Work

Hunting Structural Demons in Digital Reticular Chemistry: Lessons From Metal‐Organic Frameworks

Year: 2026

Type: article

Abstract: Digital reticular chemistry relies on accurate crystal structures to power computational screening, data‐driven discovery, and structure‐property analysis, yet recent studies reveal that more than half of the top‐performing candidates in major computational screening campaigns are chemically invalid. In experimental MOF databases, structural errors arise when disordered or incomplete structural models are incorrectly converted into fully specified simulation inputs. In hypothetical MOF database, structures are complete by construction but may encode chemically implausible oxidation states, coordination environments, or charge distributions. We term these erroneous structural models “structural demons.” This mini‐review asks three questions: where these errors enter, how we find them, and how we prevent them. On the prevention side, the key steps are keeping diffraction data and synthesis details together from the start, using consistent curation when structures enter a database, and filtering topology choices before structure generation. Connecting these steps can keep many bad structures out of downstream databases and reduce the need to fix them later.

Source: Israel Journal of Chemistry

DOI: 10.1002/ijch.70028

Authors: Yongchul G. Chung, Myoung Soo Lah

Institutions: Pusan National University, Ulsan National Institute of Science and Technology

Language: English

Topic: Metal-Organic Frameworks: Synthesis and Applications

Subfield: Inorganic Chemistry

Field: Chemistry

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,650

Funders: National Research Foundation, Ulsan National Institute of Science and Technology, National Research Foundation of Korea