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A data‐driven approach for reduction of molecular simulations
Author(s) -
Oguz Cihan,
Gallivan Martha A.
Publication year - 2005
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.1020
Subject(s) - statistical physics , molecular dynamics , reduction (mathematics) , amorphous solid , statistical mechanics , process (computing) , yield (engineering) , stochastic process , polymer , dynamics (music) , ranging , computer science , thermodynamics , materials science , chemistry , physics , mathematics , computational chemistry , telecommunications , geometry , organic chemistry , statistics , acoustics , composite material , operating system
Stochastic simulations based on non‐equilibrium statistical mechanics describe the interactions among many discrete atoms or molecules, and thus describe the dynamics of materials processing in applications ranging from inorganic crystalline films to amorphous polymer melts. In general, non‐equilibrium thermodynamics does not directly yield a closed, low‐dimensional dynamic equation, although such a model would be desirable to analyse the dynamics and to optimize and control the process. A practical approach is described here in which targeted simulations are combined with systematic tools to elucidate the dynamics. Copyright © 2005 John Wiley & Sons, Ltd.