3rd Annual SFR Workshop, November 8, 2000 8:30 – 9:00 Research and Educational Objectives / Spanos 9:00 – 9:50 Plasma, Diffusion / Graves, Lieberman, Cheung, Haller 9:50 – 10:10 break 10:10 – 11:00 Lithography / Spanos, Neureuther, Bokor 11:00 – 11:50 Sensors & Metrology / Aydil, Poolla, Smith, Dunn 12:00 – 1:00 lunch 1:00 – 1:50 CMP / Dornfeld, Talbot, Spanos 1:50 – 2:40 Integration and Control / Poolla, Spanos 2:40 – 4:30 Poster Session and Discussion, 411, 611, 651 Soda 3:30 – 4:30 Steering Committee Meeting in room 373 Soda 4:30 – 5:30 Feedback Session 3rd Annual SFR Workshop, November 8, 2000

Chemical Mechanical Planarization SFR Workshop November 8, 2000 Andrew Chang, Tiger Chang, David Dornfeld, Tanuja Gopal, Edward I. Hwang, Jianfeng Luo, Zhoujie Mao, Costas Spanos, Jan Talbot Berkeley, CA 11/8/2000

CMP Milestones September 30th, 2001 September 30th, 2002 Build integrated CMP model for basic mechanical and chemical elements. Develop periodic grating metrology (Dornfeld, Talbot, Spanos). September 30th, 2002 Integrate initial chemical models into basic CMP model. Validate predicted pattern development. (Dornfeld, Talbot) . September 30th, 2003 Develop comprehensive chemical and mechanical model. Perform experimental and metrological validation. (Dornfeld, Talbot, Spanos) 11/8/2000

We will review the recent activities in these areas Abstract 2001 Milestone: Build integrated CMP model for basic mechanical and chemical elements. Develop periodic grating metrology Key elements involved in this are: Chemical Aspects of CMP (J. Talbot and T.Gopal) Particle Size Distribution in CMP: Modeling and Verification (J. Luo) Slurry Flow Analysis and Integrated CMP Model (Z. Mao) Scratch Testing of Silicon Wafers for Surface Characterization (E. Hwang) Process Monitoring of CMP using Acoustic Emission (A. Chang) Development of periodic grating metrology (C. Spanos and T. Chang) We will review the recent activities in these areas 11/8/2000

Overview X Model Structure & Development Basic Process Mechanism Model Validation Metrology, Process Control, & Optimization Chem Mech Chemical Aspects (JT/TG) X Particle Size Distribution (JL) Slurry Flow (ZM) Surface Effects (EH) Process Monitoring (AC) Grating Metrology (CS/TC) Process control (KP) 11/8/2000

Overview of Integrated Model Slurry Concentration, Abrasive Shape, Density, Size and Distribution Down Pressure Pad Roughness Wafer, Pattern,Pad and Polishing Head Geometry and Material Pad Hardness Relative Velocity Slurry Chemicals Chemical Reaction Model (RR0)chem Model of Active Abrasive Number N Model of Material Removal VOL by a Single Abrasive Contact Pressure Model Wafer Hardness Pressure and Velocity Distribution Model (FEA and Dynamics) Fluid Model Physical Mechanism; MRR: N´VOL Preston’s Coefficient Ke (RR0 )mech Dishing & Erosion WIWNU Surface Damage MRR WIDNU WIWNU 11/8/2000

Chemical Aspects of CMP Role of Chemistry - Tanuja Gopal, Jan Talbot UCSD Chemical and electrochemical reactions between material (metal, glass) and constituents of the slurry (oxidizers, complexing agents, pH) Dissolution and passivation Solubility Adsorption of dissolved species on the abrasive particles Colloidal effects Change of mechanical properties by diffusion & reaction of surface 11/8/2000

