Dynamic Metal-Ligand Coordination Modes with Ensemble Learning | LeMaterial Reading Group скачать в хорошем качестве

Dynamic Metal-Ligand Coordination Modes with Ensemble Learning | LeMaterial Reading Group

Paper Link: https://pubs.acs.org/doi/10.1021/jacs... Despite their significance in catalysis, medicine, and sustainability, transition metal complexes are challenging to model due to complicated electronic structures, limited experimental data, and a vast chemical space. This talk discusses recent advances in accurately predicting the structural properties of transition metal complexes with deep learning, facilitating the systematic exploration of chemical space. We conclude by demonstrating the integration of these models with generative AI for exploring novel organometallic chemistries and reactions. Jacob is a PhD candidate in Chemical Engineering and Computational Science in the Kulik Group at MIT. His research focuses on combining machine learning with quantum chemistry for the modeling and discovery of novel, functional transition metal complexes. LeMaterial Reading Group is a recurring gathering where we discuss recent papers at the intersection of AI, chemistry and materials science.