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Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

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Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
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AI-based analysis algorithm incorporating nanoscale structural variations and measurement-angle misalignment

Juwon Jung1, Leeju Hwang1, Nagyeong Kim1

  • 1Department of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea.

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|December 22, 2025
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Summary
This summary is machine-generated.

This study introduces an advanced spectroscopic ellipsometry (SE) analysis framework to accurately characterize nanoscale structures, accounting for variations and improving metrology for manufacturing.

Keywords:
fabrication-induced structural variationmeasurement-anglenanostructurespectroscopic ellipsometry

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Optical Metrology

Background:

  • Spectroscopic ellipsometry (SE) is crucial for nanoscale characterization but limited by assumptions of perfect periodicity.
  • Fabrication variations and measurement errors reduce accuracy in conventional SE data analysis.
  • Accurate metrology is vital for advanced manufacturing processes in semiconductors, photonics, and displays.

Purpose of the Study:

  • To develop an enhanced SE analysis framework addressing nanoscale structural variations and measurement misalignment.
  • To improve the precision and reliability of SE-based metrology for industrial applications.
  • To enable high-throughput characterization of nanostructures with high accuracy.

Main Methods:

  • Developed an enhanced SE analysis framework using an average Mueller matrix (MM) to represent structural distributions.
  • Introduced a high-throughput neural network for rapid MM generation, approximating rigorous coupled-wave analysis (RCWA) simulations.
  • Validated the framework against RCWA simulations for SiO2 nanogratings and applied it to experimental MM data.

Main Results:

  • The MM-generation model achieved a mean-squared error of 9.99 × 10^-8 MSE against RCWA data.
  • The enhanced analysis framework achieved dimensional prediction errors below 0.4 nm compared to SEM.
  • Demonstrated accurate characterization of nanoscale structures, including 1D SiO2 nanogratings.

Conclusions:

  • The developed SE analysis framework significantly enhances metrology precision for nanoscale structures.
  • This approach accounts for fabrication variations and measurement errors, improving structural parameter prediction.
  • The framework holds potential for advancing high-precision metrology in semiconductor, photonic, and display manufacturing.