 cm. 92 Page

113 Chapter 6 Effect of power and stand-off distance on the HA coatings 6. Effect of power and stand-off distance on the HA coatings Materials from this chapter have been accepted in the following journal: Hasan, Md. Fahad; Wang, James; Berndt, C.C.; Effect of power and stand-off distance on plasma sprayed hydroxyapatite coatings. Materials and Manufacturing Process, vols. 28(2), pp , Introduction Plasma sprayed coatings build up on the substrate by melting material feedstock at high temperature and velocity, accelerating the molten particles towards the substrate, onto which they impact and cool under rapid solidification conditions [270]. The thermal spray parameters play a pivotal role in determining the microstructures and properties of HA coatings. Power and stand-off distance have been identified as two decisive factors that influence the microstructures and properties of HA coatings. It was reported that changing the current, voltage, gas flow rate, and the stand-off distance resulted in variations of phase component, microstructure and crystallinity of coatings [215]. Sun and Lu et al. [69, 78] demonstrated that the power and standoff distance influence the microstructure, phase, crystallinity, and microhardness of the hydroxyapatite coating. Higher power evolved a much longer plasma spray flame than low power and created good quality coatings, but these operational parameters were more likely to superheat the powder particles and possibly melt the substrate[69, 215]. The stand-off distance must be coupled with power to avoid the overheating of the substrate [78, 269]. Therefore, in this chapter, the coupled effect of power and stand-off distance on coating properties were investigated Methodology From Table 5-2, process parameters used for samples 1 (Power 20 kw, SOD 8cm), 4 (Power 30 kw, SOD 11 cm), and 7 (Power 40 kw, SOD 16 cm) are presented in Table 6-1. The same samples are used in this chapter to analyse the effect of power and stand-off distance, which are coupled by a single factor that is denoted as x. 93 Page

114 Chapter 6 Effect of power and stand-off distance on the HA coatings Sample Power (kw) Table 6-1 Plasma spray process parameters. Primary gas flow rate, Argon (slpm) Secondary gas flow rate, Helium (slpm) Carrier gas flow rate, Argon (slpm) Powder feed rate (g/min) Stand-off distance (cm) Results & discussions Morphology and microstructure of the coatings Figure 6-1 exhibits the SEM microstructures on the top surface under the three spray parameters. Figure 6-1 (a) reveals a microstructure consisting of unmelted particles, semi-melted particles and some partially melted lamellae. Figure 6-1 (b) shows spheroidized particles, partially melted lamellae and some melted lamellae. Figure 6-1 (c) displays many spheroidized particles and flattened well-melted splats. It can be seen that the number of spheroidized particles increases with an increase in power and stand-off distance. The coatings were composed of a combination of well-melted, partially melted, and unmelted adhering irregular splats/particles with pores and microcracks. All coatings were porous and contained fine spherical particles. The scope of particle melting increased with increasing power and stand-off distances; i.e., x, as indicated by the shape change from unmelted particles to flat splats. The higher power increased the processing temperature of the plasma effluent, and the greater stand-off distance lead to an increased residence time for the particle to heat; hence, both factors provided conditions that gave rise to enhanced particle melting [228]. Cracks were presented as white lines for the higher power and stand-off distances due to quenching stress generated during the spraying process. Similar crack results were reported by Lu et al. [78], although findings from Sun et al. [69] and Zhao et al. [215] indicated that there was an absence of cracks on the surface of the coatings. The significance of cracks is beneficial from the viewpoint of the 94 Page

115 Chapter 6 Effect of power and stand-off distance on the HA coatings application; however, the large numbers of cracks are detrimental to the mechanical strength of the coatings. Any voids will allow physiological media to penetrate the coating and influence remodelling of the artificial HA if the phase structure is appropriate. A- Unmelted particle B- Semi-melted particle C- Partially melted lamellae D- Spheroidized particle E- Melted lamellae Figure 6-1 SEM surface morphology a) sample 1: (20 kw, 8 cm), b) sample 4: (30kW, 11 cm), and c) sample 7: (40 kw, 16 cm). By comparing the microstructures of three cross-sections for sample 1, 4, and 7 in Fig. 6-2, it is noticed that the microstructure consisted of pores, cracks and lamellae. The microstructure of Fig. 6-2 (a) depicts many pores, whereas Fig. 6-2 (b) demonstrates a structure with less porosity; which is indicative of improved particle melting that gives rise to a typical lamellae structure. Figure 6-2 (c) reveals plasma spray process conditions that produced the least porous coating. It can be summarised that the degree of unmelted particles was greater and the pore size larger, in the qualitative sense, when power and stand-off distance were decreased. Thus, for the purposes of the bioengineering application, the quality of the microstructure in terms of the degree of particle melting; which influences the phase 95 Page

116 Chapter 6 Effect of power and stand-off distance on the HA coatings content and porosity, can be controlled by adjusting the thermal spray process envelope. Figure 6-2 Cross-section of the coatings a) sample 1: (20 kw, 8 cm), b) sample 4: (30 kw, 11 cm), and c) sample 7: (40 kw, 16 cm). No distinct, unambiguous lamellae structure was observed in Fig. 6-2 (a) for sample 1 (20 kw, 8 cm), whereas Fig. 6-2 (b) for sample 4 (30 kw, 11 cm) exhibits a lamellae structure in good agreement with the results of Sun et al. [69]. Many microcracks were observed in Fig. 6-2 (b) and Fig. 6-2 (c) that indicated quenching phenomena occurred during deposition Porosity and deposition efficiency Figure 6-3 (a) indicates the influence of plasma spray parameters on the porosity of HA coatings, where porosity is the average of 10 measurements and the error bars represent +/- one standard deviations. The trend confirmed that porosity was reduced at the greater power and stand-off distance, since the plasma power increased the in-flight particle temperature and velocity. The increase of in-flight particle temperature and velocity increased the degree of molten lamellae and reduced the porosity; both features that will influence the physical characteristics of the HA coating. Also, the porosity error bar reduced with increases in power and stand-off distance, which demonstrates that porosity is less variable; the coating also 96 Page

117 Chapter 6 Effect of power and stand-off distance on the HA coatings shows improved homogeneity and reliability with increasing power and stand-off distance. Greater stand-off distances offer particles more time to resolidify and produce coatings that exhibit a crystalline character [78, 269]. However, at higher power and stand-off distance, several well-melted lamellae may stack together and molten particles will fill in voids between neighbouring splats so that porosity is reduced. Figure 6-3 (b) shows the effect of plasma spray parameters on the deposition efficiency of HA coatings. The deposition efficiency ranged from 25% to 53%. Higher power and stand-off distance produced less porous coatings, with well-melted lamellae that also revealed an increase in deposition efficiency. Figure 6-3 Influence of spraying parameters on the porosity of hydroxyapatite coatings (a) porosity, (b) deposition efficiency, (c) microhardness, and (d) surface roughness. 97 Page

