scholarly journals Predictions for water clusters from a first-principles two- and three-body force field

2014 ◽  
Vol 140 (19) ◽  
pp. 194101 ◽  
Author(s):  
Urszula Góra ◽  
Wojciech Cencek ◽  
Rafał Podeszwa ◽  
Ad van der Avoird ◽  
Krzysztof Szalewicz
Keyword(s):  
Force Field ◽  
First Principles ◽  
Body Force ◽  
Water Clusters ◽  
Three Body

Three body force model for lattice dynamics of copper

1986 ◽  
Vol 57 (8) ◽  
pp. 559-562 ◽  
Author(s):  
H. Nait-Laziz ◽  
K.K. Chopra
Keyword(s):  
Lattice Dynamics ◽  
Body Force ◽  
Force Model ◽  
Three Body

scholarly journals Hot nuclear matter equation of state with a three-body force

2004 ◽  
Vol 69 (6) ◽  
Author(s):  
W. Zuo ◽  
Z. H. Li ◽  
A. Li ◽  
G. C. Lu
Keyword(s):  
Equation Of State ◽  
Nuclear Matter ◽  
Body Force ◽  
Three Body

scholarly journals Effect of Two-Pion-Exchange Three-Body Force in 3H and 4He

1974 ◽  
Vol 51 (6) ◽  
pp. 1979-1980 ◽  
Author(s):  
M. Sato ◽  
H. Tanaka
Keyword(s):  
Body Force ◽  
Pion Exchange ◽  
Three Body

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.

Rho-meson exchange three-body force effects

1992 ◽  
Vol 68 (24) ◽  
pp. 3503-3506 ◽  
Author(s):  
T. Sasakawa ◽  
S. Ishikawa ◽  
Y. Wu ◽  
T-Y. Saito
Keyword(s):  
Body Force ◽  
Meson Exchange ◽  
Rho Meson ◽  
Three Body
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