Feature-level Compensation & Control F LCC CMP April 5, 2006 A UC Discovery Project

FLCC 04/05/2006 FLCC - CMP 2 Chemical Mechanical Planarization - Faculty Team Mechanical Phenomena Chemical Phenomena Interfacial and Colloid Phenomena Jan B. Talbot Chemical Engineering UCSB David A. Dornfeld Mechanical Engineering UCB Fiona M. Doyle Materials Science and Engineering UCB

FLCC 04/05/2006 FLCC - CMP 3 Chemical Mechanical Planarization - Student Team Mechanical Phenomena Chemical Phenomena Interfacial and Colloid Phenomena Robin Ihnfeldt Chem Eng UCSB Sunghoon Lee ME-UCB Alex DeFeo ME-UCB Shantanu Tripathi ME/MSE UCB Jihong Choi ME-UCB Diego Arbelaez ME-UCB Summer ‘06

FLCC 04/05/2006 FLCC - CMP 4 CMP Research Description: The major objective of this work continues to be to establish an effective linkage between capable process models for CMP and its consumables to be applied to process recipe generation and process optimization and linked to device design and other critical processes surrounding CMP. Specific issues include dishing, erosion and overpolishing in metal polishing, which have an impact on circuit performance — all pattern dependent effects at the chip level — wetability effects in polishing, and novel consumable design (pads and abrasives) for optimized performance. We develop integrated feature-level process models which drive process optimization to minimize feature, chip and wafer-level defects. Goals: The final goals remain reliable, verifiable process control in the face of decreasing feature sizes, more complex patterns and more challenging materials, including heterogeneous structures and process models linked to CAD tools for realizing “CMP compatible chip design.”

FLCC 04/05/2006 FLCC - CMP 5 Current Milestones Wetting studies on two phase or multiphase surfaces (CMP Y3.1) Studies on modification of the wetting behavior through optimized use of surfactants and other solvents. Further development of basic understanding of agglomeration/dispersion effects (CMP Y3.2) Experimental analysis of slurry particle size characteristics. Study influence of chemistry on particle behavior for characterizing particle size effects. SMART pad design scaleup and validation (Y3.3) Scaleup (larger size) and validation of SMART pad design for more commercially viable experimental conditions for enhanced planarization with reduced overpolishing (ILD) and dishing and erosion (metal). CMP process model development (Y3.4) Continue development of model for characterizing chip scale pattern dependencies for process optimization with respect to within die and within wafer nonuniformity; validate with specific tests patterns; formulation as “CMP compatible chip design” software. Mechanisms for coupling of chemical and mechanical phenomena in CMP (CMP Y3.5) Develop chemical models to characterize the material removal due to chemical/electrochemical effects, and integrate the chemical models into the comprehensive CMP model to account for mechanical, interfacial and chemical phenomena. Basic material removal model development (Milestone continued from Y2, CMP Y3.6) Continue development of process model and validation with attention to low down force applications/ non-Prestonian material removal as well as subsurface damage effects; applicable to electrolytic polishing (E-CMP) as well.

FLCC 04/05/2006 FLCC - CMP 6 Student Research and Milestones Wetting studies on two phase or multiphase surfaces (CMP Y3.1) Further development of basic understanding of agglomeration/dispersion effects (CMP Y3.2) SMART pad design scaleup and validation (Y3.3) CMP process model development (Y3.4) Mechanisms for coupling of chemical and mechanical phenomena in CMP (CMP Y3.5) Basic material removal model development (Milestone continued from Y2, CMP Y3.6) Jihong Choi Sunghoon Lee Alex DeFeo Robin Ihnfeldt Shantanu Tripathi Diego Arbelaez Shantanu Tripathi

FLCC 04/05/2006 FLCC - CMP 7 Today’s Presentation- see the posters for details - SMART Pad ( Pad Micro Feature Design for CMP with Sensor Integration) Pad prototypes Validation results Sensors for CMP/ Sensor requirements (proposed research) Integrated Tribo-Chemical CMP Model Mechanisms for coupling of chemical and mechanical phenomena in CMP Basic material removal model development Colloidal behavior of slurry particles agglomeration/dispersion effects on CMP Incorporate colloidal and chemical effects into basic material removal model Chip Scale Modeling of High Selectivity STI CMP, Linking HDP-CVD Oxide Topography Application of chip scale model to high selectivity STI process Modeling HDP-CVD oxide topography for CMP model input Model calibration by comparison with test pattern wafer CMP results Model application and verification for production pattern wafer

