[8p-S202-1~8] Lab to Fab: Accelerating R&D to Mass Production via Semiconductor DX

4:45 PM - 5:25 PM JST(7:45 AM - 8:25 AM UTC)

[8p-S202-6] Accelerated Discovery of Materials for Semiconductor Cleaning through Materials Informatics and Quantum Annealing

〇Shogo Kunieda¹, Yosuke Hanawa¹, Shigeru Takatsuji¹, Yuta Sasaki¹, Kazuki Muro², Renichiro Haba², Shinobu Fujikura² (1.SCREEN Holdings, 2.Sigma-i)

Keywords:

Materials Informatics,Quantum Annealing,Digital Transformation

With the miniaturization and three-dimensional structuring of semiconductors, pattern collapse during cleaning and drying processes has become a critical issue. Sublimation drying can suppress pattern collapse, but selecting appropriate sublimation materials is essential. In this study, we utilized machine learning and optimization techniques to efficiently select and evaluate promising materials based on a small number of experimental data. In the presentation, we also introduce case studies on process optimization using material property prediction and image analysis.