Consistent and Transferable Force Fields for Statistical Copolymer Systems at the Mesoscale

The statistical trajectory matching (STM) method was applied successfully to derive coarse grain (CG) models for bulk properties of homopolymers. The extension of the methodology for building CG models for statistical copolymer systems is much more challenging. We present here the strategy for devel...

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Veröffentlicht in:Journal of chemical theory and computation 2022-11, Vol.18 (11), p.6940-6951
Hauptverfasser: Nkepsu Mbitou, R. L., Goujon, F., Dequidt, A., Latour, B., Devémy, J., Blaak, R., Martzel, N., Emeriau-Viard, C., Tchoufag, J., Garruchet, S., Munch, E., Hauret, P., Malfreyt, P.
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Sprache:eng
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Zusammenfassung:The statistical trajectory matching (STM) method was applied successfully to derive coarse grain (CG) models for bulk properties of homopolymers. The extension of the methodology for building CG models for statistical copolymer systems is much more challenging. We present here the strategy for developing CG models for styrene–butadiene–rubber, and we compare the quality of the resulting CG force fields on the structure and thermodynamics at different chemical compositions. The CG models are used through the use of a genuine mesoscopic method called the dissipative particle dynamics method and compared to high-resolution molecular dynamics simulations. We conclude that the STM method is able to produce coarse-grained potentials that are transferable in composition by using only a few reference systems. Additionally, this methodology can be applied on any copolymer system.
ISSN:1549-9618
1549-9626
DOI:10.1021/acs.jctc.2c00945