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Structure and Dynamics of Stimuli-Responsive Nanoparticle Monolayers at Fluid Interfaces.
Langmuir ; 34(19): 5581-5591, 2018 05 15.
Article em En | MEDLINE | ID: mdl-29676917
Stimuli-responsive nanoparticles at fluid interfaces offer great potential for realizing on-demand and controllable self-assembly that can benefit various applications. Here, we conducted electrostatic dissipative particle dynamics simulations to provide a fundamental understanding of the microstructure and interfacial dynamics of responsive nanoparticle monolayers at a water-oil interface. The model nanoparticle is functionalized with polyelectrolytes to render the pH sensitivity, which permits further manipulation of the monolayer properties. The monolayer structure was analyzed in great detail through the density and electric field distributions, structure factor, and Voronoi tessellation. Even at a low surface coverage, a continuous disorder-to-order phase transition was observed when the particle's degree of ionization increases in response to pH changes. The six-neighbor particle fraction and bond orientation order parameter quantitatively characterize the structural transition induced by long-range electrostatic interactions. Adding salt can screen the electrostatic interactions and offer additional control on the monolayer structure. The detailed dynamics of the monolayer in different states was revealed by analyzing mean-squared displacements, in which different diffusion regimes were identified. The self-diffusion of individual particles and the collective dynamics of the whole monolayer were probed and correlated with the structural transition. Our results provide deeper insight into the dynamic behavior of responsive nanoparticle surfactants and lay the groundwork for bottom-up synthesis of novel nanomaterials, responsive emulsions, and microdroplet reactors.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article