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Apurba Nandi - Publications

Affiliations: 
Emory University, Atlanta, GA 
Area:
Theoretical Chemistry, Reaction Dynamics
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32 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2024 Ge F, Wang R, Qu C, Zheng P, Nandi A, Conte R, Houston PL, Bowman JM, Dral PO. Tell Machine Learning Potentials What They Are Needed For: Simulation-Oriented Training Exemplified for Glycine. The Journal of Physical Chemistry Letters. 4451-4460. PMID 38626460 DOI: 10.1021/acs.jpclett.4c00746  0.741
2024 Houston PL, Qu C, Yu Q, Pandey P, Conte R, Nandi A, Bowman JM. No Headache for PIPs: A PIP Potential for Aspirin Runs Much Faster and with Similar Precision Than Other Machine-Learned Potentials. Journal of Chemical Theory and Computation. PMID 38593438 DOI: 10.1021/acs.jctc.4c00054  0.739
2024 Houston PL, Qu C, Yu Q, Pandey P, Conte R, Nandi A, Bowman JM, Kukolich SG. Formic Acid-Ammonia Heterodimer: A New Δ-Machine Learning CCSD(T)-Level Potential Energy Surface Allows Investigation of the Double Proton Transfer. Journal of Chemical Theory and Computation. PMID 38382541 DOI: 10.1021/acs.jctc.3c01273  0.769
2024 Pandey P, Qu C, Nandi A, Yu Q, Houston PL, Conte R, Bowman JM. Ab Initio Potential Energy Surface for NaCl-H with Correct Long-Range Behavior. The Journal of Physical Chemistry. A. PMID 38271992 DOI: 10.1021/acs.jpca.3c07687  0.762
2024 Houston PL, Qu C, Yu Q, Pandey P, Conte R, Nandi A, Bowman JM. A New Method to Avoid Calculation of Negligible Hamiltonian Matrix Elements in CI Calculation. The Journal of Physical Chemistry. A. PMID 38180902 DOI: 10.1021/acs.jpca.3c06985  0.733
2023 Yu Q, Qu C, Houston PL, Nandi A, Pandey P, Conte R, Bowman JM. A Status Report on "Gold Standard" Machine-Learned Potentials for Water. The Journal of Physical Chemistry Letters. 8077-8087. PMID 37656898 DOI: 10.1021/acs.jpclett.3c01791  0.729
2023 Qu C, Houston PL, Yu Q, Conte R, Pandey P, Nandi A, Bowman JM. Machine learning classification can significantly reduce the cost of calculating the Hamiltonian matrix in CI calculations. The Journal of Chemical Physics. 159. PMID 37584439 DOI: 10.1063/5.0168590  0.728
2023 Qu C, Yu Q, Houston PL, Conte R, Nandi A, Bowman JM. Interfacing q-AQUA with a Polarizable Force Field: The Best of Both Worlds. Journal of Chemical Theory and Computation. PMID 37249502 DOI: 10.1021/acs.jctc.3c00334  0.708
2023 Nandi A, Laude G, Khire SS, Gurav ND, Qu C, Conte R, Yu Q, Li S, Houston PL, Gadre SR, Richardson JO, Evangelista FA, Bowman JM. Ring-Polymer Instanton Tunneling Splittings of Tropolone and Isotopomers using a Δ-Machine Learned CCSD(T) Potential: Theory and Experiment Shake Hands. Journal of the American Chemical Society. 145: 9655-9664. PMID 37078852 DOI: 10.1021/jacs.3c00769  0.797
2023 Houston PL, Qu C, Yu Q, Conte R, Nandi A, Li JK, Bowman JM. PESPIP: Software to fit complex molecular and many-body potential energy surfaces with permutationally invariant polynomials. The Journal of Chemical Physics. 158: 044109. PMID 36725524 DOI: 10.1063/5.0134442  0.73
2022 Bowman JM, Qu C, Conte R, Nandi A, Houston PL, Yu Q. Δ-Machine Learned Potential Energy Surfaces and Force Fields. Journal of Chemical Theory and Computation. PMID 36527383 DOI: 10.1021/acs.jctc.2c01034  0.782
2022 Conte R, Nandi A, Qu C, Yu Q, Houston PL, Bowman JM. Semiclassical and VSCF/VCI Calculations of the Vibrational Energies of - and -Ethanol Using a CCSD(T) Potential Energy Surface. The Journal of Physical Chemistry. A. 126: 7709-7718. PMID 36240438 DOI: 10.1021/acs.jpca.2c06322  0.762
2022 Houston PL, Nandi A, Bowman JM. A Machine Learning Approach for Rate Constants. III. Application to the Cl(P) + CH → CH + HCl Reaction. The Journal of Physical Chemistry. A. PMID 35960874 DOI: 10.1021/acs.jpca.2c04376  0.633
2022 Nandi A, Conte R, Qu C, Houston PL, Yu Q, Bowman JM. Quantum Calculations on a New CCSD(T) Machine-Learned Potential Energy Surface Reveal the Leaky Nature of Gas-Phase and Ethanol Conformers. Journal of Chemical Theory and Computation. PMID 35951990 DOI: 10.1021/acs.jctc.2c00760  0.786
2022 Bowman JM, Qu C, Conte R, Nandi A, Houston PL, Yu Q. The MD17 datasets from the perspective of datasets for gas-phase "small" molecule potentials. The Journal of Chemical Physics. 156: 240901. PMID 35778068 DOI: 10.1063/5.0089200  0.772