118 Chapter 6 Effect of power and stand-off distance on the HA coatings Other studies [69] indicated that the plasma power level did not distinctly influence the deposition efficiency; whereas Vijay et al. [271] reported that deposition efficiency increased when there was an increase of power for plasma sprayed alumina-titania coatings. The coatings produced in this study revealed a significant influence of power and stand-off distance on the deposition efficiency, since the selected spray parameters influenced the coating microstructure. The HA particles were partially melted or unmelted at lower power and stand-off distance. Such particles were not fully incorporated into the coating or may have bounced off the substrate, leading to physical conditions that reduced the deposition efficiency under these thermal spray process parameters. The increase of input power increased the flame temperature and, consequently, increased the degree of melting so that the deposition efficiency was improved Physical properties: microhardness and roughness The microhardness results, Fig. 6-3 (c), indicated an expected increase with power levels and stand-off distance, as would be expected since the density increased. This result is a direct reflection of the microstructure that evolves due to the melting conditions within the plasma processing zone [69]. There is an inverse relationship between porosity and microhardness; i.e., the porosity reduced as the microhardness increased. Higher power and stand-off distance produced well-melted lamellae and splat bonding as indicated in the microstructural study. The inference is that such microstructural conditions enhanced the cohesion between splats and gave rise to improved mechanical properties of these HA coatings. Increasing power and stand-off distance produced more smooth coatings as exhibited in Fig. 6-3 (d) that reflects the results of 10 measurements. Figure 6-1 (a) reveals the roughest coating that was produced due to unmelted and partially melted particles; whereas highly flattened particles, Fig. 6-1 (c), gave rise to the smoothest surfaces. 98 Page

119 Chapter 6 Effect of power and stand-off distance on the HA coatings Phase structure and crystaliinity The percentages of crystallinity are 73%, 50% and 46% for samples 1, 4, and 7, respectively. Increasing power decreased the crystallinity, while increasing stand-off distance had the reverse effect of increasing crystallinity [69], Figure 6-4 (a). Higher power increased the proportion of well-melted lamellae and the glassy phase, which lead to an increased amount of amorphous phase as confirmed by the literature [69]. Higher stand-off distance provided more time for particles to cool, resolidify and recrystallize, which ultimately increased crystallinity. Therefore, the degree of crystallinity is a coupled effect of power and stand-off distance that preserves crystallinity at an acceptable level. Hydroxyapatite coatings for bioengineering applications should demonstrate a crystallinity of at least 45%, according to ISO standards [49]. Figure 6-4 (b) represents X-ray diffraction (XRD) patterns of plasma sprayed coatings. It shows both crystalline and amorphous HA. In addition, other contaminations such as tri-calcium phosphate (TCP), tetra-calcium phosphate (TTCP), and calcium oxide (CaO) are also noticed. The amorphous trace on the XRD pattern increased, implying reduced crystallinity as the power and stand-off distance increased. The intensity of HA peak (211) decreased with the increase of power and stand-off distance, which indicates the reduction of HA contents and the reduction of crystallinity. EDX analyses were performed to calculate the Ca/P ratio of the coatings, Table 6-2, by the averaging of 5 measurements. The percentages of Ca, P, and O varied by less than 5%, and the Ca/P ratio varied from 1.51, 1.61, and 1.62 in molar ratio for samples 1, 4, and 7, respectively. This indicated that the coatings deposited at higher power and stand-off distance have a Ca/P ratio closer to the nominal value of stoichiometric hydroxyapatite (1.67). These increases of Ca/P ratio value are due to the change of plasma spray parameters. 99 Page

120 Chapter 6 Effect of power and stand-off distance on the HA coatings Figure 6-4 Influence of process parameters on the a) crystallinity, b) XRD pattern for i) sample 1: (20 kw, 8 cm), ii) sample 4: (30 kw, 11 cm), and iii) sample 7: (40 kw, 16 cm) of hydroxyapatite coatings. 100 Page

121 Chapter 6 Effect of power and stand-off distance on the HA coatings Table 6-2 Chemical composition of the coatings for samples. Element Sample 1 wt.% (n=5) Sample 4 wt.% (n=5) Sample 7 wt.% (n=5) Ca 37.60± ± ±0.23 P 19.17± ± ±0.31 O 43.23± ± ±0.54 Ca/P ratio (wt.%) Ca/P ratio (molar ratio) The Ca/P ratio was also measured via the X-ray diffraction [272] from the heights of the crystalline HA peaks at (210) and (202), TTCP (Tetracalcium phospahte), ß- TCP (ß-Tricalcium phosphate), and CaO (Calcium oxide). Crystalline peaks were identified according to JCPDS cards. The calculation of the amorphous phase Ca/P ratio (denoted as Ca/P amorphous ) was deduced from the XRD results by following the method of Carayon et al. [272]. The Ca/P ratio remained constant at 1.66 for the three experimental conditions measured by the XRD technique. The Ca/P ratio was constant since the plasma power increase was compensated by a corresponding increase in the stand-off distance Summary Power and stand-off distance were coupled in this series of experiments and selected on the basis of a comprehensive literature survey. The result shows that coupled power and stand-off distance strongly influence the properties of coatings. The following conclusions can be drawn: 1. The coating microstructure was improved with increasing power and standoff distance (i.e., x ) due to enhanced particle melting and an increased proportion of melted lamellae. 2. Porosity, and surface roughness were reduced with increasing power and stand-off distance. Coating porosity was reduced due to an increase of inflight particle temperature and velocity. The reduction in porosity error bars with increasing power and stand-off distance indicates the improved homogeneity and reliability of the coatings. A longer stand-off distance 101 Page

122 Chapter 6 Effect of power and stand-off distance on the HA coatings permitted particles to either (i) resolidify and recrystallize, or (ii) to produce well-melted lamellae depending on the initial particle size. The crystallinity reduced with increasing power and stand-off distance as did the smoothness due to better particle melting. The intensity of the HA peak (211) decreased with the increase in power and stand-off distance, which indicates the reduction of HA content. 3. Deposition efficiency and microhardness increased with increasing power and stand-off distance. Microhardness increased due to reduced porosity, since well-melted lamellae were able to stack together. 4. The combined effect of increasing power and stand-off distance allowed the Ca/P ratio of the coatings to be maintained at a constant of However, the Ca/P ratio measured from EDX analyses indicated that higher power and stand-off distance provides a Ca/P ratio of the coatings closer to the nominal value of stoichiometric hydroxyapatite (1.67). This chapter provides guidelines concerning operational conditions of the plasma spray process that can be used to manufacture an appropriate hydroxyapatite coating that exhibits the appropriate microstructure, porosity, and Ca/P ratio. The operational conditions of roughness and deposition efficiency have also been related to the physical attributes of the coating. 102 Page

