Theoretical Studies on Triplet-state Driven Dissociation of Formaldehyde by Quasi-classical Molecular Dynamics Simulation on Machine-Learning Potential Energy Surface

2021 ◽  
Author(s):  
Shichen Lin ◽  
Daoling Peng ◽  
Weitao Yang ◽  
Feng Long Gu ◽  
Zhenggang Lan
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Triplet State ◽  
Energy Surface ◽  
Dynamics Simulation ◽  
Theoretical Studies ◽  
Learning Potential

Potential energy surface and molecular dynamics simulation of gold(I) in liquid nitromethane

2009 ◽  
Vol 147 (1-2) ◽  
pp. 64-70 ◽  
Author(s):  
Natcha Injan ◽  
Tünde Megyes ◽  
Tamas Radnai ◽  
Imre Bako ◽  
Szabolcz Balint ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Dynamics Simulation

Stilbene isomerization dynamics on multidimensional potential energy surface. Molecular dynamics simulation

1993 ◽  
Vol 215 (4) ◽  
pp. 306-314 ◽  
Author(s):  
Valentin D. Vachev ◽  
John H. Frederick ◽  
Boris A. Grishanin ◽  
Victor N. Zadkov ◽  
Nikolai I. Koroteev
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Dynamics Simulation

scholarly journals Using a monomer potential energy surface to perform approximate path integral molecular dynamics simulation of ab initio water at near-zero added cost

2019 ◽  
Vol 21 (1) ◽  
pp. 409-417 ◽  
Author(s):  
Daniel C. Elton ◽  
Michelle Fritz ◽  
Marivi Fernández-Serra
Keyword(s):  
Molecular Dynamics ◽  
Density Functional Theory ◽  
Molecular Dynamics Simulation ◽  
Potential Energy ◽  
Path Integral ◽  
Liquid Water ◽  
Density Functional ◽  
Energy Surface ◽  
Dynamics Simulation ◽  
Functional Theory

We present a new approximate method for doing path integral molecular dynamics simulation with density functional theory and show the utility of the method for liquid water.

scholarly journals An On-the-fly Approach to Construct Generalized Energy-Based Fragmentation Machine Learning Force Fields of Complex Systems

2020 ◽  
Author(s):  
zheng cheng ◽  
Zhao Dongbo ◽  
Jing Ma ◽  
Wei Li ◽  
Shuhua Li
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Active Learning ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Force Field ◽  
Ab Initio Calculation ◽  
Energy Surface ◽  
Speed Up ◽  
Ab Inito

The paper describes a modification to the generalized energy-based fragmentation (GEBF) method that uses a machine fitted potential energy surface for the subsytems instead of ab initio calculation, in order to speed up the calculations. An on-the-fly active learning is used to construct vaious kind of subsystems force field automatically. Our method can bpyss over 99% of the QM calculations during the ab inito molecular dynamics.

scholarly journals An On-the-fly Approach to Construct Generalized Energy-Based Fragmentation Machine Learning Force Fields of Complex Systems

2020 ◽  
Author(s):  
zheng cheng ◽  
Zhao Dongbo ◽  
Jing Ma ◽  
Wei Li ◽  
Shuhua Li
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Active Learning ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Force Field ◽  
Ab Initio Calculation ◽  
Energy Surface ◽  
Speed Up ◽  
Ab Inito

The paper describes a modification to the generalized energy-based fragmentation (GEBF) method that uses a machine fitted potential energy surface for the subsytems instead of ab initio calculation, in order to speed up the calculations. An on-the-fly active learning is used to construct vaious kind of subsystems force field automatically. Our method can bpyss over 99% of the QM calculations during the ab inito molecular dynamics.

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