Crossref journal-article
American Chemical Society (ACS)
Journal of Chemical Theory and Computation (316)
Bibliography

Sun, G., & Sautet, P. (2019). Toward Fast and Reliable Potential Energy Surfaces for Metallic Pt Clusters by Hierarchical Delta Neural Networks. Journal of Chemical Theory and Computation, 15(10), 5614–5627.

Authors 2
  1. Geng Sun (first)
  2. Philippe Sautet (additional)
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Dates
Type When
Created 6 years ago (Aug. 29, 2019, 4:22 p.m.)
Deposited 2 years, 4 months ago (April 16, 2023, 7:54 a.m.)
Indexed 1 month ago (Aug. 1, 2025, 11:58 p.m.)
Issued 6 years ago (Aug. 29, 2019)
Published 6 years ago (Aug. 29, 2019)
Published Online 6 years ago (Aug. 29, 2019)
Published Print 5 years, 10 months ago (Oct. 8, 2019)
Funders 2
  1. University of California, Los Angeles 10.13039/100007185

    Region: Americas

    gov (Universities (academic only))

    Labels3
    1. University of California-Los Angeles
    2. University of California Los Angeles
    3. UCLA
  2. Basic Energy Sciences 10.13039/100006151

    Region: Americas

    gov (National government)

    Labels6
    1. Office of Basic Energy Sciences
    2. DOE Office of Basic Energy Sciences
    3. US Department of Energy's Basic Energy Sciences
    4. DOE Basic Energy Sciences
    5. Department of Energy Basic Energy Sciences Program
    6. BES
    Awards1
    1. DE-SC0019152

@article{Sun_2019, title={Toward Fast and Reliable Potential Energy Surfaces for Metallic Pt Clusters by Hierarchical Delta Neural Networks}, volume={15}, ISSN={1549-9626}, url={http://dx.doi.org/10.1021/acs.jctc.9b00465}, DOI={10.1021/acs.jctc.9b00465}, number={10}, journal={Journal of Chemical Theory and Computation}, publisher={American Chemical Society (ACS)}, author={Sun, Geng and Sautet, Philippe}, year={2019}, month=aug, pages={5614–5627} }