123 Chapter 7 Microhardness study using indentation techniques 7. Microhardness study using indentation techniques Materials from this section (Section 7.3) have been published in the following journal: Hasan, Md. Fahad; Wang, James; Berndt, C.C.; Evaluation of the mechanical properties of plasma sprayed hydroxyapatite coatings. Applied Surface Science, vols. 303, pp , Introduction Thermal spray coatings exhibit complex microstructures with highly heterogeneous and anisotropic behaviour. They feature flat plate like lamellae, cracks, pores, unmelted particles, weak interfaces between splats, and oxides [164, ]. It is, therefore, important to consider measurement direction, location, and applied load condition when determining the microhardness of thermal sprayed coatings. Microhardness is reported in the literature as an average value with a standard deviation of a certain number of random indentations (usually from 10 to 30) on the cross section of the coatings. However, the average with standard deviation does not reflect the actual microstructural characteristics of thermal spray coatings. As a result, studies have investigated microhardness and elastic modulus using indentation techniques [142, 147, 156, 161, 163, 167, 170, 277, 278]. However, further work is necessary to investigate the effect of applied loads throughout the coating thickness; as well as these studies need to take into consideration the dense and porous areas, and the indentation angle, to fully understand the characteristics of thermal spray coatings Methodology The plasma sprayed HA coating used for the microhardness study was of thickness 346±24 µm. Table 7-1 shows the plasma spray parameters used for this coating. The Vickers and Knoop microhardness measurements were executed on the top surface and the cross-section of the coating by indenting at loads of 50, 100, 300, and 500 gf for a dwell time of 15 s. More detailed procedures are described in 103 Page

124 Chapter 7 Microhardness study using indentation techniques Sections 7.3 and 7.4 in relation to the Vickers and Knoop microhardness methods employed in this study. Table 7-1 Plasma spray parameters. Parameters Value Power (kw) 40 Primary gas flow rate, Ar (slpm) 50 Secondary gas flow rate, He (slpm) 12 Carrier gas flow rate, Ar (slpm) 7 Powder feed rate (g/min) 27 Stand-off distance (cm) Microhardness study using Vickers indentation Indentations were performed on the cross-section of coatings at locations of 75, 175, and 275 µm distance from the substrate-coating interface for all loads to avoid the effect of impinging stress fields, Figure 7-1. Twenty readings were taken along each region of interest, considering dense and porous areas for each indenter loads, testing directions, and indent locations; Figure 7-2. The distance between each indentation was three times greater than the indent diagonal [279]. The rule of mixtures was used to determine a composite microhardness from dense and porous areas with varying percentage contributions (25%, 50%, and 75%). The composite microhardness can be calculated from the following equation: H c = dh d + (1-d)H p (31) where d is the percentage contribution of the dense area, and H c, H d, H p are the composite microhardness, dense microhardness and porous microhardness, respectively. The surface roughness was measured using a 3D profilometer (Bruker AXS ContourGT-K) on the polished cross-section after Vickers indentation. Roughness was measured from the corner of the horizontal indent impression to a 5 µm distance along the horizontal direction. This procedure is denoted as indent roughness in this chapter. For each indent, roughness was measured at the two corners of the horizontal indent impression, and the averages of these two indent roughnesses are presented. The intent of this experimental study was to gauge the influence of the 104 Page

125 Chapter 7 Microhardness study using indentation techniques indent experiment on the surface deformation near the indent. For example, it may be possible to detect splat movement and crack features. For clear visualisation of the graphs, 100 and 300 gf data are presented (Figs. 7-4, 7-6, and 7-8) analytically by displacing the data on the x-axis position by 2 µm. Figure 7-1 Schematic of Vickers indentation at different indent location within a typical thermal spray coating microstructure. 105 Page

126 Chapter 7 Microhardness study using indentation techniques Figure 7-2 SEM micrographs of plasma sprayed hydroxyapatite coating (a) top surface, and (b) cross-section Effects of applied load on the microhardness and indenter tip roughness Figure 7-3 shows the effect of applied load on the microhardness of the coating top surface. Increasing the applied load, decreases the microhardness for both dense and porous areas. The effects of 50, 100, 300, and 500 gf loads on the microhardness of the coating cross-section followed similar trends, as shown in Fig Thermal spray coatings are formed from many thousands of molten particles that stack up as flat plate-like lamellae that are parallel to the substrate. The coatings consist of defects such as pores, cracks, unmelted particles and weak interfaces due to the uneven and irregular shape of the lamellae. At low loads, the indentor diagonal length is small and might cover almost pore free areas and few lamellae. However, it is more probable that pores will be encompassed by the indent area at higher loads. Also, a higher load results in large cracks with permanent deformation, whereas a lower load leads to small cracks that may recover due to the elastic recovery of indentation. Thus, at a higher load, the microhardness decreases since it encompasses coating defects such as, pores and cracks. In addition [146, 147], the effect of stress relaxation encourages a decrease in microhardness at a higher load. Figure 7-5 shows the effects of applied load on the indent roughness of the coating top surface. Indent roughness increases with an increase in applied load, since a higher load directly increases cracking from the indent corners. As the load increases, the error increases, since the roughness is more scattered at higher loads due to the inhomogeneous microstructure. Also, the indent roughness on the crosssection of the coating shows similar results, Figure Page

127 Chapter 7 Microhardness study using indentation techniques 350 a n=20 Top surface Dense area Microhardness (HV) Load (gf) 350 b n=20 Top surface Porous area Microhardness (HV) Load (gf) Figure 7-3 Effects of applied load on the microhardness of the coating top section a) dense area, and b) porous area. 107 Page

128 Chapter 7 Microhardness study using indentation techniques a n=20 Cross-section Dense area 50 gf 100 gf 300 gf 500 gf Microhardness (HV) Distance from the substrate-coating interface (um) Microhardness (HV) 300 b n=20 Cross-section Porous area 50 gf 100 gf 300 gf 500 gf Distance from the substrate-coating interface (um) Figure 7-4 Effects of applied load and distance from the substrate-coating interface of the coating on the microhardness a) dense area, and b) porous area (indent location is presented in Fig. 7-1; 100 and 300 gf data are presented on the x-axis position of 77, 177, and 277 µm for clear visualisation). 108 Page

129 Chapter 7 Microhardness study using indentation techniques Surface roughness near the horizontal indenter tip (um) n=20 Top surface Desnse area Load (gf) Figure 7-5 Effects of applied load on the surface roughness of indenter horizontal tip. Surface roughness near the horizontal indenter tip (um) n=20 Cross-section Dense area 50 gf 100 gf 300 gf 500 gf Distance from the substrate-coating interface (um) Figure 7-6 Effects of applied load and distance from the substrate-coating interface of coating on the indent roughness (indent location is presented in Fig. 7-1; 100 and 300 gf data are presented on the x-axis position of 77, 177, and 277 µm for clear visualisation). 109 Page

