Analysis and Classification of non-metallic inclusions in Clean and Ultra-Clean Steels

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1 Analysis and Classification of non-metallic inclusions in Clean and Ultra-Clean Steels Introduction The use of speciality steels in industry is becoming increasingly widespread. These speciality steels have improved mechanical behaviour including improved toughness, machinability, ductility, and fatigue life. An important controlling factor for this superior behaviour is the 'cleanliness' of the steel. This is a measure of the amount and type of small non-metallic inclusions. As demand for clean and ultraclean steels increases, there is a requirement to detect smaller and smaller inclusions in larger sample areas. Methods have been developed using light optical microscopes to classify steels by counting and measuring the inclusions present. However, this requires time and expertise, limits the minimum inclusion size and lacks chemical data. is an automated package developed specifically for the analysis and classification of steel inclusions, using Energy Dispersive X-ray microanalysis () in a scanning electron microscope (SEM). consists of AZtecFeature and Inclusion Classifier. AZtecFeature is used to detect, measure and analyse the inclusions in the Steel. Inclusion Classifier processes the resulting data set to the published standard methods, and includes functionality to plot complex ternary diagrams. This report describes the use of in classifying steel inclusions, including the data processing options and the reporting available. 250 mm 1

2 Inclusion Classifier 4. Matrix Correction Inclusion Classifier is launched from within AZtecFeature and the steel inclusion data set is transferred automatically to this application. The compositional data used in Inclusion Classifier will be the un-normalized apparent concentration. The advantage of using apparent concentration over normalized weight % is that the size of the inclusions and the surrounding Steel matrix has less influence on the data. 1. Standard Selection Inclusion Classifier will determine steel cleanliness using the following published methods: When analysing inclusions in steel there will probably be some contribution from the steel matrix. With you can correct for this matrix contribution. A spectrum is collected from the steel matrix using AZtecFeature. This composition is then transferred to Inclusion Classifier with the AZtecFeature data set. Using Inclusion Classifier the composition of the Steel matrix can be displayed, Figure 2. A reference element is selected. This should be a major constituent of the matrix and is assumed to be absent from the inclusions. In the example shown, Fe was selected as the reference element. The matrix composition is then removed from the inclusion composition as a ratio of this reference element. 5. Ternary Plot ASTM E2142 and E2283 SS DIN ISO 4967 As shown in Figure 1. It is easy to classify the same data set to more than one standard if required. 2. Rolling Direction Inclusion Classifier assumes that the rolling direction of the sample is either horizontal or vertical in the field of view. Therefore, the sample must be correctly orientated in the microscope chamber before the analysis is undertaken. This orientation is essential for correct calculation of the stringers. 3. Field Size Data collection in AZtecFeature can be undertaken at any magnification, and this magnification will control the field size. The standards used to classify steel inclusions each dictate a field size that should be used, and the field size is recalculated to that specified in the selected standard. Consequently, you can analyze the sample at a high magnification detecting the smallest inclusions, but still classify the data following the rules of the standard. Figure 1 Standard set-up window in Inclusion Classifier Software Figure 2 Matrix Correction step in Inclusion Classifier Ternary plots are often used to study inclusion chemistry. This is a powerful tool for comparing different inclusion types within a sample and for comparing different steel samples. For example, it is an ideal tool for studying the effect of different steel manufacturing processes, such as heat treatments. Within Inclusion Classifier, there is a mini navigator specifically for the definition of ternary plots, shown in Figure 3. There are 6 different plot types available: Element Plot Oxide Plot Area Separation Plot Liquidus Phase Plot Sulphide Plot Compound Weight % Plot When ternary diagrams have been defined, the set-up is saved for future use, making routine analysis and data processing straightforward. The set-up can be recalled using the ternary plot navigator and is linked to the AZtecFeature recipe, so that the specific set-up is loaded when the Inclusion Classifier is launched. Any plot set-up can be easily modified as required. 2 3

