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

2. FLCC 4/5/2006 FLCC - Sensors and Control 2 Year II Milestones – 1.27.2005 through 1.26.2006 Integrated sensor platform development 2 (M26 YII.16) –Gather CMP and etching rate data and correlate with process variables. Complete preliminary experimental study for CD non-uniformity reducing across the litho-etch sequence (M27 YII.17) –Assess predictive capability of mode, and build optimizing software to compute optimal changes in control parameters. Provide proof of concept test of CD non- uniformity reduction scheme based on direct CD metrology. Zero-footprint Optical Metrology Wafer (Milestone Added, YII.18) –Evaluate and calibrate dielectric thickness monitoring (resolution, sensitivity, and stability). –Metal etch endpoint and pre-endpoint (<50nm) detection and monitoring. Testing the prototype metrology wafer in vacuum environment. Using Spatial CD Correlation in IC Design (M30 Major Revision, YII.19) –Initial experiments on test structures and measurement for extracting spatial correlation characteristics. Aerial Image Metrology (M31 YII.20) –Integrate prototype transducer for use and deployment on a silicon wafer.

3. FLCC 4/5/2006 FLCC - Sensors and Control 3 Year III Milestones – 1.27.2006 through 1.26.2007 Zero-footprint Optical Metrology Wafer (SENS Y3.1) –Modeling and demonstration of metrology wafer for detection and thin-film roughness monitoring. Initiate prototyping of wireless data acquisition/transmission and evaluate performance with measurements made in experimental systems. Complete experimental study for CD non-uniformity reducing across the litho-etch sequence (SENS Y3.2) –Experimentally verify DI & FI CDU improvement using model based optimal control of PEB with various CD objective functions. Using Spatial CD Correlation in IC Design (SENS Y3.3) –Develop test structures and measurement plans for extracting spatial correlation characteristics. Aerial Image Metrology (SENS Y3.4) –Complete the micro-assembly of the commercial CCD with the Si carrier wafer. Integrate the aperture mask and the CCD arrays.

4. FLCC 4/5/2006 FLCC - Sensors and Control 4 Zero-footprint Optical Metrology Wafer – Prototyping and Modeling Student: Vorrada Loryuenyong Faculty: Prof. Nathan Cheung UC Berkeley Milestones  Testing the prototype metrology wafer in vacuum environment  Demonstration of metrology wafer for detection and metal endpoint monitoring, aimed for chemical mechanical polishing (CMP) process

5. FLCC 4/5/2006 FLCC - Sensors and Control 5 Current Accomplishments  To optimize design of the zero-footprint optical metrology wafer, window material effects, LED spectral distribution effects, and incidence angle effects have been quantitatively investigated.  Metal endpoint detection using wet etch has been demonstrated for Cr and Cu.  Time progression of Cu etching near end-point shows multiple mechanisms  CMP Metal etch endpoint mapping set up is in progress. Initial results indicate method can distinguish various slurries. 2006 Main Objectives  Calibrate metal thickness and slurry optical properties  Monitoring of Metal endpoint and pre-endpoint (<50nm) mechanisms for CMP  Complete automatic data acquisition system

6. FLCC 4/5/2006 FLCC - Sensors and Control 6 Feasibility Demonstration Unit Fabrication

7. FLCC 4/5/2006 FLCC - Sensors and Control 7 Choice of Optical Window Materials Simulation Condition: Vacuum ambient, Cu thin film, window thickness 649nm, LED peak wavelength 463nm, the refractive index of Cu: n=1.16, k=2.43. *D.L. Windt, IMD Software. Signal sensing depends greatly on incident angle. Si 3 N 4 optical window shows more signal variation before end-point. Si 3 N 4 Optical window SiO 2 Optical window

8. FLCC 4/5/2006 FLCC - Sensors and Control 8 1.0 × 1.0 mm 2 1.1 × 1.1 mm 2 0.4 × 0.4 mm 2 BROKEN Si 3 N 4 layer 0.9 × 0.9 mm 2 Si 3 N 4 layer Top view Optical Window Mechanical Testing Air Vacuum ambient Test structure Si a a Top view 643 nm Si 3 N 4 optical window Pressure ~ 1 atm Fracture resistance of optical window to differential pressure depends on the window dimension and thickness. 643 nm Si 3 N 4 optical window dimension up to 1.0 × 1.0 mm 2 can withstand the vacuum ambient. Evaluate maximum window size that can withstand a differential pressure of 1 atm