130 Chapter 7 Microhardness study using indentation techniques Effects of indenter location on the microhardness and indenter tip roughness Figure 7-4 shows the variation of microhardness with the indenter location throughout the thickness of the coating cross-section. Maximum microhardness is found on the central location (175 µm) of the cross-section. From Fig. 7-4 (a), it can be observed that the distribution of microhardness throughout the coatings for 50 and 100 gf shows a similar trend due to the smaller test volume. Similarly, 300 and 500 gf loads exhibit a similar trend due to testing a larger volume that may contain defects (i.e., pores and cracks). The coating cross-sections were encased into epoxy mounts. Therefore, in the following discussions, reference to the coating-epoxy interface implies coating locations that are near to the coating surface. Coatings are brittle near the two interfaces of the coatings; i.e., substrate-coating and coating-epoxy interface for higher loads (300 and 500 gf). Coatings are more brittle near the coating-epoxy interface position (275 µm) and exhibit low microhardness compared to the position near the substrate-coating interface (75 µm) for higher loads (300 and 500 gf). Kuroda et al. [280] also observed similar results for HVOF processes on 316 stainless steel substrates. Increased microhardness observed near the substratecoating interface may arise from a strain-hardening effect due to the grit blast preparation of the substrate [280]. Figure 7-6 reveals the indent location influence on the indent roughness. This data indicates that indent roughness follows two distinct trends that can be graphed according to (i) 50 and 100 gf loads, and (ii) 300 and 500 gf loads Effects of testing direction The microhardness variations on the polished top surface and on the crosssection are shown in Fig. 7-3 and Fig. 7-4, respectively. Thermal spray coatings consist of globular and interlamellar flat pores, intralamellar cracks, flat splats, and partially melted splats, and exhibit microstructural anisotropy. The Vickers indentor interacts with small flat pores, intralamellar cracks, and thin impact splats on the cross-section; whereas it interacts with large flattened droplets and pores on the top surface. As a consequence, microhardness values are higher on the cross-section 110 Page

131 Chapter 7 Microhardness study using indentation techniques than the top surface of the plasma spray coatings, as has been reported in the literature [162, 163, 276, 278]. However, plasma spray hydroxyapatite coatings exhibited fewer pores on the top surface than on the cross-section. Plasma sprayed hydroxyapatite coating exhibits porosity of 4.1% on the cross-section, as opposed to 3.2% on the top surface. There are some cracks on the cross-section that may have the effect of reducing microhardness, whereas the top surface exhibits a crack free coating with a dense area, which may have the effect of increasing the microhardness. Top surface microhardness is compared with the central position (175 µm) microhardness on the cross-section. For 50 and 100 gf indentation in the dense area, microhardness on the top surface and cross-section shows almost similar hardness, since the small load does not interact with pores, Figure 7-3 (a) and Figure 7-4 (a). For 300 and 500 gf loads in the dense area, microhardness on the top surface are higher compared to the cross-section near the central position (175 µm) since the top surface has less pores compared to the cross-section, Figure 7-3 (a) and Figure 7-4 (a). For indentation in a porous area, microhardness on the top surface exhibits a higher value compared to the cross-section. Thermal spray coatings are formed by numerous splats stacked together. On the cross-section of thermal spray coatings, indentations are facing along the thickness of the splat, which is thin (2-5 µm), Figure 7-1 (b). It is easier for the indentor to penetrate along this thin splat layer since the bonding of these attached splats is weak. However, on the top surface, the splat surface area is large and the indentor breaks this melted top surface, Figure 7-2. Top surface splats also have much more support from underlying splats due to the large area. Thus, the indentor faces relatively a hard surface from the top orientation compared to the cross-section profile Rule of mixture The combined microhardness was calculated by using the rule of mixture technique from dense and porous area microhardness values for the top surface and cross-section, Figs. 7-7 and 7-8. The percentage contributions of dense and porous area microhardness varied between 75%, 50%, and 25%. It can be seen that 111 Page

132 Chapter 7 Microhardness study using indentation techniques combined microhardness decreases with the increase of porous area percentage microhardness. These results indicated that, for comparison of microhardness, it is necessary to consider similar percentages of microhardness from dense and porous areas. 350 Top surface 75 % dense 25% porous area 50% dense and 50% porous area 25% dense and 75% porous area Microhardness (HV) Load (gf) Figure 7-7 Combined microhardness on the top surface using rule of mixture for 75% dense and 25% porous area, 50% dense and 50% porous area, 25% dense and 75% porous area microhardness. 112 Page

133 Chapter 7 Microhardness study using indentation techniques Figure 7-8 Microhardness on the cross-section calculated using rule of mixture for a) 75% dense and 25% porous area, b) 50% dense and 50% porous area, and c) 25% dense and 75% porous area microhardness (100 and 300 gf data are presented on the x-axis position of 77, 177, and 277 µm for clear visualisation) Weibull modulus analysis Weibull modulus measures the variability of material strength. A high Weibull modulus indicates a low variability in strength, and vice-versa. From Figs. 7-9 and 7-10, it can be seen that the increases in load lead to an increase in the Weibull modulus of microhardness. Since a larger load interacts with a large test volume, this reflects less scattering in the distribution of microhardness data because the influence of material heterogeneity is less. Similar results are also reported in the literature [156, 278]. Weibull moduli of microhardness are higher in the dense area than in the porous area since microhardness values are less scattered in the dense area. 113 Page

134 Chapter 7 Microhardness study using indentation techniques Weibull modulus of microhardness 25 a n=20 Top surface Dense area Load (gf) 25 b n=20 Top surface Porous area Weibull modulus of microhardness Load (gf) Figure 7-9 Weibull modulus of microhardness on the top surface a) dense area, and b) porous area. 114 Page

135 Chapter 7 Microhardness study using indentation techniques Weibull modulus of microhardness a n=20 Cross-section Dense area 50 gf 100 gf 300 gf 500 gf Distance from the substrate-coating interface (um) Weibull modulus of microhardness b n=20 Cross-section Porous area 50 gf 100 gf 300 gf 500 gf Distance from the substrate-coating interface (um) Figure 7-10 Weibull modulus of microhardness on the cross-section a) dense area, and b) porous area (indent location is presented in Fig. 7-1). 115 Page

