1. Andrew Chang, David Dornfeld
Signal Processing and Analysis of Acoustic Emission Monitoring for Chemical Mechanical Polishing
SFR Workshop
May 24, 2001
Andrew Chang, David Dornfeld
Berkeley, CA
2001 GOAL: To build integrated CMP model for basic mechanical and chemical elements. Develop periodic grating metrology by 9/30/2001.
5/24/2001

2. Motivation
Alternative sensing methods are in-direct (motor current, pad temperature, etc.) or limited to localized areas of the wafer
Endpointing for multi-material layer polishing creates tighter process control and minimizes overpolishing.
Strategies for scratch detection and process control can be developed with acoustic emission sensing of the polishing process.
5/24/2001

3. Acoustic Emission Propagation in the Wafer
Schematic view of abrasive particles during polishing (exaggerated view)
Wafer
Sensor
Oil film couplant
Wafer carrier
Carrier ring
Abrasives in slurry
Pad
Polishing plate
Wafer
Individual burst emission waves generated by abrasive particles contacting wafer produce a continuous acoustic emission source.
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4. Primary amplification
Experimental Setup
Pre-amplification &
Primary amplification
PC Data Acquisition
Raw AE
Signal Conditioning
( dB)
Raw Sampling Rate = 2 MHz
CMP Tool
Toyoda Float Polishing Machine
Test Wafers
Bare silicon & copper blanket wafers
Slurry type
ILD 1300, abrasive size (~100 nm)
Alumina slurry, abrasive size (~100 nm)
Pad type
IC 1000/Suba IV stacked pad
Polishing Conditions
Pressure = ~ 1 psi
Table Speed = 50 RPM
Wafer Carrier Speed = Stationary
Slurry flowrate = 150 ml/min
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5. Characterization of Acoustic Emission
Silicon vs. Copper
Characteristic raw acoustic emission signals produced by breaking a 0.5 mm lead on the surface of the material.
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6. Raw Acoustic Emission from CMP Process
Low frequency noise due vibrations from table motor, pad pattern effects, etc.
Filtered raw signal containing high frequency AE content
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7. Frequency Content: Bare Silicon vs. Copper
Less high frequency content for bare silicon wafer.
Increased high frequency content for copper wafer.
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8. Applications for AE in CMP
Endpoint Detection
The characteristics of the acoustic emission signal from various materials can be easily discernable during the polishing process.
Outside noise sources, once characterized, can be minimized and filtered from disturbing the process signal.
Scratch Detection
Scratches and/or other mechanically induced flaws (large agglomeration of particles, contaminants on the pad, etc.) can be detected and used as feedback for purposes of real-time process control.
Abrasive Slurry Design
Energy of the AE signal can be correlated to the active number of abrasive particles during polishing for slurry concentration optimization
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9. 2002 and 2003 Goals
Integrate initial chemical models into basic CMP model. Validate predicted pattern development by 9/30/2002.
Develop comprehensive chemical and mechanical model. Perform experimental and metrological validation by 9/30/2003.
5/24/2001