Project Details
Projekt
Machine Learning for asymmetric and electrochemical 3d transition metal catalyzed C–H activations
Applicant
Professor Dr. Lutz Ackermann
Subject Area
Organic Molecular Chemistry - Synthesis and Characterisation
Term
since 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 497259673
Transition metal-catalyzed C–H activation has surfaced as a powerful strategy for molecular synthesis, with applications in drug discovery, late-stage diversification, and material sciences, among others. The development of challenging asymmetric 3d metal-catalyzed C–H activations continues misrepresented. Here, the multi-parameter reaction optimization represents a major drawback. During the last few years, data-driven strategies have emerged as an increasingly viable toolbox in molecular sciences. Within the SPP 2363, we seek to create and implement machine learning predictive models to propel the field of asymmetric 3d transition metal-catalyzed C–H activation, for the construction of C-center as well as the axial-chirality of biologically relevant compounds. In this regard, the use of a reliable and robust dataset is of extreme importance. Here, the use of High-Throughput Experimentation (HTE) will be implemented to assist in the rapid creation and expansion of an experimental database. Thereafter, state-of-the-art (SOTA) machine learning algorithms and GNN will be employed in the generation of predictive models for the accurate prediction of reactivity and selectivity of electrocatalytic 3d transition metal-catalyzed C–H activations. However, their success relies on the precise definition of three-dimensional descriptors between other and accurate molecular representations. Hence, within the SPP 2363 the synergetic relation between experimental chemistry and computer sciences will be explored for the benchmarking and development of accurate predictive models for the synthesis of medicinal relevant compounds through asymmetric catalysis. Such breakthroughs will contribute to establishing Germany in the vanguard of artificial intelligence applied in asymmetric catalysis on an international level worldwide.
DFG Programme
Priority Programmes
