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Frontiers of Mechanical Engineering

ISSN 2095-0233

ISSN 2095-0241(Online)

CN 11-5984/TH

Postal Subscription Code 80-975

2018 Impact Factor: 0.989

Front. Mech. Eng.    2024, Vol. 19 Issue (4) : 24    https://doi.org/10.1007/s11465-024-0795-1
Efficient measurement and optical proximity correction modeling to catch lithography pattern shift issues of arbitrarily distributed hole layer
Yaobin FENG1, Jiamin LIU1(), Zhiyang SONG1, Hao JIANG1(), Shiyuan LIU1,2
1. State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
2. Optics Valley Laboratory, Wuhan 430074, China
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Abstract

With the continued shrinking of the critical dimensions (CDs) of wafer patterning, the requirements for modeling precision in optical proximity correction (OPC) increase accordingly. This requirement extends beyond CD controlling accuracy to include pattern alignment accuracy because misalignment can lead to considerable overlay and metal-via coverage issues at advanced nodes, affecting process window and yield. This paper proposes an efficient OPC modeling approach that prioritizes pattern-shift-related elements to tackle the issue accurately. Our method integrates careful measurement selection, the implementation of pattern-shift-aware structures in design, and the manipulation of the cost function during model tuning to establish a robust model. Confirmatory experiments are performed on a via layer fabricated using a negative tone development. Results demonstrate that pattern shifts can be constrained within a range of ±1 nm, remarkably better than the original range of ±3 nm. Furthermore, simulations reveal notable differences between post OPC and original masks when considering pattern shifts at locations sensitive to this phenomenon. Experimental validation confirms the accuracy of the proposed modeling approach, and a firm consistency is observed between the simulation results and experimental data obtained from actual design structures.

Keywords computational lithography      optical proximity correction      modeling      pattern shift      metrology     
Corresponding Author(s): Jiamin LIU,Hao JIANG   
Issue Date: 15 July 2024
 Cite this article:   
Yaobin FENG,Jiamin LIU,Zhiyang SONG, et al. Efficient measurement and optical proximity correction modeling to catch lithography pattern shift issues of arbitrarily distributed hole layer[J]. Front. Mech. Eng., 2024, 19(4): 24.
 URL:  
https://academic.hep.com.cn/fme/EN/10.1007/s11465-024-0795-1
https://academic.hep.com.cn/fme/EN/Y2024/V19/I4/24
Fig.1  (a) Designed array structure for pattern match measurement and (b) SEM image.
Fig.2  (a–b) Error analysis of pitch measurement from two SEM settings.
Fig.3  Pattern shift data from the array’s left edge to its right edge under different pitches: pitches of (a) 287, (b) 410, (c) 451, and (d) 984 nm. Extreme edges with substantial shift can be observed at (a) and (b).
Fig.4  Intensity distribution of aerial image (higher intensity and threshold) and resist image (lower intensity and threshold) at the extreme edge of different pitches: pitches of (a) 287, (b) 410, and (c) 451 nm.
Fig.5  Contour extraction and alignment with SEM image: (a) pattern shift averaged among contours, making the value inaccurate; (b) proper patterns with an anchor for alignment and accurate pattern shift extracted at edges.
Fig.6  Model error analysis on the same set of verification data: models from (a) classical genetic algorithm (GA) with gauges of critical dimensions (CDs) and spaces, (b) machine learning algorithm with the edge placement (EP) gauge, (c) classical GA with the EP gauge, and (d) beta model from only CD information.
Target pitch/nm Wafer pitch/nm Pitch error/nm
Beta model New model
369 366.50 −2.55 0.19
369 367.10 −1.90 0.75
369 366.90 −2.00 0.51
328 325.00 −3.00 −0.42
533 536.30 3.30 0.78
328 324.60 −3.40 −0.78
533 536.14 3.14 0.62
328 325.77 −2.13 0.12
533 576.38 2.48 0.27
328 325.30 −2.50 −0.06
574 576.50 2.70 1.00
369 367.25 −1.65 0.48
369 367.73 −1.37 0.96
Tab.1  Pattern shift error analysis on pitch measurement of sequential patterns from left to right within one row
Fig.7  Wafer verification data of pattern shift with a new mask from a batch of 4 wafers.
Abbreviations
CD Critical dimension
EP Edge placement
FOV Field of view
IBPS Image-based pattern selection
ML Machine learning
OD Optical diameter
OPC Optical proximity correction
RET Resolution enhancement technique
RMS Root mean square
SEM Scanning electron microscope
SRAF Sub-resolution assist feature
TCC Transmission cross-coefficient
  
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