Year |
Citation |
Score |
2023 |
Spronk SA, Glick ZL, Metcalf DP, Sherrill CD, Cheney DL. A quantum chemical interaction energy dataset for accurately modeling protein-ligand interactions. Scientific Data. 10: 619. PMID 37699937 DOI: 10.1038/s41597-023-02443-1 |
0.415 |
|
2023 |
Borca CH, Glick ZL, Metcalf DP, Burns LA, Sherrill CD. Benchmark coupled-cluster lattice energy of crystalline benzene and assessment of multi-level approximations in the many-body expansion. The Journal of Chemical Physics. 158. PMID 37318167 DOI: 10.1063/5.0159410 |
0.574 |
|
2023 |
Sargent CT, Metcalf DP, Glick ZL, Borca CH, Sherrill CD. Benchmarking two-body contributions to crystal lattice energies and a range-dependent assessment of approximate methods. The Journal of Chemical Physics. 158: 054112. PMID 36754814 DOI: 10.1063/5.0141872 |
0.588 |
|
2022 |
Metcalf DP, Smith A, Glick ZL, Sherrill CD. Range-dependence of two-body intermolecular interactions and their energy components in molecular crystals. The Journal of Chemical Physics. 157: 084503. PMID 36050028 DOI: 10.1063/5.0103644 |
0.647 |
|
2020 |
Metcalf DP, Jiang A, Spronk SA, Cheney DL, Sherrill CD. Electron-Passing Neural Networks for Atomic Charge Prediction in Systems with Arbitrary Molecular Charge. Journal of Chemical Information and Modeling. PMID 33326247 DOI: 10.1021/acs.jcim.0c01071 |
0.453 |
|
2020 |
Glick ZL, Metcalf DP, Koutsoukas A, Spronk SA, Cheney DL, Sherrill CD. AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials. The Journal of Chemical Physics. 153: 044112. PMID 32752707 DOI: 10.1063/5.0011521 |
0.607 |
|
2020 |
Metcalf DP, Koutsoukas A, Spronk SA, Claus BL, Loughney DA, Johnson SR, Cheney DL, Sherrill CD. Approaches for machine learning intermolecular interaction energies and application to energy components from symmetry adapted perturbation theory. The Journal of Chemical Physics. 152: 074103. PMID 32087645 DOI: 10.1063/1.5142636 |
0.624 |
|
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