[On-Demand] Unraveling Semiconductor Processes at the Atomic Level

2026年2月16日に開催したウェビナー「原子レベルで解き明かす半導体プロセス～AIシミュレーションの最前線～」のアーカイブ配信です。

Participant comments

- We gained a deeper understanding of what can be done with machine learning in the semiconductor field.

- Even for simulation beginners, the use cases were easy to understand, and I felt that I could apply them to my work.

【Outline】※ This webinar will be conducted in Japanese only.

In recent years, materials development has become more difficult as the required properties become more sophisticated, but there is also a demand for more efficient development. In the semiconductor field in particular, as device miniaturization reaches the atomic layer level, it becomes necessary to control complex surface reactions such as thin film formation and etching. However, there are time and cost limitations in finding optimal solutions from a huge number of parameters through the conventional method of repeated experimentation and evaluation.

To address these challenges, Matlantis proposes accelerating research and development by utilizing atomistic simulations using generalized machine learning potential (PFP). Leveraging the accuracy and speed of PFP, it is applied to the semiconductor field to simulate detailed surface reaction pathways of ALD precursors and etching behavior with hydrogen fluoride. Simulations provide insight into why something happens and what happens when materials or conditions are changed, allowing you to quickly plan the next steps in development.

In this seminar, we will introduce application examples of PFP, mainly in the semiconductor field, and first share what can be seen through simulation. We hope that adding a simulation perspective to your experience will help you find the shortest route to your ideal material.

【Speakers】

Matlantis Corporation

Makoto Sato

After obtaining a PhD in Science from Rikkyo University in 2011, I worked as a postdoctoral researcher at Rikkyo University and Nagoya University, conducting research in physical organic chemistry and organic molecular catalysis. During that time, I also served as a part-time lecturer at Rikkyo University and Ochanomizu University. In 2018, I joined a semiconductor materials-related company, and in 2023, I joined Matlantis after working at ENEOS Corporation 's Central Technical Research Institute. Currently, I am engaged in computational work in the polymer and semiconductor materials fields, where organic chemical reactions are crucial.

Apply here  ※Conducted in Japanese