Optimal construction of a fast and accurate polarizable water potential based on multipole moments trained by machine learning

C. M. Handley, Glenn Hawe, D. B. Kell, P. L. A. Popelier

Research output: Contribution to journal › Article

Original language	English
Pages (from-to)	6365-6376
Journal	Physical Chemistry Chemical Physics
Volume	11
Issue number	30
DOIs	https://doi.org/10.1039/b905748j
Publication status	Published - 5 Jun 2009

Cite this

@article{395bf10018364499a3734a06054a383d,

title = "Optimal construction of a fast and accurate polarizable water potential based on multipole moments trained by machine learning",

author = "Handley, {C. M.} and Glenn Hawe and Kell, {D. B.} and Popelier, {P. L. A.}",

year = "2009",

month = jun,

day = "5",

doi = "10.1039/b905748j",

language = "English",

volume = "11",

pages = "6365--6376",

journal = "Physical Chemistry Chemical Physics",

issn = "1463-9076",

publisher = "Royal Society of Chemistry",

number = "30",

}

TY - JOUR

T1 - Optimal construction of a fast and accurate polarizable water potential based on multipole moments trained by machine learning

AU - Handley, C. M.

AU - Hawe, Glenn

AU - Kell, D. B.

AU - Popelier, P. L. A.

PY - 2009/6/5

Y1 - 2009/6/5

U2 - 10.1039/b905748j

DO - 10.1039/b905748j

M3 - Article

VL - 11

SP - 6365

EP - 6376

JO - Physical Chemistry Chemical Physics

JF - Physical Chemistry Chemical Physics

SN - 1463-9076

IS - 30

ER -