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Special lecture at High-Performance Materials Week @ Intex Osaka

シュレーディンガー

**Bringing Innovation to Material Development: High-Speed Molecular Simulation and Machine Learning** Recently, there has been a growing interest in digital transformation (DX) across various fields, and efforts to utilize machine learning in the research and development of new materials are advancing. However, leveraging machine learning requires a large amount of experimental data, and gathering that data is not easy. Additionally, it is generally considered difficult to analyze phenomena within materials using only machine learning. At Schrödinger, we are developing a technology that integrates atomic-level simulation with machine learning to address this challenge. In this presentation, we will introduce our initiatives aimed at material development DX, focusing on examples from polymer materials. Date and Time: May 10 (Friday) 14:00 - 14:45 Location: Seminar venue within High-Functionality Materials Week, Intex Osaka Title: Material Development DX through Atomic-Level Simulation and Machine Learning *Advance registration is required to attend the presentation.*