Soft nanocomposites represent both a theoretical and an experimental challenge due to the high number of the microscopic constituents that strongly influence the behaviour of the systems. An effective theoretical description of such systems invokes a reduction of the degrees of freedom to be analysed, hence requiring the introduction of an efficient, quantitative, coarse-grained description. We here report on a novel coarse graining approach based on a set of transferable potentials that quantitatively reproduces properties of mixtures of linear and star-shaped homopolymeric nanocomposites. By renormalizing groups of monomers into a single effective potential between a f-functional star polymer and an homopolymer of length N0, and through a scaling argument, it will be shown how a substantial reduction of the to degrees of freedom allows for a full quantitative description of the system. Our methodology is tested upon full monomer simulations for systems of different molecular weight, proving its full predictive potential.
Locatelli, E., Capone, B., Likos, C.N. (2016). Multiblob coarse-graining for mixtures of long polymers and soft colloids. THE JOURNAL OF CHEMICAL PHYSICS, 145(17), 174901 [10.1063/1.4965957].
Multiblob coarse-graining for mixtures of long polymers and soft colloids
Capone B.;
2016-01-01
Abstract
Soft nanocomposites represent both a theoretical and an experimental challenge due to the high number of the microscopic constituents that strongly influence the behaviour of the systems. An effective theoretical description of such systems invokes a reduction of the degrees of freedom to be analysed, hence requiring the introduction of an efficient, quantitative, coarse-grained description. We here report on a novel coarse graining approach based on a set of transferable potentials that quantitatively reproduces properties of mixtures of linear and star-shaped homopolymeric nanocomposites. By renormalizing groups of monomers into a single effective potential between a f-functional star polymer and an homopolymer of length N0, and through a scaling argument, it will be shown how a substantial reduction of the to degrees of freedom allows for a full quantitative description of the system. Our methodology is tested upon full monomer simulations for systems of different molecular weight, proving its full predictive potential.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.