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Use of Sacrificial Nanoparticles to Remove the Effects of Shot-noise in Contact Holes Fabricated by E-beam Lithography
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EPE contribution analysis method of multiple patterning lithography by Monte Carlo and Sobol sensitivity analysis.

Fei Ai1, Xiaojing Su1,2,3, Yajuan Su1,2,3

  • 1School of Integrated Circuits, University of Chinese Academy of Sciences Beijing 101408 China suxiaojing@ime.ac.cn weiyayi@ime.ac.cn.

Nanoscale Advances
|May 28, 2026
PubMed
Summary

Edge placement error (EPE) analysis is crucial for semiconductor manufacturing. This study proposes a method to analyze EPE contributions in multiple litho-etch patterning, identifying key process parameters impacting yield.

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Area of Science:

  • Semiconductor Manufacturing
  • Process Engineering
  • Lithography and Etching

Background:

  • Shrinking critical dimensions in semiconductor technologies necessitate tighter process margins.
  • Multiple patterning schemes amplify the importance of edge placement error (EPE) analysis for process performance and yield.
  • Accurate EPE assessment is vital for maintaining in-line process control.

Purpose of the Study:

  • To propose a novel EPE contribution analysis method for multiple litho-etch (LE) patterning processes.
  • To simulate and quantify the impact of individual process steps on the after-etch-inspection (AEI) contour.
  • To identify critical process parameters influencing AEI critical dimensions (CDs) and spaces.

Main Methods:

  • Development of a process flow model for quadruple patterning.
  • Simulation of resist profiles under varying process conditions.
  • Statistical analysis using Monte Carlo and Sobol sensitivity analysis for AEI contour distribution.
  • Quantification of parameter contributions to AEI CDs and spaces.

Main Results:

  • The after-develop-inspection (ADI) contour significantly impacts EPE.
  • Deposition and etching process parameters show comparable contributions to EPE.
  • Overlay errors primarily affect the distribution of spaces.
  • Sobol sensitivity analysis identified key contributors to EPE.

Conclusions:

  • The proposed method effectively analyzes EPE contributions in quadruple patterning.
  • Understanding parameter impacts guides process optimization for improved yield.
  • Error budgets for individual parameters can be derived to meet EPE specifications.