Andrew Zahrt

Chemistry University of Illinois, Urbana-Champaign, Urbana-Champaign, IL 
 Massachusetts Institute of Technology, Cambridge, MA, United States 
"Andrew Zahrt"
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Schnitzer T, Schnurr M, Zahrt AF, et al. (2024) Machine Learning to Develop Peptide Catalysts-Successes, Limitations, and Opportunities. Acs Central Science. 10: 367-373
Delaney CP, Zahrt AF, Kassel VM, et al. (2024) Effects of Ring Size and Steric Encumbrance on Boron-to-Palladium Transmetalation from Arylboronic Esters. The Journal of Organic Chemistry
Rinehart NI, Saunthwal RK, Wellauer J, et al. (2023) A machine-learning tool to predict substrate-adaptive conditions for Pd-catalyzed C-N couplings. Science (New York, N.Y.). 381: 965-972
Zahrt AF, Mo Y, Nandiwale KY, et al. (2022) Machine-Learning-Guided Discovery of Electrochemical Reactions. Journal of the American Chemical Society
Rinehart NI, Zahrt AF, Denmark SE. (2021) Leveraging Machine Learning for Enantioselective Catalysis: From Dream to Reality. Chimia. 75: 592-597
Rinehart NI, Zahrt AF, Henle JJ, et al. (2021) Dreams, False Starts, Dead Ends, and Redemption: A Chronicle of the Evolution of a Chemoinformatic Workflow for the Optimization of Enantioselective Catalysts. Accounts of Chemical Research
Zahrt AF, Henle JJ, Denmark SE. (2020) Cautionary Guidelines for Machine Learning Studies with Combinatorial Datasets. Acs Combinatorial Science
Henle JJ, Zahrt AF, Rose BT, et al. (2020) Development of a Computer-Guided Workflow for Catalyst Optimization. Descriptor Validation, Subset Selection, and Training Set Analysis. Journal of the American Chemical Society
Zahrt AF, Denmark SE. (2019) Evaluating continuous chirality measure as a 3D descriptor in chemoinformatics applied to asymmetric catalysis. Tetrahedron Letters. 75: 1841-1851
Zahrt AF, Athavale SV, Denmark SE. (2019) Quantitative Structure-Selectivity Relationships in Enantioselective Catalysis: Past, Present, and Future. Chemical Reviews
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