136 Chapter 7 Microhardness study using indentation techniques Figure 7-10 represents the Weibull modulus distribution of microhardness for different applied loads throughout the coating thickness. Figure 7-10 (a) shows that the Weibull modulus of microhardness in the dense area, followed similar trends throughout the coating thickness for lower loads (50 and 100 gf). Similarly, the Weibull modulus of microhardness for higher loads (300 and 500 gf) exhibited similar trends throughout the coating thickness. Maximum and minimum Weibull modulus of microhardness on the cross-section of dense area was found to be 21 and 6.3, close to the substrate-coating interface position for 300 and 50 gf, respectively. Maximum and minimum Weibull modulus of microhardness on the cross-section of the porous area are 10.2 on the centre position and 4.4 close to the substrate-coating interface position for 500 and 100 gf, respectively. Lima et al. [278] reported a Weibull modulus of 20 for titania coatings with 300 gf on the cross-section. From Fig. 7-10, it can be concluded that the high Weibull modulus of microhardness depends not only on the base material, but is also related to the applied load and the indent position Microhardness study using Knoop indentation Indentations were performed on the cross-section of coatings at locations of 75, 175, and 275 µm away from the substrate-coating interface, Figure On the cross-section, indentations were carried out with the major diagonal at an angle of 0⁰, 45⁰, and 90⁰ with respect to the spray direction. Indentation angle is considered as the angle between the major diagonal and the substrate-coating interface. Instead of optical micrograph images connected with the microhardness tester, a high magnification scanning electron microscopy (SEM) picture was used for measuring microhardness and elastic modulus to reduce the error in measurement. The distance between each indentation was at least three times the minor diagonal and two times the major diagonal to avoid any interference from the superposition of stress fields [281]. Twenty readings were taken randomly along each region of interest with respect to indentation angle, testing direction, measurement location, and applied load. Microhardness data were then adjusted by subtracting the two largest and two smallest readings to represent data for typical material properties that documented 116 Page

137 Chapter 7 Microhardness study using indentation techniques outliers. These outlier data points may arise from high or low porosity regions of the microstructure, which are unrepresentative structures of the material. Figure 7-11 Schematic of Knoop indentation at different indent location within typical thermal spray coatings microstructure. Microhardness measured at 0⁰, 45⁰, and 90⁰ indentation angles are denoted as H 0, H 45, and H 90, respectively. Similarly, elastic modulus measurements are denoted as E 0, E 45, and E 90, respectively. Weibull moduli of microhardness and elastic 117 Page

138 Chapter 7 Microhardness study using indentation techniques modulus are denoted as m H and m E, respectively. For clear visualisation of the graph, 100 and 300 gf data are presented (Fig. 7-12) by adding an extra 2⁰ on the x-axis position, i.e., 2⁰, 47⁰,92⁰. Similarly, 2 µm are added on the x-axis position for Fig. 7-14, i.e., 77, 177, 277 µm Effects of indentation angle on the microhardness and elastic modulus Figure 7-12 shows the effect of indentation angle on microhardness and elastic modulus. The dependence of microhardness and elastic modulus on the indentation angle exhibits a parabolic shape. Maximum microhardness is found at a 45⁰ indentation angle for all applied loads (50, 100, 300, and 500 gf) on the coating cross-sections. A similar effect is revealed for the elastic modulus. Figure 7-12 Distributions of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) with change of indentation angle with the substrate-coating interface (indentation angle is presented in Fig. 7-11; 100 and 300 gf data are presented on the x-axis position at 2⁰, 47⁰,92⁰ for clear visualisation). 118 Page

139 Chapter 7 Microhardness study using indentation techniques For H 0, since the major diagonal of the indenter is parallel to the substrate-coating interface, it covers fewer lamellae that are also parallel to the substrate-coating interface. For H 90, the major diagonal of the indenter is perpendicular to the substrate-coating interface; therefore, it covers the boundaries of several lamellae along the thickness. For H 45, the major diagonal of the indenter is at 45⁰ with the substrate-coating interface, and it may cover several lamellae (giving more extensive coverage than that of the 0⁰ angle) and fewer lamellae boundaries than the indenter faces at 90⁰ angle. These two effects in combination may increase the microhardness of H 45 compared to the other microhardness values of H 0 and H 90. Figure 7-11 (b) illustrates these features clearly. It is interesting to note that the dependence of the microhardness values on the indentation angle follows Pythagoras theorem that can be presented as: (H ) = (H ) + (H ) (32) The calculated values according to Pythagoras theorem and the measured values at an indentation angle of 45⁰ show good agreement with a maximum 16% error, Table 7-2. The percentage error may result from the variation in microstructure and the accuracy of the indentation angle. Table 7-2 Comparison of microhardness data with Pythagoras theorem. Load (gf) Microhardness with indentation parallel to the substratecoating interface, H 0, (KHN) n=20 Microhardness with indentation perpendicular to the substratecoating interface, H 90 (KHN) n=20 Microhardness with indentation at 45º angle to the substratecoating interface, H 45 (KHN) n=20 Microhardness calculated according to Pythagoras theorem (KHN) Difference between calculated and measured data (%) ±37 289±42 340± ±28 236±34 289± ±19 210±21 248± ±14 193±21 237± Page

140 Chapter 7 Microhardness study using indentation techniques Figure 7-12 (a) and (c) shows a graph with original data, whereas Fig (b) and (d) shows a graph with adjusted data. The adjusted graph shows a much clearer picture since it is plotted without outliers. Similar results are seen for Figs and Figure 7-13 Distributions of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) with change of testing directions and applied loads Effects of testing direction on the microhardness and elastic modulus Comparisons of microhardness and elastic modulus of the coating on the top surface and cross-section for different applied loads are shown in Fig It can be seen that microhardness and elastic modulus value are higher on the top surface than the cross-section. The top surface of the coating is dense and almost crack free, whereas the cross-section exhibits cracks, Figure 7-2. A lower porosity of 3.2% was 120 Page

141 Chapter 7 Microhardness study using indentation techniques found on the top surface compared to 4.1% on the cross-section. These cracks and pores may reduce microhardness and elastic modulus values on the cross-section. Figure 7-14 Distributions of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) at different locations on the cross-section (indent location is presented in Fig. 7-11; 100 and 300 gf data are presented on the x-axis position of 77, 177, and 277 µm for clear visualisation). These obtained results are in good agreement with those of Saeed et al. s [131], who reported higher microhardness values on the top surface for flame sprayed HA coatings compared to the cross-section using a nano-indentation technique. However, Li et al. [170] reported higher microhardness on the cross-section compared to the top surface for plasma sprayed Cr 3 C 2 -NiCr coatings using Knoop indentation. This difference in observation may be due to the different materials investigated since they exhibit different microstructures. In addition, porosity values 121 Page

142 Chapter 7 Microhardness study using indentation techniques on the top surface and cross-section may have a significant effect on the microhardness. Elastic modulus values of thermal spray coatings depend on porosity, interlamellar boundaries and intralamellar cracks. The effect of spherical shaped pores on the elastic modulus can be expressed as [282]: 5a 3 E = E0 1 ( + )P 4c 4 (33) where P is the porosity, c is the axis that is parallel to the stress direction, a is the axis in the plane that is perpendicular to the axis c, and E 0 is the elastic modulus for a zero porosity material. Equation 33 indicates that materials that have spherical pores decrease elastic modulus values. Interlamellar boundaries and intralamellar cracks can be assumed as pores that may have a detrimental effect on elastic modulus values. According to equation 33, the elastic modulus will be higher on the top surface than on the cross section. The apparent high density of the surface Knoop measurements may be attributed to the small sampling depth and less likelihood of encountering volume defects Effects of indent location on the microhardness and elastic modulus The microhardness and elastic modulus variations on the cross-sections at different locations and applied loads throughout the coating thickness are shown in Fig Microhardness and elastic modulus decrease with increased applied loads since this leads to a larger indentation area. A smaller area contains small pores whereas a large area covers a combination of several large and small pores that may have a detrimental effect on the microhardness and elastic modulus with an increase in applied load. Microhardness distributions follow a parabolic trendline for all applied loads with different locations. Microhardness reaches a maximum at the central position (175 µm) of the coatings. Elastic modulus distributions follow a parabolic trendline for lower loads (50 and 100 gf). However, higher load (300 and 500 gf) shows on almost constant elastic modulus. A small load samples only a small area and produces a small indentation 122 Page

