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Cover Image, Volume 36, Issue 32
Publication year - 2015
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Reports
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.24258
Subject(s) - cover (algebra) , maxima and minima , computer science , force field (fiction) , physics , chemistry , mathematics , artificial intelligence , mechanical engineering , engineering , mathematical analysis
Accurate next‐generation force fields must includemultipolar electrostatics. Quantum Chemical Topology (QCT) provides the required atomic multipolemoments,which are highly transferable. On page 2361 (DOI: 10.1002/jcc.24215 ), Salvatore Cardamone and Paul Popelier treat polarization effects, including charge transfer and high‐rank multipolar effects, using the machine learningmethod Kriging. After training, Kriging is able to predict the conformational dependence of all atomic multipolemoments. Energetic minima are used as “seeds” about which the vibrational modes ofmotion are used for the fine sampling of physically relevant conformational space. This proof‐of‐concept opens a new avenue to a next‐generation carbohydrate force field.