6 citations · 12 across the 6 of their papers we have counts for
8 papers
X2SBench: an open benchmark for evaluating crystal structure determination from powder diffraction
Zhiyuan Gao, Juncheng Xiao, Shuchen Pu +7
Progress towards practical powder X-ray diffraction (PXRD) structure determination requires evaluation beyond small crystals and idealized patterns. X2SBench combines 152,587 simul…
Generative crystallographic phasing through invariant relationships
Qi Li, Rui Jiao, Liming Wu +16
Crystal structure determination requires the phases of scattered waves -- yet diffraction measures only their intensities. Direct methods exploit phase invariants but become less r…
CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics
Weida Wang, Dongchen Huang, Jiatong Li +32
We introduce CMPhysBench, designed to assess the proficiency of Large Language Models (LLMs) in Condensed Matter Physics, as a novel Benchmark. CMPhysBench is composed of more than…
Materials discovery acceleration by using condition generative methodology
Caiyuan Ye, Yuzhi Wang, Xintian Xie +10
With the rapid advancement of AI technologies, generative models have been increasingly employed in the exploration of novel materials. By integrating traditional computational app…
SDW driven "magnetic breakdown" in a d-wave altermagnet KVSeO
Xu Yan, Ziyin Song, Juntao Song +3
Altermagnets, combining zero net magnetization with intrinsic spin splitting, demonstrate unique quantum phenomena crucial for spintronic applications. KVSeO is proven to b…
Machine Learning on Multiple Topological Materials Datasets
Yuqing He, Pierre-Paul De Breuck, Hongming Weng +2
A dataset of 35,608 materials with their topological properties is constructed by combining the density functional theory (DFT) results of Materiae and the Topological Materials Da…
Powder Diffraction Crystal Structure Determination Using Generative Models
Qi Li, Rui Jiao, Liming Wu +6
Accurate crystal structure determination is critical across all scientific disciplines involving crystalline materials. However, solving and refining inorganic crystal structures f…
Enhancing Large Language Models with Domain-Specific Knowledge: The Case in Topological Materials
HuangChao Xu, Baohua Zhang, Zhong Jin +3
Large language models (LLMs), such as ChatGPT, have demonstrated impressive performance in the text generation task, showing the ability to understand and respond to complex instru…