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AoE Project Nano-Process Modeling: Lithography modeling and device fabrication Philip Chan, Mansun Chan Department of ECE, HKUST Edmund Lam Department.

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Presentation on theme: "AoE Project Nano-Process Modeling: Lithography modeling and device fabrication Philip Chan, Mansun Chan Department of ECE, HKUST Edmund Lam Department."— Presentation transcript:

1 AoE Project Nano-Process Modeling: Lithography modeling and device fabrication Philip Chan, Mansun Chan Department of ECE, HKUST Edmund Lam Department of EEE, HKU

2 The role of Processing Modeling Processing Lithography Post-Lithography Processing Device Structure Device Characteristics Circuit Simulation Lateral Dimension (and variation) Lateral/vertical Dimensions, dopant/substrate interaction Structural parameters Current-voltage, charge, transport, quantum characteristics Inter-connected devices characteristics

3 Lithography Layout and Lithography *Mark E. Mason, DFM EDA Technology: A Lithographic Perspective, 2007 Symposium on VLSI Technology Layout2D SEM3D image Lithography is the driving force for scaling Lithography also becomes the major source of uncertainties

4 Lithography Impact on Device Characteristics Gate length and parasitics variation Leakage, noise margin and power consumption variation currently modeled as many transistors in parallel in 22nm technology, need to account for atomic level variations Lithography models needed for Design for Manufacturing (DFM)

5 Lithography Potential Lithography Solutions *Source: ITRS Lithography 2008

6 Lithography Optical Projection Lithography *Source: A. Wong, Resolution Enhancement Techniques in Optical Lithography. SPIE Press, 2001. p. 24

7 Lithography Mask Design Forward problem: from mask design to circuit output Inverse problem: from circuit output to mask design

8 Lithography Mask Design Pre-distort the mask!  needs optical system modeling Optical proximity correction (OPC) Rule-based and model-based maskcircuit Source adjustment Off-axis illumination (OAI) Source-mask optimization (SMO)

9 Lithography Design for Manufacturing (I) Process variations e.g. focus, dose Impact circuit behavior Require “robust” design “original” “robust” mask infocus defocus

10 Lithography Design for Manufacturing (II) Mask manufacturability (cost) need “regularization” Few segments Rectilinear shapes No close shapes (hotspots) unregularized regularized

11 post-Lithography Beyond Lithography Controlling vertical dimensions Further lateral dimension reduction The most common method to fabricate nanowire MOSFETs: stress limited oxidation Y. Tian, 2007 IEDM CEA/LETI, IEDM 2008 HKUST, EDL May 2009

12 post-Lithography Sidewall Etching Profile ♦ Existing Model *R. Zhou, et. al., “Simulation of the Bosch process with a string-cell hybrid method”, J. of Micromechanics and Microengineering, v. 14 (2004), 851-858 ♦ Cannot explain the semicircular shape in single sidewall

13 The Etch-Deposition Model ♦ Etching with deposition C 4 F 8 – passivation agentSF 6 – etching agent ♦ deposited polymer only removed by the anisotropic component of the SF 6 etchant ♦ final shape depends on the ratio of the etch rate versus deposition rate post-Lithography

14 Oxidation modeling ♦ Can stress really limit the oxidation? post-Lithography ♦ Experimental results show no limit at high temperature ♦ No model can clearly capture these effects

15 Existing Model (Deal-Grove) post-Lithography

16 Crystal Orientation ♦ Crystal orientation dependent oxidation has not been accounted for post-Lithography ♦ Oxidation model has to be improved for non-planar devices due to multiple surfaces used

17 DFM Objectives Devices Task Lithography model Post-lithography processing model Model dependent intermediate device parameters Characteristic Variations Final geometry parameters Effects of irregular cross-sectional geometry on device characteristics Non-uniform quantum effects with non-circular/non-planar devices

18 Tasks Lithography Modeling ♦ Develop lithographic model, incorporating particularly parameters for the light source, and 3D mask effects ♦ Develop mask synthesis algorithms that are robustness against mask variations ♦ Incorporate regularization methods in solving inverse problems in imaging to tackle mask complexity ♦ Investigate the resulting parameter variations for input to the post-lithography processes

19 Etching/Oxidation Model Tasks ♦ Develop post-lithography atomic etching model base on etching with co-deposition ♦ Experimentally verify the effect of stress on nano-scale oxidation ♦ Develop crystal orientation dependent oxidation model ♦ Incorporate the new models into a process simulator to predict the final shape of the device

20 Process-Aware Device Modeling Tasks ♦ Study the impact of geometrical variation (e.g. non- uniform lateral dimension, non-ideal cross-section, atomic level dopant fluctuation) on the I-V characteristics including quantum effects ♦ Develop model based with an orthogonal set of parameters that correlate the geometry data to electrical characteristics ♦ Device fabrication and model verification

21 Second Phase of The Project Tasks ♦ To Integrate the process models and device models to take in lithography process parameters and produce the corresponding device characteristics ♦ From the variations of process to predict the variation of device characteristics ♦ Develop inverse process algorithm to produce lithography patterns and process parameters to minimize the variation of device characteristics


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