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Interatomic-Potential-Free, Data-Driven Molecular Dynamics
被引:2
|作者:
Bulin, J.
[1
]
Hamaekers, J.
[1
]
Ariza, M. P.
[2
]
Ortiz, M.
[3
,4
]
机构:
[1] Fraunhofer Inst Algorithms & Sci Comp, Schloss Birlinghoven, D-53757 St Augustin, Germany
[2] Univ Seville, Escuela Tecn Super Ingn, Seville 41092, Spain
[3] Univ Bonn, Hausdorff Ctr Math, Endenicher Allee 60, D-53115 Bonn, Germany
[4] CALTECH, Div Engn & Appl Sci, Pasadena, CA 91125 USA
关键词:
Data-Driven computing;
Molecular dynamics;
Optimal control;
Game theory;
Wasserstein metric;
C-60;
APPROXIMATION;
FRAGMENTATION;
D O I:
10.1016/j.cma.2023.116224
中图分类号:
T [工业技术];
学科分类号:
08 ;
摘要:
We present a Data-Driven (DD) paradigm that enables molecular dynamics calculations to be performed directly from sampled force-field data such as obtained, e. g., from ab initio calculations, thereby eschewing the conventional step of modeling the data by empirical interatomic potentials entirely. The data required by the DD solvers consists of local atomic configurations and corresponding atomic forces and is, therefore, fundamental, i. e., it is not beholden to any particular model. The resulting DD solvers, including a fully explicit DD-Verlet algorithm, are provably convergent and exhibit robust convergence with respect to the data in selected test cases. We present an example of application to C60 buckminsterfullerenes that showcases the feasibility, range and scope of the DD molecular dynamics paradigm.& COPY; 2023 Elsevier B.V. All rights reserved.
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页数:23
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