Work

PSYMOF: computational workflow enabling systematic post-synthesis modification of metal-organic frameworks

Year: 2025

Type: article

Abstract: PSYMOF is a fully automated computational platform that introduces a new dimension in metal-organic framework (MOF) design by treating post-synthetic modification (PSM) as a tunable design variable. PSYMOF enables functional groups' systematic and chemically feasible attachment at user-defined substitution levels across predefined bonding sites by integrating cheminformatics, a sterically aware random-walk growth algorithm, and molecular dynamics simulations. To demonstrate its capabilities, we present a comprehensive case study involving the partial functionalization of UiO-66-NH₂ with various functional groups for CO₂/N₂ separation. The simulation results reveal non-monotonic trends in adsorption performance, identifying optimal functionalization levels where enhanced CO₂ affinity balances pore accessibility to maximize separation efficiency. By enabling rapid exploration of the PSM-density axis—an often-overlooked yet critical factor in MOF property tuning—PSYMOF is a powerful and generalizable tool for accelerating the discovery and optimization of functionalized porous materials tailored for gas adsorption and separation.

Source: npj Computational Materials

DOI: 10.1038/s41524-025-01888-9

Authors: Joonhyeok Park, Tao Li, Yongjin Lee

Institutions: Inha University, The University of Adelaide

Language: English

Topic: Metal-Organic Frameworks: Synthesis and Applications

Subfield: Inorganic Chemistry

Field: Chemistry

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,490

Funders: National Research Foundation, National Research Foundation of Korea, Ministry of Science and ICT, South Korea