5 papers
Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery
Mingze Li, Yu Rong, Songyou Li +16
Artificial intelligence has accelerated materials discovery through high-throughput prediction and generation, yet the decision problem remains a formidable bottleneck. While curre…
Experimental Powder X-ray Diffraction Crystal Structure Determination with RealPXRD-Solver
Qi Li, Mingyu Guo, Rui Jiao +14
Determining crystal structures from experimental powder X-ray diffraction data remains challenging because peak overlap, preferred orientation, and impurity phases obscure atomic a…
Superconductivity of 30.4 K and its Reemergence under Pressure in Fe1.11Se Synthesized via Ion-exchange and De-intercalation Reaction
Mingzhang Yang, Yuxin Ma, Qi Li +11
Binary stoichiometry FeSe (s-FeSe) is a well-known parent of high-temperature unconventional superconductors owing to its charge-neutral layer, highly tunable structure and electro…
DMFlow: Disordered Materials Generation by Flow Matching
Liming Wu, Rui Jiao, Qi Li +4
The design of materials with tailored properties is crucial for technological progress. However, most deep generative models focus exclusively on perfectly ordered crystals, neglec…
XDXD: End-to-end crystal structure determination with low resolution X-ray diffraction
Jiale Zhao, Cong Liu, Yuxuan Zhang +4
Determining crystal structures from X-ray diffraction data is fundamental across diverse scientific fields, yet remains a significant challenge when data is limited to low resoluti…