المؤلفون: Marco Bertani, Thibault Charpentier, Francesco Faglioni, Alfonso Pedone

مصطلحات موضوعية: Biophysics, Biotechnology, Computational Biology, Biological Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Physical Sciences not elsewhere classified, Information Systems not elsewhere classified, transferable machine learning, sodium silicate glasses, neural network algorithm, neighboring atoms using, multicomponent oxide glasses, large data set, empirical potentials available, classical molecular dynamics, bond angle distribution, total distribution functions, full compositional range, atomic forces computed, potential energy surface, molecular dynamics simulation, 2 , wide range, total energies, atomic distances, vibrational density, several temperatures, glass formability, future training, elements allowing

Relation: https://figshare.com/articles/journal_contribution/Accurate_and_Transferable_Machine_Learning_Potential_for_Molecular_Dynamics_Simulation_of_Sodium_Silicate_Glasses/24994486

الاتاحة: https://doi.org/10.1021/acs.jctc.3c01115.s001
https://figshare.com/articles/journal_contribution/Accurate_and_Transferable_Machine_Learning_Potential_for_Molecular_Dynamics_Simulation_of_Sodium_Silicate_Glasses/24994486