4 papers
Neural-Network Solutions to Real-Space Charge Density and Generalization
Yuxuan Zeng, Tong Xie, Taoyuze Lv +1
The Hohenberg-Kohn theorem establishes that, in principle, the ground state (GS) charge density contains all GS information of a many-electron system, such that all GS observables…
Chemical-space completeness through iterative crystal-structure generation and model adaptation
Fengyu Xie, Ruoyu Wang, Taoyuze Lv +3
The emergence of deep learning has brought large-scale exploration of crystalline materials closer to practical realization. Yet, universal atomistic models face a practical trade-…
AtomWorld: A Benchmark for Evaluating Spatial Reasoning in Large Language Models on Crystalline Materials
Taoyuze Lv, Alexander Chen, Fengyu Xie +7
Large language models (LLMs) have shown promising potential in scientific research, enabling tasks ranging from knowledge retrieval to property prediction. Existing science benchma…
EAC-Net: Predicting real-space charge density via equivariant atomic contributions
Xuejian Qin, Taoyuze Lv, Zhicheng Zhong
Charge density is central to density functional theory (DFT), as it fully defines the ground-state properties of a material system. Obtaining it with high accuracy is a computation…