Hybrid Computational Strategy for Predicting Complex Ligand–Metal Architectures

Galymzhan Moldagulov, Kisung Lee, Bartosz Andrzej Grzybowski

Submission Type: I want my submission to be considered for both oral and poster presentation.

Keywords: cheminformatics, machine learning, neural networks, organometallics

TL;DR: Researchers developed a hybrid ML and X-Ray structure knowledge-based strategy designed to accurately predict metal–ligand coordination modalities to streamline the rational design of transition metal complexes and catalysts.

Confirmation Of Submission Requirements: I submit a previously published paper. It was published in an archival peer–reviewed venue on or after September 1st 2025, I specify the DOI in the field below, and I submit the camera-ready version of the paper.

DOI: https://doi.org/10.1002/anie.202524655

Submission Number: 331