Mass Transfer Processes (a) movement of solvent into the surface layer under load imposed by abrasive particle (b) surface dissolution under load (c) adsorption of dissolution products onto abrasive particle surface (d) re-adsorption of dissolution products (e) surface dissolution without a load Ref. L. M. Cook, J. Non-Crystalline Solids, 120, 152 (1990). 11/8/2000

Reaction Chemistries Dissolution of glass Dissolution and passivation of W 11/8/2000

Generic Chemical Reactions Dissolution: M(s) + A -> M(aq) + B M(s) + A -> Mn+ + ne- + B Oxidation: M(s) + O -> M-oxide(s) Oxide dissolution: M-oxide(s) + A -> M(aq) + B M-oxide(s) + A -> Mn+ + ne- + B Complexation (to enhance solubility) 11/8/2000

Colloidal Effects Surface charge (zeta potential or isoelectric point, IEP, the pH where the surface charge is neutral) of polished surface and abrasive particle is important (Malik et al.) 11/8/2000

Colloidal effects Maximum polishing rates for glass observed compound IEP ~ solution pH > surface IEP (Cook, 1990) Polishing rate dependent upon colloidal particle - W in KIO3 slurries (Stein et al., J. Electrochem. Soc. 1999) 11/8/2000

Experimental Program Electrochemical/chemical experiments with rotating disk electrode with and without abrasion Measurement of zeta potential of abrasives as function of pH (IEP) and solution chemistry Potentiostat Coun t e r E l e c t rod e RD E R e fe r enc e E l e c t rod e P o li sh i ng P ad 11/8/2000

Modeling of Chemical Effects Electrochemical/chemical dissolution and passivation of surface constituents Colloidal effects (adsorption of dissolved surface to particles or re-adsorption) Solubility changes Change of mechanical properties (hardness, stress) 11/8/2000

Model (RR0)chem Model (RR0 )mech Slurry Concentration, Abrasive Shape, Density, Size and Distribution Down Pressure Pad Roughness Wafer, Pattern,Pad and Polishing Head Geometry and Material Pad Hardness Relative Velocity Slurry Chemicals Chemical Reaction Model (RR0)chem Model of Active Abrasive Number N Model of Material Removal VOL by a Single Abrasive Contact Pressure Model Wafer Hardness Pressure and Velocity Distribution Model (FEA and Dynamics) Fluid Model Physical Mechanism; MRR: N´VOL Preston’s Coefficient Ke (RR0 )mech Dishing & Erosion WIWNU Surface Damage MRR WIDNU WIWNU 11/8/2000

Synergistic Effects MRR = kchem (RRmech)o + kmech (RRchem)o (RRmech)o = mechanical wear = Ke PV (RRchem)o = chem. dissolution = kr exp(-E/RT)PCin Ke affected by surface chemical modification Ci affected by mass transport (i.e., V) Ref.: Y. Gokis & R. Kistler, ECS Meeting Abstract 496, Phoenix, Oct. 2000. 11/8/2000

Potential Results for Chemical MP Modeling Selective chemical slurries: 1) control reaction chemistry 2) control colloidal properties of abrasives and removed material 3) enhance solubility of removed material Material wear properties (eg, hardness) Chemically active pads 11/8/2000

Chemical Effects of CMP Synergistically enhances the rate of material removal with mechanical polishing Influences the colloidal stability of the abrasive particles Undesired effects are unwanted etching and dishing of features and increased surface roughness 11/8/2000

Effect of Particle Size Distribution in CMP Modeling Abrasive Geometry and Size - J. Luo UCB Two Abrasive Geometries Spherical Shape for Obtuse Abrasives Conical Shape for Sharp Abrasives 100nm     X X Schematic of Spherical and Conical Abrasive Shapes in the Model   SEM Picture of Slurry Abrasives for Si CMP (Moon, PhD Thesis, 1999) y Abrasive Size and Size Distribution Nano-Scale Size X Normal Distribution (Xavg , ) and p((Xavg , ) Xavg, Xmax and Standard Deviation  Xmax Xavg Portion of Active Abrasive Schematic of Abrasive Size Distribution 11/8/2000

