4 papers
DynaCrys: Crystal Generation with Dynamic Space-Group Diffusion
Zhuotao Jin, Xiaoyun Wang, Nicholas Brawand +5
The search for new crystalline materials spans an enormous compositional and structural space. Generating candidates in this space requires jointly modeling discrete crystallograph…
Neutron and X-ray Diffraction Reveal the Limits of Long-Range Machine Learning Potentials for Medium-Range Order in Silica Glass
Sai Harshit Balantrapu, Atul C. Thakur, Chris Benmore +1
Glassy silica is a foundational material in optics and electronics, yet accurately predicting its medium-range order (MRO) remains a major challenge for machine-learning interatomi…
Reciprocal Space Attention for Learning Long-Range Interactions
Hariharan Ramasubramanian, Alvaro Vazquez-Mayagoitia, Ganesh Sivaraman +1
Machine learning interatomic potentials (MLIPs) have revolutionized the modeling of materials and molecules by directly fitting to ab initio data. However, while these models excel…
Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry
Tsz Wai Ko, Bowen Deng, Marcel Nassar +7
Graph deep learning models, which incorporate a natural inductive bias for a collection of atoms, are of immense interest in materials science and chemistry. Here, we introduce the…