GTC Silicon Valley-2019 ID:S9843:A Machine Learning Method in Computational Materials Science
Xueyuan Liu(Chinese Academy of Sciences, Computer Network Information Center)
We'll discuss our work using neural networks to fit the interatomic potential function and describe how we tested the network's potential function in atomic simulation software. This method has lower computational cost than traditional density functional theory methods. We'll show how our work is applicable to different atom types and architectures and how it avoids relying on the physical model. Instead, it uses a purely mathematical representation, which reduces the need for human intervention.