Manifold experimental studies have recently pointed out how stimuli-sensitive microgels can provide a unique approach to emulsions [1]. Their stability, in fact, can be easily controlled trading on the temperature and the pH of the solutions, being the responsiveness to these parameters one of the features for which microgels are widely employed in various fields. In contrast to rigid particles that stabilize Pickering emulsions solely via interfacial tension effects, a comprehensive understanding of soft emulsion stabilizers cannot lack of a description in terms of the microgel swelling, elasticity and deformability [2]. We are now able to provide novel theoretical insights in this respect, thanks to a cutting-edge model that reproduces in silico the polymeric network of PNIPAM microgels [3]. After having tested the response of this microgel model to a coarse-grained explicit solvent [4], we perform Molecular Dynamics simulations of the liquid-liquid interface. In contrast to cases where soft ligands are anchored to a hard core, we observe the flattening of the microgel and the spread of the polymer chains at the interface. By varying the parameters of the monomer-solvent potential, we are able to selectively tune the surface tension enabling the asymmetric squeeze of the network, as expected for solvents of different qualities. Moreover, we note a dependence on the number of crosslinks of the microgel: the higher their amount, the stiffer the polymer network. The newly designed setup will allow us to provide a three-dimensional characterization of the microgel positioning and microstructure at the interface, paving the way to the calculation of multiple particles’ effective interactions. [1] W. Richtering Langmuir 2012, 28, 17218−17229. [2] L. Isa et al., Phys. Chem. Chem. Phys., 2017, 19, 8671. [3] N. Gnan, L. Rovigatti, M, Bergman, E. Zaccarelli, Macromolecules 50 (21), 2017. [4] F. Camerin, N. Gnan, L. Rovigatti, E. Zaccarelli, In preparation.
In silico modelling of microgels at interfaces / Camerin, Fabrizio. - (2018). (Intervento presentato al convegno Joint Summer School SFB 985 Georgia Institute of Technology, Functional Microgels and Microgel Systems tenutosi a Aachen; Germany).
In silico modelling of microgels at interfaces
Fabrizio Camerin
2018
Abstract
Manifold experimental studies have recently pointed out how stimuli-sensitive microgels can provide a unique approach to emulsions [1]. Their stability, in fact, can be easily controlled trading on the temperature and the pH of the solutions, being the responsiveness to these parameters one of the features for which microgels are widely employed in various fields. In contrast to rigid particles that stabilize Pickering emulsions solely via interfacial tension effects, a comprehensive understanding of soft emulsion stabilizers cannot lack of a description in terms of the microgel swelling, elasticity and deformability [2]. We are now able to provide novel theoretical insights in this respect, thanks to a cutting-edge model that reproduces in silico the polymeric network of PNIPAM microgels [3]. After having tested the response of this microgel model to a coarse-grained explicit solvent [4], we perform Molecular Dynamics simulations of the liquid-liquid interface. In contrast to cases where soft ligands are anchored to a hard core, we observe the flattening of the microgel and the spread of the polymer chains at the interface. By varying the parameters of the monomer-solvent potential, we are able to selectively tune the surface tension enabling the asymmetric squeeze of the network, as expected for solvents of different qualities. Moreover, we note a dependence on the number of crosslinks of the microgel: the higher their amount, the stiffer the polymer network. The newly designed setup will allow us to provide a three-dimensional characterization of the microgel positioning and microstructure at the interface, paving the way to the calculation of multiple particles’ effective interactions. [1] W. Richtering Langmuir 2012, 28, 17218−17229. [2] L. Isa et al., Phys. Chem. Chem. Phys., 2017, 19, 8671. [3] N. Gnan, L. Rovigatti, M, Bergman, E. Zaccarelli, Macromolecules 50 (21), 2017. [4] F. Camerin, N. Gnan, L. Rovigatti, E. Zaccarelli, In preparation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
