Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7703650 | PMC |
http://dx.doi.org/10.1073/pnas.2017827117 | DOI Listing |
J Plankton Res
November 2024
[This corrects the article DOI: 10.1093/plankt/fbae031.].
View Article and Find Full Text PDFCell Regen
December 2024
Shanghai Key Laboratory of Regulatory Biology, Institute of Molecular Medicine, School of Life Sciences, East China Normal University, Shanghai, 200241, China.
Front Microbiol
October 2024
Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States.
[This corrects the article DOI: 10.3389/fmicb.2020.
View Article and Find Full Text PDFSpectrochim Acta A Mol Biomol Spectrosc
February 2025
Department of Chemistry, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia; Chemistry Department, Faculty of Science, Damietta University, New Damietta, Damietta, Egypt. Electronic address:
J Chem Phys
November 2024
Department of Physics, Gebze Institute of Technology, Gebze, Kocaeli 41400, Türkiye.
Machine-learning interatomic potential models based on graph neural network architectures have the potential to make atomistic materials modeling widely accessible due to their computational efficiency, scalability, and broad applicability. The training datasets for many such models are derived from density-functional theory calculations, typically using a semilocal exchange-correlation functional. As a result, long-range interactions such as London dispersion are often missing in these models.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!