Manifold Diffusion for Structure Generation of Transition Metal Complexes
Transition metal complexes are central to catalysis, drug design, and materials science, with relevant properties strongly sensitive to their three-dimensional geometry. However, the electronic diversity and unconventional bonding environments of transition metal complexes pose a major challenge for accurate structure generation. In this work, we introduce TMCgen, a manifold diffusion machine learning model that efficiently and accurately generates geometries of transition metal complexes. By formulating the diffusion process over the metal-ligand coordination angles, combined with torsional and rotational diffusion of the ligands, TMCgen focuses on the key geometric degrees of freedom of...
| Authors | Luca Schaufelberger, Kjell Jorner |
|---|---|
| Primary category | cond-mat.mtrl-sci |
| Published | 30 May 2026 |
| Last updated at source | 30 May 2026 |
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