143 Chapter 7 Microhardness study using indentation techniques depth, leading to minor local variation in microstructure. On the other hand, high load samples a large area and penetrate a large indentation depth. Small indentation depth produces a short minor diagonal, whereas a large penetration depth produces a greater minor diagonal. It is recommended to use high magnification pictures for measuring elastic modulus, especially for lower loads (50 and 100 gf); since the lower load produces a short minor diagonal that may lead to measurement errors at lower magnification Weibull modulus analysis for microhardness and elastic modulus Variability of data in relation to mechanical properties can be determined by the Weibull modulus measurement. Figure 7-15 shows the effect of indentation angle on the Weibull modulus of microhardness (m H ) and elastic modulus (m E ). It can be seen that maximum m H and m E values are found at a 45⁰ indentation angle in most of the cases. These values indicate that H 45 and E 45 data are less variable. Figure 7-16 demonstrates the dependence of m H and m E values on the testing direction. The m H and m E values are varied and not really distinguishable with respect to the top surface and cross-section. Figure 7-17 reveals the m H and m E on the cross-section at different locations throughout the coating thickness. Maximum values of m H and m E are found at the central position (175 µm) of the coatings. Figures 7-15 to 7-17 indicate that increasing applied loads increases the values of m H and m E, since a low load covers a small area, and the data obtained become scattered. With an increase in the applied load, the area covered by the indenter is greater, and the data obtained become less scattered, which improves the Weibull modulus. Also, Figs to 7-17 indicate that the adjusted data show higher Weibull modulus values than the original data, due to the removal of outliers. The Weibull modulus of microhardness and elastic modulus for original data are in the range of and , respectively; whereas for adjusted data, they are in the range of and , respectively. From these results, it can be seen that the Weibull modulus of microhardness improved considerably with the adjusted data, 123 Page

144 Chapter 7 Microhardness study using indentation techniques since outliers were removed based on the microhardness results, whereas the Weibull modulus of elastic modulus shows little change. Figure 7-15 Weibull modulus of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) with different indentation angles (indentation angle is presented in Fig. 7-11). 124 Page

145 Chapter 7 Microhardness study using indentation techniques Figure 7-16 Weibull modulus of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) with change of testing directions. Elastic modulus values are more scattered than microhardness values, since m H values are found in the range of 6.3 to 13.4 (for original data), while m E are in the range of 1.8 to 4.1 (for original data). These results indicate a high Weibull modulus for microhardness compared to the elastic modulus. This observation is in good agreement with that of Li et al. [170]. There are some exceptional cases that arose for Weibull modulus values where a few of the latter showed different values compared to other characteristic trendlines, which may have been due to the variation of sample polishing. 125 Page

146 Chapter 7 Microhardness study using indentation techniques Figure 7-17 Weibull modulus of (a) microhardness (original data), (b) microhardness (adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted data) on the cross-section (indent location is presented in Fig. 7-11) Depth of indentation Change of depth of indentation with respect to indentation angle, testing direction, and indent location are presented in Figs to From Figs and 7-20, it can be seen that the depth of indentation is almost unchanged for 50 and 100 gf with respect to the change of indentation angle and indentation location, whereas for 300 and 500 gf shows variation and also indicate that 45 º indentation angle and indent location at the centre (i.e., 175 µm) of the coating shows minimum indentation depth. Figure 7-19 indicates that the depth of indentation is small for the top surface compared to the cross-section since top surface has much more support from underlying layer compared to the cross-section (described in Section 7.3.3). 126 Page

147 Chapter 7 Microhardness study using indentation techniques Depth of indentation (um) n=20 Cross-section 50 gf 100 gf 300 gf 500 gf Indentation angle (degree) Figure 7-18 Depth of indentation variation with change of indentation angles (indentation angle is presented in Fig. 7-11). 10 n=20 Cross-section Top surface Depth of indentation (um) Load (gf) Figure 7-19 Depth of indentation variation with change of testing directions. 127 Page

148 Chapter 7 Microhardness study using indentation techniques Depth of indentation (um) n=20 Cross-section 50 gf 100 gf 300 gf 500 gf Distance from the substrate-coating interface (um) Figure 7-20 Depth of indentation variation with change of indent locations on the cross-section (indent location is presented in Fig. 7-11) Frequency distribution Frequency plots of Knoop microhardness (original data) are shown in Figs and 7-22 with respect to the cross-section and top surface. From all these graphs, it can be seen that a bimodal distribution may exist for smaller loads (i.e., 50 and 100 gf), whereas it cannot be clearly distinguished for higher loads (i.e., 300 and 500 gf). Valente et al. [156] and Lin et al. [142] also reported similar results. 128 Page

149 Chapter 7 Microhardness study using indentation techniques 9 8 n=20 Cross-section (175 um) Frequency counts gf 100 gf 300 gf 500 gf Microhardness (HV) Figure 7-21 Frequency distribution of microhardness on the cross-section at the centre (175 µm) of the coatings. 12 n=20 Top surface Frequency counts gf 100 gf 300 gf 500 gf Microhardness (HV) Figure 7-22 Frequency distribution of microhardness on the top surface. 129 Page

150 Chapter 7 Microhardness study using indentation techniques Student s t-test Student s t-test results for the top surface and cross-section with original data and adjusted data are presented in Tables 7-3 and 7-4. Student s t-test determines the probability of whether two sets of data are completely different or not. It also allows examination of whether a null hypothesis exists or not, based on the probability value. If the probability value is less than 0.05, then a null hypotheses can be rejected. T stat values suggest the similarity of two data sets. A higher T stat value indicates a completely different data set. From Tables 7-3 and 7-4, it can be seen that T stat values are higher for load 50 vs. 500 gf and lower for load 300 vs. 500 gf. These figures explain that a load of 50 and 500 gf show completely different data sets whereas loads of 300 and 500 gf show close data sets. The probability values for load 300 vs. 500 gf show greater than 0.05 in most of the cases whereas other load comparisons show less than These also indicate that the data sets for loads of 300 and 500 gf are similar, whereas others data sets may be different from one another. Table 7-3 Student s t-test for the microhardness on the top surface with original Load (gf) (n=20) and adjusted data (n=16). Original data (n=20) T stat Adjusted data (n=16) Original data (n=20) Probability Adjusted data (n=16) 50 vs vs vs vs vs vs Page

