The Paton Research Group

Predictive Computational Chemistry

Research in the Paton group is focussed on the development and application of computational tools to accelerate chemical discovery. Quantum chemistry, open source software and statistical modeling tools are used to explore organic reactivity and selectivity aided by extensive collaborations with experimentalists.

paton lab logo


Data Driven Chemistry FI
Computer aided catalyst design
reaction mechanism

Recent Publications

Late-Stage “Benzenoid-to-Troponoid” Skeletal Modification of the Cephalotanes: Total Synthesis of Harringtonolide and Computational Analysis.

Wiesler, S.; Sennari, G.;  Popescu, M. P.; Gardner, K. E.; Aida, K., Paton, R. S.; Sarpong. R. Nat. Commun. 2024, 15, 4125

A Deconstruction-Reconstruction Strategy for Pyrimidine Diversification.

Uhlenbruck, B. J. H.; Josephitis, C. M.; Lescure, L.; Paton, R. S.; McNally, A. Nature 2024, DOI: 10.1038/s41586-024-07474-1

Radical Chlorination of Non-Resonant Heterobenzylic C‒H Bonds and High-Throughput Diversification of Heterocycles.

Golden, D. L.; Flynn, K. M.; Aikonen, S.; Kalyani, D.; Krska, S. W.; Paton, R. S.; Stahl, S. S. Chem. 2024, DOI: 10.1016/j.chempr.2024.04.001.

Predicting Lewis Acidity: Machine Learning the Fluoride Ion Affinity of p-Block Atom-based Molecules.

Sigmund, L. M.; Sowndarya, S. S. V.; Albers, A.; Erdmann, P.; Paton, R. S.; Greb, L. Angew. Chem. Int. Ed. 2024, DOI: 10.1002/anie.202401084

Mechanistic Investigation Reveals a Perylene-like Closed Shell Super-Photoreductant.

Sau, A.; Pompetti, N. F.; Green, A.; Popescu, M. V.; Paton, R. S.; Miyake, G. M.; Damrauer, N. H. ACS Catal. 2024, 14, 2252–2263

Bottom-Up Atomistic Descriptions of Top-Down Macroscopic Measurements: Computational Benchmarks for Hammett Electronic Parameters.

Luchini, G.; Paton, R. S. ACS Phys. Chem. Au2024, DOI: 10.1021/acsphyschemau.3c00045