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dc.contributor.authorHarmandaris, Vagelis
dc.contributor.authorKalligiannaki, Evangelia
dc.contributor.authorKatsoulakis, Markos
dc.contributor.authorPlechac, Petr
dc.date.accessioned2018-03-20T12:34:07Z
dc.date.available2018-03-20T12:34:07Z
dc.date.issued2017-10-03
dc.identifier.citationHarmandaris V, Kalligiannaki E, Katsoulakis M, Plechac P (2017) FROM ATOMISTIC TO SYSTEMATIC COARSE-GRAINED MODELS FOR MOLECULAR SYSTEMS. Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017) . Available: http://dx.doi.org/10.7712/120217.5378.17211.
dc.identifier.doi10.7712/120217.5378.17211
dc.identifier.urihttp://hdl.handle.net/10754/627365
dc.description.abstractThe development of systematic (rigorous) coarse-grained mesoscopic models for complex molecular systems is an intense research area. Here we first give an overview of methods for obtaining optimal parametrized coarse-grained models, starting from detailed atomistic representation for high dimensional molecular systems. Different methods are described based on (a) structural properties (inverse Boltzmann approaches), (b) forces (force matching), and (c) path-space information (relative entropy). Next, we present a detailed investigation concerning the application of these methods in systems under equilibrium and non-equilibrium conditions. Finally, we present results from the application of these methods to model molecular systems.
dc.publisherECCOMAS
dc.relation.urlhttps://www.eccomasproceedia.org/conferences/thematic-conferences/uncecomp-2017/5378
dc.rightsArchived with thanks to 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering
dc.subjectCoarse-graining
dc.subjectForce matching
dc.subjectPotential of mean force
dc.subjectRelative entropy
dc.titleFROM ATOMISTIC TO SYSTEMATIC COARSE-GRAINED MODELS FOR MOLECULAR SYSTEMS
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.identifier.journalProceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017)
dc.conference.date2017-06-15 to 2017-06-17
dc.conference.name2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2017
dc.conference.locationRhodes Island, GRC
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionInstitute of Applied and Computational Mathematics, Foundation for Research and Technology Hellas, IACM/FORTH, Heraklion, Crete, GR-70013, , Greece
dc.contributor.institutionDepartment of Mathematics and Applied Mathematics, University of Crete, Heraklion, Crete, GR-70013, , Greece
dc.contributor.institutionDepartment of Mathematics and Statistics, University of Massachusetts at Amherst, Amherst, MA, 01003, , United States
dc.contributor.institutionDepartment of Mathematical Sciences, University of Delaware, Newark, DE, 19716, , United States
kaust.personKalligiannaki, Evangelia
refterms.dateFOA2018-06-14T05:09:05Z
dc.date.published-online2017-10-03
dc.date.published-print2017


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