Development of a machine learning potential for graphene

Physical Review B

Volumn 97, Issue 5, 2018, Pages

  Rowe, Patrick ^a   Csányi, Gábor ^b   Alfè, Dario ^a   Michaelides, Angelos ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CALCULATIONS; COMPUTATION THEORY; DENSITY FUNCTIONAL THEORY; DISPERSIONS; ELECTRONIC STRUCTURE; GRAPHENE; MOLECULAR DYNAMICS; PHONONS; POTENTIAL ENERGY; QUANTUM CHEMISTRY; THERMAL EXPANSION;

AB INITIO MOLECULAR DYNAMICS SIMULATION; BOND-ORDER POTENTIAL; EMPIRICAL POTENTIALS; GAUSSIAN APPROXIMATIONS; INTERATOMIC POTENTIAL; MACHINE LEARNING MODELS; MOLECULAR DYNAMICS SIMULATIONS; PHONON DISPERSION CURVES;

MACHINE LEARNING;

EID: 85042188168     PISSN: 24699950     EISSN: 24699969     Source Type: Journal    
DOI: 10.1103/PhysRevB.97.054303     Document Type: Article

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