Multiscale modeling of emergent materials : biological and soft matter

T. Murtola, A. Bunker, I. Vattulainen, M. Deserno, M.E.J. Karttunen

    Research output: Contribution to journalArticleAcademicpeer-review

    201 Citations (Scopus)

    Abstract

    In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed in the context of the so-called Henderson theorem and the inverse Monte Carlo method of Lyubartsev and Laaksonen. In the second part, we take a different look at coarse graining by analyzing conformations of molecules. This is done by the application of self-organizing maps, i.e., a neural network type approach. Such an approach can be used to guide the selection of the relevant degrees of freedom. Then, we discuss technical issues related to the popular dissipative particle dynamics (DPD) method. Importantly, the potentials derived using the inverse Monte Carlo method can be used together with the DPD thermostat. In the final part we focus on solvent-free modeling which offers a different route to coarse graining by integrating out the degrees of freedom associated with solvent.
    Original languageEnglish
    Pages (from-to)1869-1892
    JournalPhysical Chemistry Chemical Physics
    Volume11
    Issue number12
    DOIs
    Publication statusPublished - 2009

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