2022 Yu Q, Qu C, Houston PL, Conte R, Nandi A, Bowman JM. q-AQUA: A Many-Body CCSD(T) Water Potential, Including Four-Body Interactions, Demonstrates the Quantum Nature of Water from Clusters to the Liquid Phase. The Journal of Physical Chemistry Letters. 5068-5074. PMID 35652912 DOI: 10.1021/acs.jpclett.2c00966  0.765
2022 Khire SS, Gurav ND, Nandi A, Gadre SR. Enabling Rapid and Accurate Construction of CCSD(T)-Level Potential Energy Surface of Large Molecules Using Molecular Tailoring Approach. The Journal of Physical Chemistry. A. PMID 35170973 DOI: 10.1021/acs.jpca.2c00025  0.665
2022 Houston PL, Qu C, Nandi A, Conte R, Yu Q, Bowman JM. Permutationally invariant polynomial regression for energies and gradients, using reverse differentiation, achieves orders of magnitude speed-up with high precision compared to other machine learning methods. The Journal of Chemical Physics. 156: 044120. PMID 35105104 DOI: 10.1063/5.0080506  0.735
2021 Nandi A, Qu C, Houston PL, Conte R, Yu Q, Bowman JM. A CCSD(T)-Based 4-Body Potential for Water. The Journal of Physical Chemistry Letters. 12: 10318-10324. PMID 34662138 DOI: 10.1021/acs.jpclett.1c03152  0.768
2021 Qu C, Houston PL, Conte R, Nandi A, Bowman JM. MULTIMODE Calculations of Vibrational Spectroscopy and 1d Interconformer Tunneling Dynamics in Glycine Using a Full-Dimensional Potential Energy Surface. The Journal of Physical Chemistry. A. PMID 34110169 DOI: 10.1021/acs.jpca.1c03738  0.75
2021 Qu C, Houston PL, Conte R, Nandi A, Bowman JM. Breaking the Coupled Cluster Barrier for Machine-Learned Potentials of Large Molecules: The Case of 15-Atom Acetylacetone. The Journal of Physical Chemistry Letters. 4902-4909. PMID 34006096 DOI: 10.1021/acs.jpclett.1c01142  0.783
2021 Nandi A, Qu C, Houston PL, Conte R, Bowman JM. Δ-machine learning for potential energy surfaces: A PIP approach to bring a DFT-based PES to CCSD(T) level of theory. The Journal of Chemical Physics. 154: 051102. PMID 33557535 DOI: 10.1063/5.0038301  0.792
2021 Nandi A, Zhang P, Chen J, Guo H, Bowman JM. Quasiclassical simulations based on cluster models reveal vibration-facilitated roaming in the isomerization of CO adsorbed on NaCl. Nature Chemistry. PMID 33462381 DOI: 10.1038/s41557-020-00612-y  0.543
2020 Nandi A, Bowman JM, Houston PL. A Machine Learning Approach for Rate Constants II: Clustering, Training, and Predictions for the O(P)+HCl -> OH+Cl Reaction. The Journal of Physical Chemistry. A. PMID 32543849 DOI: 10.1021/Acs.Jpca.0C04348  0.647
2019 Nandi A, Qu C, Bowman JM. Full and fragmented permutationally invariant polynomial potential energy surfaces for trans and cis N-methyl acetamide and isomerization saddle points. The Journal of Chemical Physics. 151: 084306. PMID 31470729 DOI: 10.1063/1.5119348  0.614
2019 Houston PL, Nandi A, Bowman JM. A Machine Learning Approach for Prediction of Rate Constants. The Journal of Physical Chemistry Letters. PMID 31423788 DOI: 10.1021/Acs.Jpclett.9B01810  0.665
2019 Nandi A, Qu C, Bowman JM. Using Gradients in Permutationally Invariant Polynomial Potential fitting: A Demonstration for CH4 Using as Few as 100 Configurations. Journal of Chemical Theory and Computation. PMID 30896950 DOI: 10.1021/Acs.Jctc.9B00043  0.622
2019 Koch W, Bonfanti M, Eisenbrandt P, Nandi A, Fu B, Bowman J, Tannor D, Burghardt I. Two-layer Gaussian-based MCTDH study of the S1 ← S0 vibronic absorption spectrum of formaldehyde using multiplicative neural network potentials The Journal of Chemical Physics. 151: 064121. DOI: 10.1063/1.5113579  0.525
2018 Nandi A, Qu C, Bowman JM. Diffusion Monte Carlo Calculations of Zero-Point Energies of Methanol and Deuterated Methanol. Journal of Computational Chemistry. PMID 30284291 DOI: 10.1002/Jcc.25601  0.619
2017 Singh G, Nandi A, Gadre SR, Chiba T, Fujii A. A combined theoretical and experimental study of phenol-(acetylene)n (n ≤ 7) clusters. The Journal of Chemical Physics. 146: 154303. PMID 28433025 DOI: 10.1063/1.4979953  0.558
2016 Sahu N, Singh G, Nandi A, Gadre SR. Towards an Accurate and Inexpensive Estimation of CCSD(T)/CBS Binding Energies of Large Water Clusters. The Journal of Physical Chemistry. A. PMID 27351269 DOI: 10.1021/Acs.Jpca.6B04519  0.641
2016 Singh G, Nandi A, Gadre SR. Breaking the bottleneck: Use of molecular tailoring approach for the estimation of binding energies at MP2/CBS limit for large water clusters. The Journal of Chemical Physics. 144: 104102. PMID 26979676 DOI: 10.1063/1.4943115  0.615
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