activity
20242026
most citedEnd-to-End Crystal Structure Prediction from Powder X-Ray Diffraction

6 citations · 8 across the 11 of their papers we have counts for

collaborators

11 papers

cond-mat.mtrl-sci2026

Uni-XAS: Alignment-Driven Bidirectional Multimodal Learning for X-ray Absorption Spectroscopy

Suyang Zhong, Yuhao Zhao, Boying Huang +6

X-ray absorption spectroscopy (XAS) is a key technique for probing local atomic environments, yet learning based modeling must bridge two heterogeneous modalities: 1D continuous sp…

physics.chem-ph2026

Ai2-Kit: Streamlining AI-Accelerated Ab Initio Workflows for Complex Chemical Systems

Sheng Bi, Wei-Hong Xu, Yong-Bin Zhuang +47

Molecular simulations of complex chemical systems, such as catalysis, electrochemistry, and energy storage, often need to capture the interplay of effects such as electronic struct…

cs.LG2026

Towards Generalizable and Evidential Nuclear Magnetic Resonance-Based Molecular Structure Elucidation via Large Language Model Agent

Zheng Fang, Chen Yang, Yusen Tan +9

Nuclear Magnetic Resonance (NMR) spectroscopy is the gold standard for molecular structure elucidation, yet interpreting complex spectra for unknown molecules remains a bottleneck…

physics.chem-ph2026

A large-scale foundation model enables simulation-to-real adaptation for nuclear magnetic resonance-based molecular structure analysis

Chen Yang, Zheng Fang, Hanyu Sun +7

Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful tool for molecular structure analysis, and spectral artificial intelligence offers great potential for its rapid and aut…

cond-mat.mtrl-sci2026

Solving the inverse problem of X-ray absorption spectroscopy via physics-informed deep learning

Suyang Zhong, Boying Huang, Pengwei Xu +6

Resolving transient atomic configurations in non-crystalline or dynamic environments remains a fundamental bottleneck in the physical sciences. While X-ray absorption spectroscopy…

cond-mat.mtrl-sci2026

NMRPeak: a ready-to-use intelligent system for molecular structure elucidation enabled by synergistic cross-modal learning

Fanjie Xu, Jinyuan Hu, Jingxiang Zou +8

One-dimensional nuclear magnetic resonance (NMR) spectroscopy is essential for molecular structure elucidation in organic synthesis, drug discovery, natural product characterizatio…

cond-mat.mtrl-sci2026

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…

cs.LG2026

SpecXMaster Technical Report

Yutang Ge, Yaning Cui, Hanzheng Li +15

Intelligent spectroscopy serves as a pivotal element in AI-driven closed-loop scientific discovery, functioning as the critical bridge between matter structure and artificial intel…

physics.chem-ph2025★ 1 cited

NMR-Solver: Automated Structure Elucidation via Large-Scale Spectral Matching and Physics-Guided Fragment Optimization

Yongqi Jin, Jun-Jie Wang, Fanjie Xu +6

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the most powerful and widely used tools for molecular structure elucidation in organic chemistry. However, the interpretatio…

physics.comp-ph2024★ 1 cited

Towards a Unified Benchmark and Framework for Deep Learning-Based Prediction of Nuclear Magnetic Resonance Chemical Shifts

Fanjie Xu, Wentao Guo, Feng Wang +8

The study of structure-spectrum relationships is essential for spectral interpretation, impacting structural elucidation and material design. Predicting spectra from molecular stru…

physics.chem-ph2024★ 6 cited

End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction

Qingsi Lai, Fanjie Xu, Lin Yao +8

Powder X-ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most auto…