MOF-ChemUnity: Literature-Informed Large Language Models for Metal-Organic Framework Research.

ABSTRACT: Artificial intelligence (AI) is transforming research in metal-organic frameworks (MOFs), where models trained on structured computational data routinely predict new materials and optimize their properties. This raises a central question: What if we could leverage the full breadth of MOF knowledge, not just structured data sets, but also the scientific literature? For researchers, the literature remains the primary source of knowledge, yet much of its content, including experimental data and expert insight, remains underutilized by AI systems. We introduce MOF-ChemUnity, a structured, extensible, and scalable knowledge graph that unifies MOF data by linking literature-derived insights to crystal structures and computational data sets. By disambiguating MOF names in the literature and conne

SUBMITTER: Pruyn TM 

PROVIDER: S-EPMC12673590 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature