Date: 8th, Feb.
Time: from 17:00 (JST) / 9:00 (CET)
Title: “Machine Learning Organometallic Chemistry”
Presenter: Professor David Balcells, Hylleraas Centre for Quantum Molecular Sciences, Norway
Time: from 17:00 (JST) / 9:00 (CET)
Title: “Machine Learning Organometallic Chemistry”
Presenter: Professor David Balcells, Hylleraas Centre for Quantum Molecular Sciences, Norway
Abstract: Compared to organic chemistry, the application of machine learning to organometallics is challenged by the higher complexity of chemical bonds involving d orbitals. In this talk I will present the efforts of my group in advancing the following three topics:
1) The computation of large quantum datasets for transition metal complexes (J. Chem. Inf. Model., 2020, p. 6135)
2) The automated generation of structural guesses for the optimization of transition states in metal-catalyzed reactions (Top. Catal., 2021, DOI:10.1007/s11244-021-01506-0)
3) The use of different machine learning models to predict the reactivity of organometallic compounds in the fundamental steps found in catalysis (Chem. Sci., 2020, p.4584).
2) The automated generation of structural guesses for the optimization of transition states in metal-catalyzed reactions (Top. Catal., 2021, DOI:10.1007/s11244-021-01506-0)
3) The use of different machine learning models to predict the reactivity of organometallic compounds in the fundamental steps found in catalysis (Chem. Sci., 2020, p.4584).