scholarly journals Bayesian active learning of interatomic force field for molecular dynamics simulation of Pt/Ag(111)

2021 ◽  
Author(s):  
Kai Xu ◽  
Lei Yan ◽  
Bingran You
Keyword(s):  
Molecular Dynamics ◽  
Active Learning ◽  
Force Field ◽  
Density Functional ◽  
Process Model ◽  
Large Scale ◽  
Computational Cost ◽  
Dynamics Simulation ◽  
Potential Energy Landscape ◽  
Three Body

Force field is a central requirement in molecular dynamics (MD) simulation for accurate description of the potential energy landscape and the time evolution of individual atomic motions. Most energy models are limited by a fundamental tradeoff between accuracy and speed. Although ab initio MD based on density functional theory (DFT) has high accuracy, its high computational cost prevents its use for large-scale and long-timescale simulations. Here, we use Bayesian active learning to construct a Gaussian process model of interatomic forces to describe Pt deposited on Ag(111). An accurate model is obtained within one day of wall time after selecting only 126 atomic environments based on two- and three-body interactions, providing mean absolute errors of 52 and 142 meV/Å for Ag and Pt, respectively. Our work highlights automated and minimalistic training of machine-learning force fields with high fidelity to DFT, which would enable large-scale and long-timescale simulations of alloy surfaces at first-principles accuracy.

Bayesian active learning of interatomic force field for molecular dynamics simulation of Pt/Ag(111)

2021 ◽  
Author(s):  
Kai Xu ◽  
Lei Yan ◽  
Bingran You
Keyword(s):  
Molecular Dynamics ◽  
Active Learning ◽  
Force Field ◽  
Density Functional ◽  
Process Model ◽  
Large Scale ◽  
Computational Cost ◽  
Dynamics Simulation ◽  
Potential Energy Landscape ◽  
Three Body

Force field is a central requirement in molecular dynamics (MD) simulation for accurate description of the potential energy landscape and the time evolution of individual atomic motions. Most energy models are limited by a fundamental tradeoff between accuracy and speed. Although ab initio MD based on density functional theory (DFT) has high accuracy, its high computational cost prevents its use for large-scale and long-timescale simulations. Here, we use Bayesian active learning to construct a Gaussian process model of interatomic forces to describe Pt deposited on Ag(111). An accurate model is obtained within one day of wall time after selecting only 126 atomic environments based on two- and three-body interactions, providing mean absolute errors of 52 and 142 meV/Å for Ag and Pt, respectively. Our work highlights automated and minimalistic training of machine-learning force fields with high fidelity to DFT, which would enable large-scale and long-timescale simulations of alloy surfaces at first-principles accuracy.

Nano-Tribological Analysis by Molecular Dynamics Simulation—A Review

2006 ◽  
Vol 3 (2) ◽  
pp. 167-188 ◽  
Author(s):  
L. C. Zhang ◽  
K. Mylvaganam
Keyword(s):  
Molecular Dynamics ◽  
Large Scale ◽  
Surface Force ◽  
Atomic Scale ◽  
Dynamics Simulation ◽  
Asperity Contact ◽  
Dynamics Modeling ◽  
Body Contact ◽  
Cutting Regimes ◽  
Three Body

The advent of super computers for large scale atomic simulations and the invention of proximal testing devices such as atomic force microscope, friction force microscope, surface force apparatus, nanoScratcher etc., have led to the development of micro- and nano-tribology. This paper reviews some fundamental concepts and steps involved in molecular dynamics modeling of nanotribology together with some significant aspects such as the mechanisms of wear and friction, the scale effect of asperity contact size on friction, and the deformation induced by two-body and three-body contact sliding on the atomic scale with a focus on the authors' work on copper and silicon. Studies on diamond-copper sliding reveal that there exist four distinct regimes of deformation, and that no-wear deformation can be achieved by using a lower sliding speed, a smaller tip radius and a better lubrication. The variation of the frictional force is a function of contact area in all regimes except that in the cutting regime where the conventional friction law still holds. Investigations into the diamond-silicon sliding show that the amorphous phase transformation is the main deformation in silicon. In a two-body contact sliding, the deformation of silicon falls into no-wear, adhering, ploughing, and cutting regimes while in a three-body sliding it falls into no-wear, condensing, adhering, ploughing and no-damage wear regimes.

scholarly journals Molecular dynamics simulation of pull-out Halloysite nanotube from polyurethane matrix

2021 ◽  
Vol 13 (9) ◽  
pp. 168781402110446
Author(s):  
Mohammadreza Heidari Pebdani ◽  
Ronald E. Miller
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Density Functional ◽  
Md Simulation ◽  
Halloysite Nanotubes ◽  
Dynamics Simulation ◽  
Experimental Sample ◽  
Functional Theory ◽  
Pull Out ◽  
Good Agreement

Molecular dynamics (MD) simulation has been applied to study of pull-out of Halloysite nanotubes (HNTs) from a polyurethane (PU) matrix. First, the Machine learning (ML) particle swarm optimization (PSO) method was used to obtain force field parameters for MD from data of density functional theory (DFT) calculations. The current study shows the possibility of using a PSO technique to modify the force field with DFT data with less than 5 kcal/mol discrepancy. Second, we considered the influence of atomic interface on pulling out of HNT from PU. Energy variation has been proposed as the cohesion strength between matrix and nanoparticle. In addition, the best Lennard Jones parameters in the MD simulation make good agreement with an experimental sample stress-strain response.

Combustion Driven by Fragment-based Ab Initio Molecular Dynamics Simulation

2019 ◽  
Author(s):  
Liqun Cao ◽  
Jinzhe Zeng ◽  
Mingyuan Xu ◽  
Chih-Hao Chin ◽  
Tong Zhu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Large Scale ◽  
Methane Combustion ◽  
Combustion Method ◽  
Dynamics Simulation ◽  
Ab Initio Molecular Dynamics ◽  
Computational Time ◽  
Combustion Mechanism ◽  
Daily Lives

Combustion is a kind of important reaction that affects people's daily lives and the development of aerospace. Exploring the reaction mechanism contributes to the understanding of combustion and the more efficient use of fuels. Ab initio quantum mechanical (QM) calculation is precise but limited by its computational time for large-scale systems. In order to carry out reactive molecular dynamics (MD) simulation for combustion accurately and quickly, we develop the MFCC-combustion method in this study, which calculates the interaction between atoms using QM method at the level of MN15/6-31G(d). Each molecule in systems is treated as a fragment, and when the distance between any two atoms in different molecules is greater than 3.5 Å, a new fragment involved two molecules is produced in order to consider the two-body interaction. The deviations of MFCC-combustion from full system calculations are within a few kcal/mol, and the result clearly shows that the calculated energies of the different systems using MFCC-combustion are close to converging after the distance thresholds are larger than 3.5 Å for the two-body QM interactions. The methane combustion was studied with the MFCC-combustion method to explore the combustion mechanism of the methane-oxygen system.

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