1 Chemical Mechanical Planarization SFR Workshop & Review November 14, 2002 David Dornfeld, Fiona Doyle, Costas Spanos, Jan Talbot Berkeley, CA
2 Focus of this presentation CMP research milestones in SFR Overview of SFR vision for CMP process modeling validation metrology application Details of these and other key areas in posters! (Review past SFR presentations for more details)
3 CMP Broad Milestones September 30 th, 2001 Build integrated CMP model for basic mechanical and chemical elements. Develop periodic grating metrology (Dornfeld, Doyle, Spanos,Talbot). Model Outline Progressing- initial chemical and mechanical modules in development; Simulation software prototype; Matlab-based model in development. September 30 th, 2002 Integrate initial chemical models into basic CMP model. Validate predicted pattern development. Integrated process simulation with reduced parametric-metrology tuned MatLab-based model; Simulation model prototyped. (Dornfeld, Doyle, Poola, Spanos,Talbot). September 30 th, 2003 Develop comprehensive chemical and mechanical model. Perform experimental and metrological validation. Model enhancement and validation proceed; metrology validation underway (Dornfeld, Doyle, Spanos, Talbot)
4 Research Team modeling F. Doyle, Ling Wang, Amnuaysak Chianpairot D. Dornfeld, (MSME, B) E. Hwang, S. Lee, J. Luo (ME, B) optimization J. Talbot, T. Gopal (ChemE, SD) K. Poola, (ME, B) C. Spanos, R. Chang (EECS, B) validation metrology
5 CMP Parameters Input Parameters Pad Fiber Structure Conditioning Compressibility Modulus Output Parameters Material Removal Wafer Slurry ph Oxidizers Buffering Agents, Abrasive Concentration Abrasive Geometry and Size Distribution Wafer Geometry and Materials Process Pressure Velocity Temperature Slurry Flow Polish Time CMP WIWNU (Within-Wafer Non-Uniform Material Removal) WIDNU (Within-Die Non- Uniform Material Removal) Surface Quality Roughness, Scratching Die Surface
6 CMP Research in SFR PROCESS MODELING --parameters -pad -pad -abrasive -chemistry --materials SOFTWARE PACKAGING VALIDATION --SFR SFR testing --published data data --partner testing -other (3 (3 rd rd party party and and RPI) RPI) METROLOGY --scatterometry --mask & e-test --AE AE endpoint PROCESS APPLICATIONS -design --optimization -evaluation TOOL & CONSUMABLES --pad pad design --abrasive design --machine design DEVICE DESIGN --lithography --layout -materials
7 Process Modeling FUNDAMENTALS chemical effects mechanical effects Four Interactions: Wafer-Pad Interaction; abrasive chemistry Pad-Abrasive Interaction; Wafer-Slurry Chemical materials effects Interaction; Wafer-Abrasive Interaction Vol Chemically Influenced Wafer Surface Wafer Abrasive particles in Fluid (All inactive) Polishing pad Pad asperity Abrasive particles on Contact area with number N Active abrasives on Contact area
8 FUNDAMENTALS chemical effects mechanical effects abrasive chemistry materials effects several nanometer Process Modeling, cont d Why do we care about passivation? Pad Asperities Abrasive Particles Layer of Liquid between Asperities and Passive Film Passive Film of Copper Slurry Solution Bottom Harder Layer Semiconductor Substrate Layer of Copper Upper Softer Hydrated Layer Kaufman s Model for Chemical Mechanical Planarization Substrate of Metal Passivation Layer
9 Software Development SOFTWARE PACKAGING Real time visualization and computation
VALIDATION --SFR SFR testing --published data data --partner testing -other MRR vs time for differing pattern densities Normalized Remaining Step Height 1.1 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 20 40 60 80 100 120 140 Polishing Time (Second) 10 Validation Conductance (S) (normalized by the length of each line) Experimental (PD= 0.9) Experimental (PD= 0.85) Experimental (PD= 0.8) Experimental (PD= 0.67) Experimental (PD=0.5) Experimental (PD=0.2) M odel (PD= 0.9) M odel (PD= 0.85) M odel (PD= 0.8) M odel (PD= 0.67) M odel (PD= 0.5) M odel (PD= 0.2) Experimental data from Stavreva et. al., Microelectronic Engineering, Vol. 33, 1997. Erosion and Dishing Extraction from E-test Results Line width (micron)