Role of Abrasive Size in the Architecture of the Integrated CMP Model Contact Mechanics( Pad Topography/Abrasive Size/Pressure ) ? Chemical Reaction Slurry pH Value and so on a12= F2/Hw  V = Vol Abrasive Geometry Material Removal Rate Function: MRR= N Vol= C1Hw-3/2 {1-(1-C2P01/3}P01/2V. Correct on both average scale & local single points Schematic of Wafer-Chemical-Abrasive-Pad Interaction to Model the Volume Removed by A Single Abrasive 1 Surface Damage N Contact Mechanics( Pad Topography/Abrasive Size/Pressure ) Abrasive Size Distribution Abrasive Geometry WIWNU a22= F2/Hp Pad Hardness Xmax-Y=2 Pressure and velocity distribution over wafer-scale WIDNU n Schematic of Wafer-Abrasive-Pad Interaction to Model the Number of Active Abrasive Number Pattern Density Detailed Fluid Model 11/8/2000

MRR As A Function of Particle Size Distribution Before Saturation (Luo & Dornfeld, 2000) MRR as A Function of Down Pressure and Velocity: MRR= N Vol= C1Hw-3/2 {1-(1-C2P01/3}P01/2V. MRR= C3: A Function of Down Pressure, Velocity, Weight Concentration etc. C4: 0.25(4/3)2/3(1/Hp)Ep2/3/b1P01/3 A Function of Down Pressure, Pad Hardness and Pad Topography. Function p: The probability of the appearance of abrasive size Function : Probability density function. Contribution of Active Particle Number Contribution of Active Particle Size (Larger than Xavg) Contribution of Total Number of Particles over the Wafer-Pad Interface MRR as A Function of Particle Size and Size Distribution 11/8/2000

Particle Size Distribution Measurement (II) Dynamical Light Scattering 0.288768 0.88 AA07 0.210633 0.60 AKP15 1.056197 2.00 AA2 0.118959 0.38 AKP30 0.070222 0.29 AKP50 Standard Deviation (m) Mean Size (m) *Bielmann et. al. 1999 11/8/2000

Particle Size Dependence on MRR: Experiment VS. Model Predictions (0.29, 0.07022) (0.38, 0.118959) (0.60, 0.210633) (0.88, 0.288768) (2.0, 1.056197) C4: 0.25(4/3)2/3(1/Hp)Ep2/3/b1P01/3= 0.015 * Bielmann et. al. 1999 11/8/2000

Fraction of Active Particles Based on Model Prediction [0.726, 0.737m] 0.1827% [1.213, 1.231m] 0.1798% [1.720, 1.746m] 0.1815% [0.49, 0.50m] 0.19105% [5.091, 5.169m] 0.1719% 11/8/2000

Relationship between Standard Deviation and MRR Based on Model Prediction Number Dominant Region Size Dominant Region 11/8/2000

2002 & 2003 Goals Develop comprehensive chemical and mechanical model. Perform experimental and metrological validation, by 9/30/2003.   Down Pressure Wafer Smaller contact area Larger contact area H H a 11/8/2000

Slurry Flow Analysis and Integrated CMP Model Zhoujie Mao UCB Motivation Study the effects of slurry flow on the material removal in CMP Develop integrated process model for CMP to provide insight into the MRR and WIWNU Develop process model for environmental impact analysis for CMP 11/8/2000

Overall Picture of Slurry Flow in CMP Side view Polishing plate Polishing pad Wafer Carrier film Carrier Slurry Slurry feeder Two flow stages: slurry flow on the polishing pad, slurry flow between wafer and polishing pad 11/8/2000

Slurry Flow on the pad Slurry Polishing pad Abrasive particle Estimate the abrasive particle settling mechanism on the polishing pad Study the effects of slurry supply rate and slurry delivery position on the material removal rate 11/8/2000