151 Chapter 7 Microhardness study using indentation techniques Table 7-4 Student s t-test for the microhardness on the cross-section with original (n=20) and adjusted (n=16) data. Indent distance from the T stat Probability substrate-coating Load (gf) Original Adjusted Original Adjusted interface (µm) or data data data data indentation (n=20) (n=16) (n=20) (n=16) angles (º) vs ( ) H ( ) H vs H H vs H H vs H H vs H H vs H H H 90 and H 45 indicates indentation angles of 90º and 45º with the substrate-coating interface 131 Page

152 Chapter 7 Microhardness study using indentation techniques Effects of indentation on the microstructure The effects of indentation with an applied load of 100 gf on the cross-section of coatings microstructure are shown in Fig There is evidence of splat movement or possibly ductile plastic deformation or tearing. Figure 7-23 (a, b) shows indentation without splat movement whereas Fig (c, d, e, f) shows evidence of splat movement. It also shows that the indentation without splat movement (Fig (a, b)) exhibit higher microhardness values than the indentation with splat movement (Fig (c, d, e, f)). The splat movement may occur due to the splat corners being loosely connected and therefore liable to break during the indentation measurement. Figure 7-23 Indentation on the cross-section of the coatings at the centre position (175 µm) with an applied load of 100 gf (a, b) without splat movement, and (c, d, e, f) with splat movement ( HK indicates Knoop microhardness value and a indicates major diagonal length of Knoop indentation) Summary The microhardness of plasma sprayed HA coatings was measured using Vickers indentation with respect to testing direction, different applied load, and indent location. Dense and porous areas throughout the coating thickness were taken into accounts that are related to the microstructure and anisotropic behaviour of the coatings. Also, indent roughness at the tip after Vickers indentation was measured to establish the effects of indentation on the coatings. Statistical analyses were used to determine the reliability and variability of the measured data. The following conclusions can be drawn from this Vickers indentation study: 132 Page

153 Chapter 7 Microhardness study using indentation techniques 1. Loads of 50 and 100 gf, as well as 300 and 500 gf, show similar effects on the microhardness, indent roughness and Weibull modulus of microhardness throughout the coating thickness in the dense area. Loads of 50 and 100 gf present microhardness information on a small volume of the coatings for almost pore free areas; whereas loads of 300 and 500 gf show microhardness information on a large volume of the coating that contains defects (i.e., pores and cracks). 2. Coatings are brittle near the two interface positions (i.e., substrate-coating and coating-epoxy interface) of the coatings for higher loads (300 and 500 gf). Coatings are more brittle near the coating-epoxy interface position (275 µm) and exhibit low microhardness compared to the position near the substrate-coating interface (75 µm) of the coatings at higher loads (300 and 500 gf). This effect is due to strain-hardening that may arise during grit blast preparation of the substrate. 3. Indent roughness increases as the load increases since a higher load increases the crack on the two horizontal tips. 4. The combined microhardness calculated from a rule of mixtures decreases with an increase of porous percentage area microhardness. These measurements indicated that, for comparison of microhardness results, it is necessary to consider similar percentages of microhardness from dense and porous areas. 5. Weibull modulus values of microhardness are higher in the dense area than in the porous area, since microhardness values are less scattered in the dense area. The Weibull modulus of microhardness depends not only on the base material but is also related to the applied load and indent position, since the Weibull modulus value changes with change in applied load and indent position. The microhardness and elastic modulus of plasma sprayed HA coatings were investigated in terms of indentation angle, testing direction, different applied load, and indent location throughout the coating thickness using Knoop indentation. 133 Page

154 Chapter 7 Microhardness study using indentation techniques Statistical analyses were used to study the variability of the measured data. The following conclusions can be drawn from this Knoop indentation study: 1. The dependence of microhardness and elastic modulus on the indentation angle is a parabolic curve. Maximum microhardness and elastic modulus were found at 45⁰ indentation angle. H 0, H 45 and H 90 values are found to approximately satisfy Pythagoras theorem. 2. Microhardness and elastic modulus is higher on the top surface than the cross-section, since the top surface is less porous and is almost crack free compared to the cross-section of the coatings. 3. Microhardness distribution follows a parabolic trendline for all applied loads at different locations on the cross-section. Maximum microhardness is found in the central position (175 µm) of the coating s cross-section. Elastic modulus values are almost constant on the coating cross-section for higher loads (300 and 500 gf), since the area of measurement is greater and the minor diagonal is long enough compared to the lower loads (50 and 100 gf). However, elastic modulus shows a variation along the coating thickness for lower loads (50 and 100 gf). 4. Microhardness and elastic modulus decreases with increasing applied loads, since the increase in applied load increases the indenter testing area that covers more large and small pores, which, in turn, may decrease the microhardness and elastic modulus. 5. On the cross-section, the maximum Weibull modulus of microhardness (m H ) and elastic modulus (m E ) are found at the central position (175 µm) of the coatings. 6. Depth of indentation remains almost unchanged on the cross-section with a change of indent location for lower loads (50 and 100 gf). This depth shows variation changes for higher loads (300 and 500 gf). An increase in applied load increases the depth of indentation. 7. The frequency distribution of Knoop microhardness indicates that a bimodal distribution may exist for smaller loads (i.e., 50 and 100 gf), whereas it cannot be clearly distinguished for higher loads (i.e., 300 and 500 gf). 134 Page

155 Chapter 7 Microhardness study using indentation techniques 8. Student s t-test demonstrates that T stat values are higher for load 50 vs. 500 gf and lower for load 300 vs. 500 gf. The probability values for load 300 vs. 500 gf show greater than 0.05 in most of the cases, whereas other load comparisons show less than These statistical results indicate that data sets for loads of 300 and 500 gf are similar; whereas other data sets may be different from one another. 9. Splat movement evidence was visible due to the indentation on the microstructure. 10. It is recommended to use high magnification SEM picture for measuring elastic modulus, especially for lower loads (50 and 100 gf) to overcome the measurement error of the minor diagonal. 135 Page

156 Chapter 8 Sol-gel modified thermal spray coatings 8. Sol-gel modified thermal spray coatings 8.1. Introduction HA has been widely studied and clinically applied for bone substitution and bone reconstruction in the human skeletal system. This is due to it possessing the crystal structure and chemical composition identical to apatite, which makes it suitable for such applications [205]. It has attracted promising interest in areas such as bioactive and biocompatible coatings on metal implants in dentistry, maxillofacial surgery, bone filler and orthopaedics [24, 205, ]. Clinical observation of coatings has indicated failure by chipping, spalling, delamination and dissolution for explanted endoprostheses due to the brittle nature of HA coatings [257]. Among several deposition techniques, thermal spray, in particular plasma spray, is very popular for depositing HA coatings. Plasma spraying of HA offers good mechanical properties with superior osteoconductivity of HA [272]. However, plasma spray coatings contain cracks, pores and residual stress that reduce the durability, mechanical properties and can results in partial or complete delamination of the coatings. On the other hand, pores and cracks are beneficial for bone growth. Thus, a novel technique was applied to fulfil these two conflicting requirements. Sol-gel coatings were applied onto the thermal spray coating to fill up the pores and cracks; and thereby strengthen the mechanical properties. These sol-gel coatings could also act as an active top layer, as shown in Fig These active top layers could dissolve more quickly within the body due to their poor adhesion compared to the thermal spray coating. They could, thus, provide calcium and phosphate ions; which have been reported to increase the bone growth on the coating surface [288]. Figure 8-1 Sol-gel modified thermal spray coatings with active top layer. 136 Page

