3 papers
cond-mat.mtrl-sci2026
Chemically Meaningful Textualization Enables Explainable Validation of Metal-Organic Frameworks by Large Language Models
Guobin Zhao, Xiao-Yan Li
Computation-ready metal-organic framework (MOF) databases are essential for high-throughput screening, yet many reported crystal structures remain chemically unreasonable or disord…
cs.AI2026
MOF-Sleuth: Tool-Grounded Reward Alignment for Explainable Fine-Grained MOF CIF Auditing
Yu Liu, Zhiwei Yang, Diandian Guo +7
Large metal-organic framework (MOF) databases support simulation, screening, and machine learning through crystallographic information files (CIFs). Subtle chemical and structural…
physics.chem-ph2025
MOFClassifier: A Machine Learning Approach for Validating Computation-Ready Metal-Organic Frameworks
Guobin Zhao, Pengyu Zhao, Yongchul G. Chung
The computational discovery and design of new crystalline materials, particularly metal-organic frameworks (MOFs), heavily relies on high-quality, computation-ready structural data…