Steven Maley

My primary research interest is the computational design of earth abundant transition-metal catalysts. Specifically, I am interested in iron catalysts for cross-coupling reactions, CO2 hydrogenation, and photoredox reactions. I develop machine learning models to reveal reactivity principles and aid in the design of new catalysts.

Students interested in performing research in computational chemistry are encouraged to contact me.

Maley, S.M.; Kwon, D.-H.; Rollins, N.; Stanley, J.C.; Sydora, O.L.; Bischof, S.M.*; Ess, D.H.* “Quantum Mechanical Transition-State Model and Machine Learning Features Provide Selective Cr Olefin Oligomerization Catalyst Design” Chemical Science, 2020, 11, 9665-9674, 10.1039/D0SC03552A

Kwon, D.-H.; Maley, S.M.; Stanley, J.C.; Sydora, O.L.; Bischof, S.M.*; Ess, D.H.* “Why Less Coordination Provides Higher Reactivity Chromium Phosphinoamidine Ethylene Trimerization Catalysts” ACS Catalysis, 2020, 10, 17, 9674-9683, 10.1021/acscatal.0c02595

Maley, S.M.; Steagall, R.J.; Yang, Q.; Lief, G.R.; Buck, R.M; Sydora, O.L.; Bischof, S.M*.; Ess, D.H*. “Modulating Polyethylene Co-monomer Selectivity by Non-Covalent Dispersion Interactions in Zirconocene Catalyst Design” Organometallics, 2022, 41, 5, 581-593 10.1021/acs.organomet.1c00670

Maley, S.M.; Melville, J.; Yu, S.; Hargis, C.; Teynor, M.S.; Ess, D.H.* “Machine Learning Analysis Reveals Non-Intrinsic Reaction Coordinate Dynamical Motion for Cyclopropyl Radical Ring Opening” Phys. Chem. Chem. Phys., 2021, 23 12309-12320, 10.1039/D1CP00612F

Rollins, N.; Pugh, S.L.; Maley, S.M.; Grant, B.O.; Hamilton, R.S.; Teynor, M.S.; Carlsen, R.; Jenkins, J.R.; Ess, D.H.* “Machine Learning Analysis of Direct Dynamics Trajectory Outcomes for Thermal Deazetization of 2,3-Diazabicyclo[2.2.1]hept-2-ene” J. Phys. Chem. A, 2020, 124,23,4813-4826, 10.1021/acs.jpca.9b10410