157 Chapter 8 Sol-gel modified thermal spray coatings 8.2. Methodology Typical thermal sprayed HA coatings were prepared by using plasma spray parameters, as shown in Table 8-1. These typical thermal spray coatings were modified by sol-gel HA solution. Sol-gel HA solution was prepared by dissolving pure HA powder into dilute nitric acid. Dilute nitric acid was prepared by mixing 3.2 ml of nitric acid with 50 ml of distilled water and then it was stirred for 30 minutes using a magnetic stirrer. Then, 3 g of HA powder was mixed with dilute nitric acid and further stirred for 1 hour. In the next step, 1 g of HA powder was added and stirred for 1 hour and this step was repeated once. The concentration of HA in the solution became 0.2 M. Then, the thermal spray HA coating sample (20 10 mm) was dipped into the prepared solution and withdrawn slowly after 1 min. The as-dipped liquid coating was dried in a vacuum hood for 3 hours, after which, it was heated using an air furnace at 200 ºC for 2 hours and subsequently cooled to room temperature. A sol-gel modified thermal spray sample was sectioned into small pieces and then ground and polished to remove the scratches. Grinding (grit sizes P600, P800, P1200) and polishing (15, 5, and 1 µm) was performed with care so that the sol-gel coatings were subjected to minimal effects during the metallographic preparation. However, evidence was seen on the cross-section that indicated delamination of the sol-gel coatings. As a result, a thin gold coating (200 nm thicknesses) was deposited on the dried, as-dipped sol-gel modified sample top surface using a DC magnetron sputtering (CMS 18 Kurt J Lesker-USA sputtering unit) to protect the sol-gel coatings from delamination during metallographic preparation. The base pressure was set at 5x10-8 torr with an argon gas flow rate of about 40 sccm. The working pressure was 4 x10-3 torr and the power was 150 W. Samples were examined by SEM after 3 days and 7 days of sol-gel treatment. 137 Page

158 Chapter 8 Sol-gel modified thermal spray coatings Table 8-1 Plasma spray parameters. Parameters Value Power (kw) 40 Primary gas flow rate, Ar (slpm) 50 Secondary gas flow rate, He (slpm) 12 Carrier gas flow rate, Ar (slpm) 7 Powder feed rate (g/min) 27 Stand-off distance (cm) Effects of sol-gel coatings on microstructure improvement Figure 8-2 demonstrates that a typical thermal spray coating surface consists of melted lamellae and partially melted lamellae. Figure 8-3 and Fig. 8-4 shows the top surface of sol-gel modified thermal spray coatings after 3 days and 7 days of sol-gel treatment, respectively. Figure 8-3 indicates a variation in several shapes on the top surface; whereas Fig. 8-4 shows the final stage of the top surface after completion of crystal growth. Figure 8-3 (a) shows the dried sol-gel solution with evidence of several HA particle shapes and Fig. 8-3 (b) shows evidence of crystal growth on the top surface with the presence of spherical HA particles. Figure 8-3 (c) exhibits thin top layers that cover the whole coating, which could be the previous stage of crystallization or the start of the crystallization step. The reasoning here is that, Fig. 8-3 (d) shows the existence of a thin layer that covers the coating and crystal growth of the coatings together. This morphology indicates that some thin layers could already have been converted to crystal and that some regions are under a thin top layer that is still in the process of crystal growth. Figure 8-3 shows the top surface after 7 days from the sol-gel treatment day, which indicates that crystallization processes are complete on the top surface. Crystallization of the top surface occurs in a normal temperature range. Some spherical particles, which could be partially dissolved or undissolved HA particles, are visible on the top surface. Also, evidence of platelet particles and crystal growth are discerned on the top surface. 138 Page

159 Chapter 8 Sol-gel modified thermal spray coatings Figure 8-2 Typical thermal spray coatings top surface. Figure 8-3 Sol-gel modified thermal spray coating top surface morphology after 3 days from the sol-gel treatment day. 139 Page

160 Chapter 8 Sol-gel modified thermal spray coatings Figure 8-4 Sol-gel modified thermal spray coating top surface after 7 days from the sol-gel treatment day. Figure 8-5 represents a typical thermal spray coating cross-section with many pores and cracks. In comparison, Fig. 8-6 shows a sol-gel modified thermal spray coating with fewer pores and almost crack free coatings since the sol-gel solution can penetrate to the thermal spray coating that fills the pores and cracks. However, there is a large gap that exists at the coating-epoxy interface, as shown in Fig From Fig. 8-3, it can be seen that the top surface shows some partially dissolved spherical particles and some platelet particles. During polishing of the cross-section of the sol-gel modified thermal spray coatings, these particles could be removed from the surface which would evolve small gaps between the coating and epoxy. Due to these small gaps, the rest of the sol-gel layer coating may be removed from 140 Page

161 Chapter 8 Sol-gel modified thermal spray coatings the coating-epoxy interface during polishing and, therefore create the large gap between the epoxy and the coating. Figure 8-7 shows a cross-section image after sol-gel treatment on the thermal spray coatings. Thin sol-gel coating layers with few HA particles are visible in Fig HA particles in the sol-gel coatings are denoted as particle and sol-gel coatings formed from sol-gel solution are denoted as sol-gel solution in this chapter. Figure 8-5 Typical thermal spray coating cross-section. Figure 8-6 Sol-gel modified thermal spray coating cross-section. 141 Page

162 Chapter 8 Sol-gel modified thermal spray coatings Figure 8-7 Sol-gel modified thermal spray coating cross-section after using gold coatings by PVD technique on the top surface of the sample Coating properties Porosity Comparisons of porosity variation for thermal spray coatings and sol-gel modified thermal spray coatings are presented in Fig. 8-8 with respect to the different coating areas (i.e., coating-epoxy, coating-centre, and substrate-coating area). Porosity was reduced the most near the coating-epoxy interface area; since the sol-gel solution can penetrate most at this location. Porosity of sol-gel modified thermal spray coatings increased as the measurement position moved from the coating-epoxy interface to the substrate-coating interface. The sol-gel solution penetration decreased with the increase in distance from the surface. Sol-gel modified thermal spray coatings showed 54% less total porosity than the porosity of the total typical thermal spray coatings. 142 Page