High-Dimensional Atomistic Neural Network Potentials for Molecule-Surface Interactions: HCl Scattering from Au(111)

Journal of Physical Chemistry Letters

Volumn 8, Issue 3, 2017, Pages 666-672

  Kolb, Brian ^a,b   Luo, Xuan ^c   Zhou, Xueyao ^c   Jiang, Bin ^c   Guo, Hua ^a  

^a UNIVERSITY OF NEW MEXICO   (United States)

^b Massachusetts Institute of Technology   (United States)

^c UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CALCULATIONS; COMPUTATION THEORY; DEGREES OF FREEDOM (MECHANICS); DENSITY FUNCTIONAL THEORY; ENERGY TRANSFER; LEARNING SYSTEMS; MOLECULAR DYNAMICS; MOLECULES; POTENTIAL ENERGY; QUANTUM CHEMISTRY;

AB INITIO MOLECULAR DYNAMICS SIMULATION; CLASSICAL TRAJECTORIES; COMPUTATIONAL BOTTLENECKS; FIRST PRINCIPLES; HIGH-DIMENSIONAL; MACHINE LEARNING APPROACHES; MOLECULE SURFACE; SURFACE ATOMS;

SURFACE SCATTERING;

EID: 85011373245     PISSN: None     EISSN: 19487185     Source Type: Journal    
DOI: 10.1021/acs.jpclett.6b02994     Document Type: Article

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