FLCC 04/05/2006 FLCC - CMP 8 Colloidal behavior of slurry particles –Develop basic understanding of agglomeration/dispersion effects on CMP Characterize slurry colloidal behavior using zeta potential and particle size measurements Understand effects of common chemical additives and presence of copper nanoparticles Study particle size distribution – Gaussian or bimodal? Investigate the effects of slurry chemistry on copper surface hardness Determine the state of the Cu (Cu, CuO, Cu 2+, etc.) both in the slurry and on the wafer surface –Basic material removal model development Incorporate colloidal and chemical effects into the Luo-Dornfeld model (IEEE Trans. on Semi. Manuf. 2001) thru: –particle size and distributions –copper surface hardness

FLCC 04/05/2006 FLCC - CMP 9 Zeta Potential and Particle Size a) Zeta potential and b) particle size versus pH for alumina in a 1 mM KNO 3 solution with and without 0.12 mM copper (error bars indicate standard deviation of particle size distribution). IEP = ~6.5 with and without copper Agglomerates larger with copper at pH >7

FLCC 04/05/2006 FLCC - CMP 10 Potential-pH Diagram for Cu-H 2 O Potential-pH diagram for the copper- water system with [Cu]=10 -4 M at 25°C and 1 atm (M. Pourbaix 1957)

FLCC 04/05/2006 FLCC - CMP 11 Nanohardness Measurements of 1  m Cu on 15 nm Ta on silicon after 10 min exposure to 5 wt% H 2 O 2 slurry solution *A. Jindal and S. V. Babu, J. Electrochemical Society, (2004). Nanomechanical Test Instrument from Hysitron, Inc.

FLCC 04/05/2006 FLCC - CMP 12 Model MRR Predictions MRR predictions improved at low pH values. MRR predictions are highly sensitive to the standard deviation of the particle size. alumina slurry containing 0.1M Glycine and 2.0 wt% H 2 O 2 Lou and Dornfeld model Modified Lou and Dornfeld model ( with full particle size distribution in presence of copper particles and measured hardness)

FLCC 04/05/2006 FLCC - CMP 13 Conclusions Chemical Additives pH has the greatest effect on colloidal behavior Glycine acts as a stabilizing agent for alumina Addition of both glycine and H 2 O 2 increases MRR Agglomerate size distribution becomes broader as zeta potential becomes smaller and particles agglomerate Presence of Cu nano-particles Larger alumina agglomerates at pH>7 Magnitude of zeta potential is slightly lower Luo and Dornfeld model MRR predictions improved using distributions in presence of copper and measured surface hardness

FLCC 04/05/2006 FLCC - CMP 14 Future Goals -Further develop understanding of chemical/colloidal effects Continue to investigate the effects of additives on the copper surface hardness Study colloidal properties of nanoparticles in the slurries Determine the state of the copper (Cu, CuO, etc.) in solution as well as on the wafer surface -Basic material removal rate model development Investigate the model sensitivity to changes in particle size and standard deviation Use CMP data to develop chemical component of FLCC developed models (Luo, Choi)

FLCC 04/05/2006 FLCC - CMP 15 Integrated Tribo-Chemical CMP Model Design & simulation of CMP process Lower pressure copper CMP for porous low-K. With technology node moving 65nm & below impact of defects much greater. CMP process underutilized – possibility of getting higher performance (higher removal rate, higher planarity, lesser defects, lesser pressure) at lower costs. Need for fundamental understanding, need for bringing together different segments of CMP knowledge

FLCC 04/05/2006 FLCC - CMP Main Objective Mechanisms for coupling of chemical and mechanical phenomena in CMP (CMP Y3.5): –Develop chemical models to characterize the material removal due to chemical/electrochemical effects, and integrate the chemical models into the comprehensive CMP model to account for mechanical, interfacial and chemical phenomena. Basic material removal model development (Milestone continued from Y2 (CMP Y3.6)) –Development of process model and validation with attention to low down-force applications/non-Prestonian material removal, as well as subsurface damage effects; applicable to electrolytic polishing (E-CMP) as well.

FLCC 04/05/2006 FLCC - CMP 17 The Problem Integrated Cu CMP Model Colloid Agglomeration Oxidizer Inhibitor Complexing agent Surface Film Pad Pressure/ Velocity Abrasive Needed: an Integrated Copper CMP Model Fluid Mechanics Mass Transfer Needed: understanding of the synergy between different components Interactions: Asperity-copper Abrasive-copper Fluid pressure Contact pressure

FLCC 04/05/2006 FLCC - CMP 18 Challenges Chemical behavior complex – highly sensitive to chemistry, which can change during CMP Mechanical material removal more pronounced Evidence of synergy between chemical and mechanical effects Knowledge Gaps Asperity-copper interaction Local pressure vs material removal Threshold pressure and removal saturation Dissolution vs surface film growth Interval between consequent asperity-wafer contacts Abrasive-copper interaction Soft surface film removal: Plowing Plucking Mechanically enhanced chemical reaction