Abrasive Particle Settling Rate Vs. Slurry Supply Rate Rate of Deposition (n/m2/s) Radius (mm) 11/8/2000

Abrasive Particle Settling Rate Vs. Delivery Position Average Settling Rate Beneath Wafer Eccentricity Average Settling Rate (n/m2/s) Radial Position (mm) 11/8/2000

Integrated Slurry Flow Model Slurry flow between wafer and polishing pad Slurry flow inside polishing pad Deformation of wafer Deformation of polishing pad h(x) hp(x) Pad 11/8/2000

2002 & 2003 Goals Develop comprehensive chemical and mechanical model. Perform experimental and metrological validation, by 9/30/2003. Simulation of Integrated CMP model Experimental verification of integrated CMP model (role of active abrasives in mechanical material removal) 11/8/2000

Scratch Testing of Silicon Wafers for Surface Characterization Edward Hwang UCB Motivation Wafer surface characterization is important to understand and model the material removal mechanism in CMP - Scratch testing supports the identification and verification of surface characteristics of the wafer representative of the CMP process - Scratch testing can give insight on the stress levels occurring during the CMP Process 11/8/2000

plastically compressed network Actual CMP Situations Cross Section View bulk not affected by the process polishing pad Si wafer layer 2(order of 20 nm ) plastically compressed network – higher density layer 1(order of a few nm ) highly hydrated, loosely bound network – lower density Trogolo et al “Near Surface Modification of Silica Structure Induced by Chemical/Mechanical Polishing”, J. Materials Science 29 (1994) pp. 4554 - 4558 11/8/2000

Experimental Setup Workpiece: Silicon wafer <100> p-type Pre-CMP Wafers & Post-CMP Wafers Diamond tool: Nose radius: 48μm Feed rate: V=399μm/s Tilt angles: 0.06 degrees. Acoustic emission sensor: DECI Pico-Z AE sensor Data collection: 50kHz sampling rate 11/8/2000

AE signals are proportional to the depth of cut in Layers vs. AE Signals (1) Pre-CMP Wafers AE signals are proportional to the depth of cut in 11/8/2000

Layers vs. AE Signals (2) Post-CMP Wafers 0.00 0.05 0.10 0.15 0.20 0.25 0.30 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 time(s) AE Raw Signals (volts) Air-cut + Layer 1 Layer 2 Bulk 0.35 Unlike the pre-CMP wafers, post-CMP wafers show discontinuous transitions in the AE signal due to penetration of Layer 2. 11/8/2000

Results Observation of distinct signal changes for transitions between Layer 1  Layer 2  bulk supports surface characterization Signal for Layer 2 is observed up to 20 nm depth of cut Highly compressed Layer 2 is more ductile than bulk : - Plastic deformation dominates the material removal mechanism in this regime and should relate to removal rate during CMP SEM images support the verification of the multi-layered wafer surface 11/8/2000

2002 & 2003 Goals Develop comprehensive chemical and mechanical model. Perform experimental and metrological validation, by 9/30/2003. Replicate the scratch testing with AFM machine in order to be closer to actual CMP situations Quantify the wafer surface characteristics in CMP 11/8/2000

Process Monitoring of CMP using Acoustic Emission Andrew Chang UCB Motivation AE monitoring is an applicable diagnostic tool for studying abrasive interaction during CMP Experimental verification for abrasive particle interaction is needed for CMP modeling Alternative sensing methods are in-direct (motor current, pad temperature, etc.) or limited to localized areas of the wafer 11/8/2000

Acoustic Emission Sources in CMP Acoustic emission is highly sensitive to abrasive particle interaction between wafer and pad 11/8/2000

