• B.S. Chemical Engineering, Michigan State University, 2018
• Ph.D. Chemistry, Georgia Tech, 2022

     Building Blocks of Neural Network Intermolecular Interaction Potentials

     SETCA Poster Award, 2019

• Machine Learning in Chemistry
• Molecular crystals

``Benchmarking Two-Body Contributions to Crystal Lattice Energies and a Range-Dependent Assessment of Approximate Methods,'' C. T. Sargent, D. P. Metcalf, Z. L. Glick, C. H. Borca, and C. D. Sherrill, J. Chem. Phys. 158, 054112 (2023) (doi: 10.1063/5.0141872)

``Range-Dependence of Two-Body Intermolecular Interactions and Their Energy Components in Molecular Crystals,'' D. P. Metcalf, A. Smith, Z. L. Glick, and C. D. Sherrill, J. Chem. Phys. 157, 084503 (2022) (doi: 10.1063/5.0103644)

``Electron-Passing Neural Networks for Atomic Charge Prediction in Systems with Arbitrary Molecular Charge,'' D. P. Metcalf, A. Jiang, S. A. Spronk, D. L. Cheney, and C. D. Sherrill, J. Chem Inf. Model. 61, 115 (2021) (doi: 10.1021/acs.jcim.0c01071)

``AP-Net: An Atomic-Pairwise Neural Network for Smooth and Transferable Interaction Potentials,'' Z. L. Glick, D. P. Metcalf, A. Koutsoukas, S. A. Spronk, D. L. Cheney, and C. D. Sherrill, J. Chem. Phys. 153, 044112 (2020) (doi: 10.1063/5.0011521)

``Approaches for Machine Learning Intermolecular Interaction Energies and Application to Energy Components From Symmetry Adapted Perturbation Theory,'' D. P. Metcalf, A. Koutsoukas, S. A. Spronk, B. L. Claus, D. A. Loughney, S. R. Johnson, D. L. Cheney, and C. D. Sherrill, J. Chem. Phys. 152, 074103 (2020) (doi: 10.1063/1.5142636)