3 6. Data Reporting (ii) Oversized The results reported are as required for each individual standard. The processed data is exported automatically into Microsoft Excel and presented on different worksheets. For each standard, the worksheets presented include; (i) Results, (ii) Oversized, (iii) Classification, (iv) Diagrams, (v) Statistics, and (vi) Overview The data for the oversized inclusions is shown in Figure 6. This includes the inclusion number, which corresponds to the particle number given in AZtecFeature so it is easy to identify these inclusions and relocate them under the SEM beam for further analysis. Also included on this table is the size of the inclusion and the inclusion type. (iii) Classification This worksheet includes any class data imported from AZtecFeature. The Inclusion Classifier software does not use the class scheme in any calculations. However, if one is selected then this information is transferred and included with the results. (i) Results: These will be standard specific, for ASTM E2142. This includes severity ratings and stringer measurements, and for DIN 50602, K values are calculated. Figure 3 The Ternary Plot Navigator Figure 6 Data Table - Summary of Oversized Inclusions Included with the results are summary details of the analysis, the standard used for the classification, the field size, the number of fields, and the number of inclusions analyzed and a date stamp. If the total sample area scanned is less than required by the standard, then the classification will be completed, but the results page will include a warning message. An example of results recorded for the ASTM standard is shown in Figure 4. The data includes severity ratings for the different inclusion types (Type A and B are shown) and a summary table giving details of the stringers. This includes the number of stringers identified for each inclusion type with the average, maximum and minimum length. An example of this data is shown in Figure 5. 5 mm Figure 4 Example of results as reported in MS Excel for ASTM Figure 5 Results from Inclusion Classifier - Stringer Statistics 4 5

4 (iv) Diagrams Ternary diagrams are shown on the diagrams worksheet. The example shown in Figure 7 shows an oxide plot, of Type B, C, & D, inclusions where SiO2 and Al2O3 are plotted against CaO + MnO. The sum threshold was set at 30%, and 1752 inclusions were rejected on this basis. 137 Inclusions are plotted 136 were classified as oxides and 1 as an oxysulphide (shown in blue). The same inclusions are plotted on Figure 8. In this example, MgO has been included in the plot and the background has been divided into phases. Figure 7 A Ternary Plot of Mg, Al and Mn + Ca (v) Statistics 900 nm The statistics worksheet gives the summary statistics for the different inclusion types: A, B, C, D, nitrides, carbides, sulphides and stringers. It includes an average calculation of how many inclusions of each type are present in each field. An example of this report is shown in Figure 10. (vi) Overview The inclusion overview shows the relationship between deformable and non-deformable inclusions, shown in the example on Figure 9. This data is plotted for inclusion numbers, length and area. Figure 8 An example of an oxide plot where the background of the plot has been divided into phases Figure 10 Statistics Summary Report Aluminium & titanium oxides form the core of an inclusion with mechanically weaker phases enclosing it. High resolution X-ray mapping exposes the internal variations that define inclusion behaviour. Figure 9 Summary data as presented in the overview worksheet 6 7

5 With an active area up to 150 mm 2, Oxford Instruments X-Max N silicon drift detector delivers the most sensitive performance on the market. It helps to analyse inclusions at the nanoscale. 7. Summary offers a powerful automated solution for the location and analysis of steel inclusions. It is an ideal tool for analysing clean and ultra-clean Steels. Data can be classified to any of four published standard methods, giving results that comply to the selected standard. All of the data is reported in MS Excel, presenting the data in an easily accessible format. There is also the flexibility to plot the data using a range of user defined ternary diagrams. This publication provides outline information only, which (unless agreed by the company in writing) may not form part of any order or contract. Oxford Instruments policy is one of continued improvement and reserves the right to alter, without notice the specification, design or conditions of supply of any product or service. Oxford Instruments acknowledges all trademarks and registrations. AZtec and X-Max are Registered Trademark of Oxford Instruments plc, all other trademarks acknowledged. Oxford Instruments plc, All rights reserved. Document reference: OINA//A/1114.