Experimental Setup Pressure = ~ 1 psi Table Speed = 20 – 80 RPM PC Data Acquisition Pre-amplifier (60 dB) Amplifier (40 dB) RMS Filter RMS AE Raw AE Raw Sampling Rate = 2 MHz RMS Sampling Rate = 5 kHz AE Transducer Wafer Pressure = ~ 1 psi Table Speed = 20 – 80 RPM Slurry flowrate = 150 ml/min Polishing Conditions IC 1000/Suba IV stacked pad Pad type ILD 1300, abrasive size (~100 nm) W-Slurry, abrasive size (~37 nm) Alumina slurry, abrasive size (~100 nm) Slurry type Oxide, aluminum, tungsten, copper blanket wafers Test Wafers Toyoda Float Polishing Machine CMP Tool 11/8/2000

AE Ratio Signal Processing ASL HFpeak Dt High Pass Filter >100 kHz Ratio = HFpeak LFpeak Raw AE Signal Low Pass Filter 20-60 kHz ASL LFpeak Dt 11/8/2000

AE Signal for Varied Materials 11/8/2000

Application to Endpoint Detection The sensitivity of acoustic emission to various materials during polishing is ideal for endpoint detection in CMP Pad Pad Oxide Wafer Pad 11/8/2000

Sensitivity to CMP Process Background noise characterization AE is insensitive to low-frequency (audible) noise from CMP tool (motors, belts, etc.) Sensor location (backside of wafer is ideal) isolates signal from process and filters noise Signal from process is sensitive to abrasive particle interaction Signal comparison between deionized water and abrasive slurry Sensitivity to different materials 11/8/2000

2002 & 2003 Goals Develop comprehensive chemical and mechanical model. Perform experimental and metrological validation, by 9/30/2003. Future tests planned with industrial CMP tool manufacturer Further experimental tests for validation of integrated CMP model (role of active abrasives in mechanical material removal) 11/8/2000

Pattern density mask - MIT 96.4 Establishing full-profile metrology for CMP modeling Costas Spanos & Tiger Chang UCB Pattern density mask - MIT 96.4 Feature size 10 m Die size 20mm by 20mm Pattern density ranges from 4% to 100% 11/8/2000

Process Flow The final structure Get the mask files PSG deposition 1 mm PECVD oxide ~2mm Design contact mask Aluminum 0.7 mm CMP Make emulsion mask Pattern Aluminum The final structure 11/8/2000

Results of Experiment (typical) The characteristic length is about 2~3mm; this motivates a new mask design 11/8/2000

New Mask Design The size of the metrology cell is 250m by 250m 2m pitch with 50% pattern density 11/8/2000

Key ideas Oxide Substrate Use Scatterometry to monitor the profile evolution The results can be used for better CMP modeling 11/8/2000

Current status Done mask design and processing in the Lab, 12 wafers are ready to polish Before the characterization experiments, we want to know Is the scatterometer signal sensitive enough for the profile evolution? Simulated a conceptual profile evolution How does the initial profile look like? LEO can give a cross section SEM view (we need to cut the wafer, then can’t do CMP on this wafer anymore!) AFM can give a smooth profile (it needs reliable de-convolution) 11/8/2000

CMP Profile evolution used in GTK simulation 11/8/2000

GTK Metrology Simulation Results We simulated 1 mm feature size, 2 mm pitch and 500nm initial step height, as it polishes. The simulation shows that the response difference was fairly strong and detectable. 11/8/2000

Profiles before polishing (LEO) 11/8/2000

Immediate Metrology Objectives Do measurements using Sopra for the initial structures, compare results with the AFM measurements Build a pseudo response library Design experiments, polish finished wafers and do scatterometry measurements AFM measurements at AMD, refine the library 11/8/2000

Conclusions Chemical effects model and synergy with mechanical effects being developed Integrated model validated for abrasive size and activity Fluid modeling of particle behavior corroborates abrasive activity Extent and behavior of surface modified layer being characterized Sensing system for process monitoring and basic process studies being validated Scatterometry metrology sensitivity study indicates suitability for observing profile evolution 11/8/2000