9. FLCC 4/5/2006 FLCC - Sensors and Control 9 [Signal (h) - Signal (h=0)] / Signal (h=0) Time, t (s) Etching Results – Cr Endpoint Detection Experimental Condition: Sputtering deposition, etching solution: Cyantek CR-7 (Perchoric based), nitride window thickness 649±10nm + 500µm quartz slide, LED peak wavelength 463±15nm. h = metal thickness at time t  t = 0 indicates the point where the optical signal start dropping. Near end-point average etching rate ~40-50nm/min. CrCR-7 h = 40-50nm h = 0nm Pre-endpoint region

10. FLCC 4/5/2006 FLCC - Sensors and Control 10 Etching Results – Cu Endpoint Detection Experimental Condition: Sputtering deposition, etching solution: Cyantek CR-7 (Perchoric based), nitride window thickness 649±10nm, LED peak wavelength 463±15nm. h = metal thickness at time t. CuCR-7  t = 0 indicates the point where the optical signal start dropping. Near end-point average etching rate ~500-600nm/min. h = 50-60nm h = 0nm Pre-endpoint region

11. FLCC 4/5/2006 FLCC - Sensors and Control 11  Wafer can distinguish various slurries with no metal  Needs optical data of slurry for model fitting Work in Progress: Endpoint Mapping in Chemical Mechanical Polishing * Products are commercially available from South Bay Technology. The suspension consists of diamond particles in water with trace amount of proprietary suspending agents. Metrology wafer Effects of the surface condition (e.g. slurry particles and volume) water 45  m-sized diamond suspension* 250nm-sized diamond suspension* 3  m-sized diamond suspension* 6  m-sized diamond suspension* DS002-16 DS030-16 DS060-16 DS450-16

12. FLCC 4/5/2006 FLCC - Sensors and Control 12 Students:Jing Xue, Kurt Moen Faculty:Costas J. Spanos Dept of EECS, UC Berkeley Integrated Aerial Image Sensor (IAIS) Accomplishments Completed first principle simulations and optimized design Developed two approaches for mechanical assembly

13. FLCC 4/5/2006 FLCC - Sensors and Control 13 2006 Objectives Complete the micro-assembly of the commercial CCD with the Si carrier wafer. Integrate the aperture mask and the CCD arrays (year III milestone: 1,27,2006 – 1,27,2007) Complete the liquid assembly and polymer assembly to integrating CCD chips to wafer carrier Complete the aperture mask pattern on CCD chips by e-beam lithography for 193nm/248nm stepper Complete the aberration analysis to predict the ability of IAIS calibration Future Goals Package the technology for inclusion into the zero-footprint metrology prototype Integrate prototype transducer for use and development on a wafer

14. FLCC 4/5/2006 FLCC - Sensors and Control 14 Integrated Aerial Image Sensor (IAIS) Concept High spatial frequency aerial image Aperture mask transmission Low spatial frequency detector signal x

15. FLCC 4/5/2006 FLCC - Sensors and Control 15 Integrated Aerial Image Sensor (IAIS) Concept Poly-silicon mask Substrate Photo- detector Mask aperture Φ 1 Φ 2 Φ 3 Φ 1 Φ 2 Φ 3 p-Si Dark contact mask forming a series of spatial frequency shifting apertures. On-wafer photo-detectors to detect the optical signal captured by the aperture mask

16. FLCC 4/5/2006 FLCC - Sensors and Control 16 IAIS Design – Aperture Mask (65nm nodes) wawa t l WiWi WdWd WgWg WtWt  - Si

17. FLCC 4/5/2006 FLCC - Sensors and Control 17 IAIS Design – Aperture Mask (65nm nodes) Pinhole design improves polarization ratio, however transmission efficiency is very low.

