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NANDI Apurba

University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS)

ORCID
0000-0002-6191-5584
Main Referenced Co-authors
Bowman, Joel M (3)
Pandey, Priyanka (3)
Conte, Riccardo (2)
Houston, Paul L (2)
Qu, Chen (2)
Main Referenced Keywords
Computer Science Applications (2); Alkanes (1); Atomic decomposition (1); Biochemistry, Genetics and Molecular Biology (all) (1); Body representations (1);
Main Referenced Disciplines
Chemistry (5)

Publications (total 5)

The most downloaded
62 downloads
Yu, Q., Ma, R., Qu, C., Conte, R., NANDI, A., Pandey, P., Houston, P. L., Zhang, D. H., & Bowman, J. M. (2025). Extending atomic decomposition and many-body representation with a chemistry-motivated approach to machine learning potentials. Nature computational science. doi:10.1038/s43588-025-00790-0 https://hdl.handle.net/10993/64782

The most cited

5 citations (WOS)

NANDI, A., Pandey, P., Houston, P. L., Qu, C., Yu, Q., Conte, R., TKATCHENKO, A., & Bowman, J. M. (22 October 2024). Δ-Machine Learning to Elevate DFT-Based Potentials and a Force Field to the CCSD(T) Level Illustrated for Ethanol. Journal of Chemical Theory and Computation, 20 (20), 8807 - 8819. doi:10.1021/acs.jctc.4c00977 https://hdl.handle.net/10993/65038

Scientific outputs

Articles in scientific journals with peer reviewing verified by ORBi or included in HEC journal guide

Korol, R., Turner, A. C., NANDI, A., Bowman, J. M., Goddard, W. A., & Stolper, D. A. (May 2025). Stable isotope equilibria in the dihydrogen-water-methane-ethane-propane system. Part 1: Path-integral calculations with CCSD(T) quality potentials. Geochimica et Cosmochimica Acta, 396, 71 - 90. doi:10.1016/j.gca.2025.02.028
Peer Reviewed verified by ORBi

Yu, Q., Ma, R., Qu, C., Conte, R., NANDI, A., Pandey, P., Houston, P. L., Zhang, D. H., & Bowman, J. M. (2025). Extending atomic decomposition and many-body representation with a chemistry-motivated approach to machine learning potentials. Nature computational science. doi:10.1038/s43588-025-00790-0
Peer reviewed

Jäger, S., Khatri, J., Meyer, P., Henkel, S., Schwaab, G., NANDI, A., Pandey, P., Barlow, K. R., Perkins, M. A., Tschumper, G. S., Bowman, J. M., van der Avoird, A., & Havenith, M. (05 November 2024). On the nature of hydrogen bonding in the H2S dimer. Nature Communications, 15 (1), 9540. doi:10.1038/s41467-024-53444-6
Peer Reviewed verified by ORBi

NANDI, A., Pandey, P., Houston, P. L., Qu, C., Yu, Q., Conte, R., TKATCHENKO, A., & Bowman, J. M. (22 October 2024). Δ-Machine Learning to Elevate DFT-Based Potentials and a Force Field to the CCSD(T) Level Illustrated for Ethanol. Journal of Chemical Theory and Computation, 20 (20), 8807 - 8819. doi:10.1021/acs.jctc.4c00977
Peer Reviewed verified by ORBi

NANDI, A., & Nagy, P. R. (June 2024). Combining state-of-the-art quantum chemistry and machine learning make gold standard potential energy surfaces accessible for medium-sized molecules. Artificial Intelligence Chemistry, 2 (1), 100036. doi:10.1016/j.aichem.2023.100036
Peer reviewed

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