FLCC 04/05/2006 FLCC - CMP 19 Dornfeld – Luo Model Framework connecting input physical parameters with material removal rate

FLCC 04/05/2006 FLCC - CMP 20 Tribological Models Hydrodynamic Model No pad-wafer contact Thin slurry film (h < 20–50 µm) However, Danyluk et al claim interfacial fluid pressure is sub- ambient. Sundararajan, Thakurta, Gill, J. Electrochem. Soc., 146, (1999) Contact Model: –Indentation depth & MRR  applied pressure –Real contact area  applied pressure –Properties of surface film (thickness, effective hardness) –Material removal per abrasive –#abrasives per asperity –Overall removal rate

FLCC 04/05/2006 FLCC - CMP 21 Electrochemical Behavior of Copper E. Paul, F. Kaufman, et al. J. Electrochem. Soc., 152, G322- G328 (2005) Copper CMP model: method of kinetics Pourbaix diagram: Copper-glycine system S. Aksu & F. M. Doyle, J. Electrochem. Soc., 148, B51-B57 (2001)

FLCC 04/05/2006 FLCC - CMP 22 Passivation in H 2 O 2 Equivalent polarization curves for copper dissolution and polishing in aqueous M glycine solutions containing different amounts of H 2 O 2 at pH 4 S. Aksu & F. M. Doyle, CMP V, Ed. S. Seal, The Electrochemical Society, PV pp (2002) L. Wang & F. M. Doyle, Mat. Res. Soc. Symp. Proc. Vol. 767, F6.5.1 Unexpected passivation observed due to presence of H 2 O 2 Passivation due to catalytic action of Cu(II)- glycine on H 2 O 2 decomposition Mechanism still not fully understood Active behavior Passive behavior Alternating active/passive behavior + mechanical enhancement

FLCC 04/05/2006 FLCC - CMP 23 EQCM of Surface Film L. Wang & F. M. Doyle, unpublished Surface film thickness and composition can be estimated at a given chemistry from charge and mass gain measured with EQCM Rate of formation of surface film can be determined Etch rates, polishing rates, and repassivation kinetics. (W. Lu, J. Zhang, F. Kaufman, & A. C. Hilliera, J. Electrochem. Soc., 152, B17-B22, 2005)

FLCC 04/05/2006 FLCC - CMP 24 Removal Rate Model i active i passive time Interval between two asperity-copper contacts (t 0 ) net charge transfer = q 0 Asperity-copper interaction Function of pad asperity distribution, velocity, down-force By Faraday’s Law: (Mass copper removed)/(Area) = M Cu q 0 /(nF) Can be simplified to a bimodal form

FLCC 04/05/2006 FLCC - CMP 25 Other Considerations Other considerations: Role of Inhibitors (BTA) Particle Agglomeration Surfactant behavior Abrasive “chemical tooth” Fluid dynamics Mass transport More fundamental studies needed for: Asperity-copper interaction to investigate – threshold pressure required for surface film removal; importance of interval between contacts Surface film characterization Verification of mechanically enhanced chemical reaction rates

FLCC 04/05/2006 FLCC - CMP 26 Future Goals Continued development of integrated copper CMP model development, accounting for local variations due to wafer features. Integrated model for ECMP Experiments to investigate Asperity-wafer interaction. Process design for abrasive-less slurries.

FLCC 04/05/2006 FLCC - CMP 27 Chip Scale Modeling of High Selectivity STI CMP, Linking HDP-CVD Oxide Topography Layout pattern density Real pattern density at time t Effective real pattern density Topography at time t slurry characteristics for oxide nitride exposure ? slurry characteristics for nitride yes simulation over ? no END Edge factor Topography at time t+dt no Effective local contact pressure Layout line width Local removal rate yes no nitride exposure ? HDPCVD model Layout pattern density yes Start HDPCVD model Initial topography EPD + 30sec High Selectivity CMP Simulation procedure and results Initial Oxide Topography Future Goals  Model calibration with test CMP results  Model application for different pattern & verification  Linking with other process models  Stand-alone software

FLCC 04/05/2006 FLCC - CMP 28 CMP Pad Micro Feature Design with Sensor Integration Geometry Optimization Open Cell: slurry overflow and slurry will not fill the interface at the contact level. Closed cell: restrict slurry flow and pressure differentials will build, causing hydroplaning. Type C has show the best performance Open Cell Closed Cell A B C D 0.25µm(Cu)/0.25µm (Low-K) pattern Conventional Type C Future Goals Validate lower peak forces with micro scale sensors Pad Sensor GHz range output signals Wireless realtime monitoring Fracture Sensor Test Wafer