18. FLCC 4/5/2006 FLCC - Sensors and Control 18 Aerial Image and Detector Image Reconstruction Annular Illumination: s = 0.89/0.59, NA=0.85, BIM, CD = 65nm Discretize illumination source Mask and projection optics simulation Extract scattering orders at wafer plane IAIS aperture mask simulation Combine partial image to total detector image :

19. FLCC 4/5/2006 FLCC - Sensors and Control 19 Defocus Modeling Aerial image: 90nm L/S Aerial image: 65nm L/S  Precision of determination of focus plane on the level of 10nm, with I dark =10pA/cm2@25 o C, n read =15 electrons, QE = 0.5 * Noise magnified 200 times in the above plots

20. FLCC 4/5/2006 FLCC - Sensors and Control 20 IAIS Assembly – Method I Emmanuel P. Quévy, Roger Howe, Tsu-Jae King, MEMS 2006 Si Wafer Holder liquid Sacrificial layer CCD Aluminum bond pads with FOTS SAM (vapor phase) liquid Liquid evaporation Si Wafer Holder Liquid evaporation Sealing Material CCD front side liquid Sealing Material Removal of sacrificial layer

21. FLCC 4/5/2006 FLCC - Sensors and Control 21 IAIS Assembly fluorinated organosilane monolayer (FOTS) on Al (oxide) bond pads SiO 2 passivation layer   FOTS on Al SiO 2   Bond pads CCD dummy chip bond pads Wafer carrier backside alignment holes Contact angle measurement

22. FLCC 4/5/2006 FLCC - Sensors and Control 22 IAIS Assembly – Method II W1W1 t1t1 a. b. W2W2 W3W3 t3t3 W2W2 t DSP Si wafer SiO 2 Wafer holder Sacrificial layerCCD chip Sealing material

23. FLCC 4/5/2006 FLCC - Sensors and Control 23 Students: Paul Friedberg, Willy Cheung Faculty: Costas J. Spanos Dept of EECS, UC Berkeley Spatial Modeling of Gate Length Variation Accomplishments Completed first test pattern design and received first silicon (currently being debugged and tested) Completed macro modeling that accelerated Monte Carlo framework Used accelerated simulation for better modeling and decomposition of spatial correlation.

24. FLCC 4/5/2006 FLCC - Sensors and Control 24 2006 Main Objective Milestone M30: Spatial CD Correlation in IC Design –Design analytical Monte Carlo simulation framework constructed using macro models –Investigate effects of spatial variation (based on historical study) on circuit performance variability using analytical Monte Carlo framework –Deploy new test structures to explore short-range (0.2-200 micron) spatial variability –Submit additional test structures for manufacture; gather measurements from fabricated test structures –Incorporate new results into Monte Carlo framework 2006 Project Timeline May 1, 2006: Submit revised test structure design to foundry. June 1, 2006: Evaluate impact of preliminary micron-scale gate-length spatial variation results on circuit performance variability using Monte Carlo Framework. August 1, 2006: Submit additional test structure designs for spatial characterization of threshold voltage, oxide thickness, and LER to foundry. Fall, 2006: Complete characterization of poly CD spatial variation.

25. FLCC 4/5/2006 FLCC - Sensors and Control 25 Spatial Correlation Calculation Standardize each CD measurement, using wafer-wide distribution: For each spatial separation considered, calculate correlation r among all within-field pairs of points using: Perform analysis for both residual and original CD distributions:

26. FLCC 4/5/2006 FLCC - Sensors and Control 26 Correlation Structure of “Random” Variation “Random” variation has slight correlation structure at short end of separation distance range mm-scale spatial correlation mostly due to systematic variation. μ m-scale correlation may be significant, needs to be investigated.

27. FLCC 4/5/2006 FLCC - Sensors and Control 27 Analytical MC Simulation Framework For enhanced-speed simulation, recast Monte Carlo, SPICE-based framework as analytical, Matlab-based framework Macro model for NAND2 delay propagation: Using OLS regression, models are fit for delay & output slew for both rising and falling input signals –All modeled coefficients shown to be statistically significant –Model fit (R 2 ) ranges from 0.94 to 0.99 –Accuracy ~ 2%

28. FLCC 4/5/2006 FLCC - Sensors and Control 28 Statistical CD Model Description Does the completeness of the statistical model of CD variation used in MC simulation lead to significantly different delay variability predictions?

