• EJoIC-28-202500115-

Automated Assembly Modeling of Metal-Organic Polyhedra

Reference: European Journal of Inorganic Chemistry 28(26), 202500115, (2025)

Highlights
  • Developed an automated workflow for constructing computation-ready MOPs.
  • Extended assembly modeling to include polyoxometalates in MOP design.
  • Generated MOP geometries closely matching experimental data.
  • Workflow enables identifying MOPs for iodine capture applications.
  • Structures are accessible via TWA-Marie agent with interactive 3D visuals.
Abstract

Graphical abstract Assembly modeling has been achieved in knowledge AI systems for the automated inference of new and rational metal–organic polyhedra (J. Am. Chem. Soc. 2022, 144, 26, 11713–11728). This work presents an algorithm and data structure that extends the process of assembly modeling to the automated generation of structural information about metal–organic polyhedra, enabling automation of computational approaches to analyse trends in cavity and pore sizing. Distinct from string-based tools for purely organic cages, the workflow positions inorganic, organic, and hybrid chemical building units directly in 3-D and outputs geometries suitable for higher-level geometry optimization calculations in one step. The structural geometries obtained from this work are semantically integrated as part of The World Avatar, a dynamic knowledge ecosystem.


Access options

Associated Themes:
  Theme icon

*Corresponding author:
Telephone: +44 (0)1223 762784 (Dept) 769010 (CHU)
Address: Department of Chemical Engineering and Biotechnology
University of Cambridge
West Cambridge Site
Philippa Fawcett Drive
Cambridge CB3 0AS
United Kingdom
Website: Personal Homepage