2 papers
cs.LG2026
A Physics-Regulated Neural Framework for Learning 3D Grain Growth Dynamics
Zhihui Tian, Kang Yang, Michael Tonks +2
Grain growth is governed by the reduction in grain boundary energy and exhibits well-established statistical scaling laws. Developing data-driven surrogates that preserve these phy…
cs.LG2026
Scaling Kinetic Monte-Carlo Simulations of Grain Growth with Combined Convolutional and Graph Neural Networks
Zhihui Tian, Ethan Suwandi, Tomas Oppelstrup +3
Graph neural networks (GNN) have emerged as a promising machine learning method for microstructure simulations such as grain growth. However, accurate modeling of realistic grain b…