1. 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

2. 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

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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

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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

16. 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
11/8/2000

17. 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

18. 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

19. 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

20. 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

21. 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

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

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

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

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

26. 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

27. 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

28. 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

29. 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

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

31. 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

32. 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

33. 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

34. 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

35. 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
11/8/2000

36. 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

37. 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

38. 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

39. 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

40. 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

41. 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

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

43. 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

44. 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

45. AE Signal for Varied Materials
11/8/2000

46. 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

47. 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

48. 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

49. 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

50. 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

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

52. 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

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

54. 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

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

56. 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

57. Profiles before polishing (LEO)
11/8/2000

58. 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

59. 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