11 Metrology METROLOGY --scatterometry --mask & e-test --AE AE endpoint AE 0.018 Signals(V) 0.016 0.014 0.012 0.010 0.008 A B 0.006 0 20 40 60 80 100 120 140 160 180 AE Data for STI CMP C D Time(sec) A B C D O x Nitride E-test structure for copper dishing
12 Model Implementation - Process PROCESS APPLICATIONS -design --optimization -evaluation Polishing Head and Platen Design, Pattern Design Pressure and Velocity Distribution optimization Non-Uniformity MRR 3 B 2 Down Pressure and Velocity Dependency of Material Removal optimization A 1 Consumable Parameters including Pad Topography, Pad Material and Abrasive Size MRR 0 K pe Framework of Non-Uniformity optimization P min P avg Pma x The material removal rate equation for different consumable combinations P 0
13 Model Implementation - Pad Materials/Shape TOOL & CONSUMABLES --pad pad design --abrasive design --machine design Pad Topography Wafer-Pad Contact under Down Pressure P 0 Contact area H= H stage 1 S 1 =Df 1 2 R Contact Pressure P P 0 1/3 Area A in Contact (Micro- Scale Size) After deformation Area-pressure relationship can be affected by material and geometry pressure
14 Model Implementation - Pad Design TOOL & CONSUMABLES --pad pad design --abrasive design --machine design 150um 50um(space) Top View Hard Material (i.e. high Young s modulus) Prototype surface, 55X Software surface Soft Material (i.e. high compressibility) Side View SMART pad surface
15 Model Implementation - Pad Fabrication TOOL & CONSUMABLES --pad pad design --abrasive design --machine design Soft polymer Soft part molding SMART pad for CMP 50µm 200µm Emulsion mask Si Mold with pockets Silicon grass after DRIE
16 Model Implementation - Abrasive Design TOOL & CONSUMABLES --pad pad design --abrasive design --machine design (X avg, σ) g 1 g 2 X avg Size Distribution Φ g Stage 1 Abrasive number n C/X avg 3 Material Removal Rate (nm/min) 800 700 600 500 400 300 200 100 0 (0.29µm, 0.07022µm) (0.60, 0.210633) (0.38, 0.118959) (0.88, 0.288768) y = 314.77x -0.6695 Experimental Mean MRR Prediction of the Model Power (Experimental Mean MRR) Power (Prediction of the Model) y = 325.1x -0.6411 0 0.5 1 1.5 2 2.5 Bielmann et. al., Electrochem. Letter, 1999 Abrasive Particle Size X avg (10-6 m) (2.0, 1.056197) Stage 2
17 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0-1.0-2.0-3.0-4.0-5.0-6.0-7.0-8.0-9.0-10.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0-1.0-2.0-3.0-4.0-5.0-6.0-7.0-8.0-9.0-10.0-10.0-8.0-6.0-4.0-2.0 0.0 2.0 4.0 6.0 8.0-10.0-8.0-6.0-4.0-2.0 0.0 2.0 4.0 6.0 8.0 10.0 10.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0-1.0-2.0-3.0-4.0-5.0-6.0-7.0-8.0-9.0-10.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0-1.0-2.0-3.0-4.0-5.0-6.0-7.0-8.0-9.0-10.0-10.0-8.0-6.0-4.0-2.0 0.0 2.0 4.0 6.0 8.0-10.0-8.0-6.0-4.0-2.0 0.0 2.0 4.0 6.0 8.0 10.0 10.0 Model Implementation - Machine Design TOOL & CONSUMABLES --pad pad design --abrasive design --machine design Pressure Slurry Inlet Pad Wafer Relative velocity G&P Poli 400 (new machine) Prototype CMP machine (under development)
18 Model Implementation - Device Design DEVICE DESIGN --lithography --layout -materials 0s 40s 60s 1µm 60 40 0 near Patterned SiO 2 Profile development-radial/rotation 1µm 0 60 40 0s 40s 60s Profile development-radial/no rotation
19 What is new at this review? - Passivation of copper during CMP (Doyle, et al) - Electrochemical behavior of oxidizers in CMP systems (Doyle, et al) - Orientation effect in CMP shape evolution (Dornfeld, et al) - SMART pad development and fabrication (Dornfeld, et al) - Abrasive size effects in CMP (Talbot, et al) - Dishing and erosion in Cu Damascene CMP with linear viscoelastic pad behavior (Dornfeld, et al) - Erosion and dishing measurements with e-test in copper damascene process (Spanos, et al) See posters in session for more details!