Energy-conserving molecular dynamics is not energy conserving-Reference-Cited by-同舟云学术

Energy-conserving molecular dynamics is not energy conserving

Published:2023 Issue:35 Volume:25 Page:23467-23476
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Zhang Lina¹^ORCID,Hou Yi-Fan¹^ORCID,Ge Fuchun¹^ORCID,Dral Pavlo O.¹^ORCID

Affiliation:

1. State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen, Fujian 361005, China

Abstract

Molecular dynamics is often simulation-energy conserving but the quality of calculations is still unsatisfactory. It is more conducive to focus on evaluating and improving the theoretical best estimate of total-energy time evolution.

Funder

National Outstanding Youth Foundation of China

Young Scientists Fund

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2023/CP/D3CP03515H

Reference57 articles.

1. R. P.Feynman , R. B.Leighton and M.Sands , The Feynman lectures on physics: The new millennium edition: mainly mechanics, radiation, and heat , Basic books , 2011 , vol. 1

2. Quantum molecular dynamics: propagating wavepackets and density operators using the multiconfiguration time-dependent Hartree method

3. F.Santoro , Quantum and Semiclassical Dynamics , in Reference Module in Chemistry, Molecular Sciences and Chemical Engineering , Elsevier , 2015

4. Recent Advances and Perspectives on Nonadiabatic Mixed Quantum–Classical Dynamics

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Physics-Informed Active Learning for Accelerating Quantum Chemical Simulations;Journal of Chemical Theory and Computation;2024-09-12

2. MLatom Software Ecosystem for Surface Hopping Dynamics in Python with Quantum Mechanical and Machine Learning Methods;Journal of Chemical Theory and Computation;2024-06-05

3. Tell Machine Learning Potentials What They Are Needed For: Simulation-Oriented Training Exemplified for Glycine;The Journal of Physical Chemistry Letters;2024-04-16

4. MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows;Journal of Chemical Theory and Computation;2024-01-25

5. AI in computational chemistry through the lens of a decade-long journey;Chemical Communications;2024