About this document
CHGNet: A Universal Neural Network Potential by SubrahmanyamPattamatta is a document available to read on EtoBox.
The article presents CHGNet, a graph neural network-based machine-learning interatomic potential designed for charge-informed atomistic modeling, addressing challenges in large-scale simulations of solid-state materials. Pretrained on extensive data from the Materials Project, CHGNet incorporates magnetic moments to enhance the representation of electronic states and ionic interactions, enabling accurate modeling of complex phenomena. The study demonstrates CHGNet
- Author
- SubrahmanyamPattamatta
- Language
- EN