• Home
  • Sitemap
  • Contact us
Article Latest Issue

September, 2023, Vol.32 No 5

This study investigates MoS2 plasma etching, a key process in semiconductor manufacturing, using an ICP-RIE system and machine learning to accurately predict post-etch thickness. The results, validated by Raman spectroscopy and XPS, underscore the synergy between AI and experimental methods in advancing semiconductor techniques.

Latest Issue

  • Dielectric Characteristics of BaTiO3 Solid Solution Substituted with Nb5+, Ta5+, Bi3+, and Sb3+ Ions

  • Machine Learning-Based Prediction of Atomic Layer Control for MoS2 via Reactive Ion Etcher

  • Enhancement of Light-Harvesting Ability on Perovskite Films via Preheated Substrates

  • Spectroscopic Analysis of Effects of Additive Nitrogen on Atmospheric Pressure Ar/HMDS Plasma

  • Analysis of the Characteristics of Radio Frequency Power Transmission Lines Using a Voltage Current Probe in Low-Pressure Discharge

  • Deep Learning Predicts Ar/O2 Plasma in Inductively Coupled Plasma Discharge

  • Computational Study on the Parallel Double-Curling Probe for Multi-Site Electron Density Measurement in Low-Temperature Plasma

Journal information

July, 2023, Vol.32 No 4

Most Cited more +

Characterization of SiO2 Over Poly-Si Mask Etching in Ar/C4F8 Capacitively Coupled Plasma

In Ho Seong , Jang Jae Lee , Chul Hee Cho , Yeong Seok Lee, Si Jun Kim , and Shin Jae You

ASCT 2021; 30(6): 176-182

Micro-Electromechanical Systems-based Sensors and Their Applications

Sophia Nazir and Oh Seok Kwon

ASCT 2022; 31(2): 40-45

ASCT
in Mobile

Accept Here