3 papers
physics.chem-ph2026
Explainable Molecular Structure Inference from GC--MS with Diffusion Models and LLM Reranking
Changlin Liu, Tianyu Yi, Chengchun Liu +2
GC--EI--MS is an important technique for analyzing volatile and semivolatile compounds in complex samples. However, conventional methods rely heavily on reference spectral library…
physics.chem-ph2026
Hypothesis-and-Refinement Learning of Organic Structures from Multimodal Spectroscopic Data
Chengchun Liu, Zhiyuan Yan, Li Yuan +5
Determining molecular structures from spectroscopic data remains fundamentally challenging because the inverse problem is intrinsically underdetermined: individual spectra are spar…
physics.chem-ph2026
A Cross-Domain Graph Learning Protocol for Single-Step Molecular Geometry Refinement
Chengchun Liu, Wendi Cai, Boxuan Zhao +1
Accurate molecular geometries are a prerequisite for reliable quantum-chemical predictions, yet density functional theory (DFT) optimization remains a major bottleneck for high-thr…