29. FLCC 4/5/2006 FLCC - Sensors and Control 29 Effect of Simulated Process Control For various critical path lengths: % Variation Reduction Normalized Delay Variability

30. FLCC 4/5/2006 FLCC - Sensors and Control 30 Test Structure for Mid-Range CD Variation 2x10 Probe frame: 100um x 100um pads, 150um pitch Dense ELM base case test structure: Currently being “debugged” and measured Based on preliminary analysis, structures will be re-designed and submitted for second manufacturing run (May ’06)

31. FLCC 4/5/2006 FLCC - Sensors and Control 31 Variant ELM Submodules Dummy lines used to extend measurable range, explore effects of pattern density and regularity

32. FLCC 4/5/2006 FLCC - Sensors and Control 32 Student: Qiaolin (Charlie) Zhang Faculty: Kameshwar Poolla, Costas Spanos Depts of ME and EECS, UC Berkeley CD Uniformity Control Across Litho-etch Sequence Accomplishments Designed and (almost) completed full experiment at AMD/SDC Control algorithm developed and tested step by step Currently analyzing results while waiting for the last confirmation etch step.

33. FLCC 4/5/2006 FLCC - Sensors and Control 33 2006 Main Objectives Complete preliminary experimental study for CD uniformity improvement across the litho-etch sequence (M27 YII.17) Assess predictive capability of mode, and build optimizing software to compute optimal changes in control parameters. Provide proof of concept test of CD non-uniformity. reduction scheme based on direct CD metrology. Future Goals Official milestone (SENS Y3.2) : –Complete experimental study for CD non-uniformity reducing across the litho-etch sequence –Experimentally verify DI & FI CDU improvement using model based optimal control of PEB with various CD objective functions.

34. FLCC 4/5/2006 FLCC - Sensors and Control 34 The Problem How can we improve the across-wafer CDU and what is the maximum CDU we can achieve? Poor Across-Wafer CD Uniformity Processing Tool Etch Wafer Litho

35. FLCC 4/5/2006 FLCC - Sensors and Control 35 multi-zone bake plate 2 4 3 57 1 Our Approach Compensate for systematic across-wafer CD variation sources across the litho-etch sequence using all available control authority : –Exposure step: die to die dose –PEB step: temperature of multi-zone bake plate –Etch: backside pressure of dual-zone He chuck Exposure PEB / Develop Etch Wafer-level CD Metrology Optimizer Scatterometry/CDSEM dose temperature He pressure 6

36. FLCC 4/5/2006 FLCC - Sensors and Control 36 Develop Inspection (DI) CDU Control DI CD is a function of zone offsets Seen as a constrained nonlinear programming problem Minimize Subject to:

37. FLCC 4/5/2006 FLCC - Sensors and Control 37 Final Inspection (FI) CDU Control Across-wafer FI CD is function of zone offsets Minimize: Plasma etch signature: Subject to: plasma etch bias signature

38. FLCC 4/5/2006 FLCC - Sensors and Control 38 Experimental Data from State of the Art Litho and Etch Tools Baseline Final Inspection, Develop Inspection, Bias Signature (Plate A) DI σ=1.00 FI Bias σ=2.12 P250_1-1 P600_1-2 P800_1-4 σ=2.08 σ=1.27 σ=1.63 σ=2.17 σ=1.08 σ=1.78 σ=1.39 CD data is presented in relative scale

39. FLCC 4/5/2006 FLCC - Sensors and Control 39 Initial Results of Final Inspection CDU Verification Experiment σ=1.00 Measured Baseline FICD Simulated PEB Temperature Adjustment Measured PEB Temperature Adjustment PEB Adjustment Error σ=0.42 Simulated Optimal FICD 58% CDU improvement expected

40. FLCC 4/5/2006 FLCC - Sensors and Control 40 Initial Results of FI CDU Verification Experiment Bias Measured DICD(wf1) Measured DICD(wf2) Desired DICD Simulated DICD DICD control error(wf1) DICD control error(wf2) σ=0.86 σ=0.93