A Monte Carlo model for self-assembly of polytetrafluoroethylene nanoparticle films via repulsive electrostatic interactions

Literature Information

Publication Date 2019-05-20
DOI 10.1039/C9CP01856E
Impact Factor 3.676
Authors

Chuan Du, Dong Feng, Chaolang Chen, Jiadao Wang


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Abstract

Self-assembly of polytetrafluoroethylene (PTFE) nanoparticle films on an aluminum alloy substrate under repulsive electrostatic interactions has been achieved experimentally. However, a theoretical framework which is able to accurately predict the self-assembly kinetics based on their underlying mechanisms is not yet available. In this work, we formulate a Monte Carlo model to make predictions on the formation of close-packed monolayer and multilayer PTFE nanoparticle films during repulsive electrostatic self-assembly. In the model, the parameters are obtained from experimental measurements. Our simulation results demonstrate that the layer number of close-packed PTFE nanoparticle films on the aluminum alloy substrate increases with an increase of nanoparticle concentration and an increase of deposition time, which match well with the experimental observations. Beyond this, the underlying mechanism in which the close-packed PTFE nanoparticle film cannot be formed on the Cu substrate was also revealed, which is attributed to the decrease of the substrate repulsive interaction. Hence, the present work not only unveils the self-assembly kinetics of nanoparticle films, but also provides useful guidelines to controllable self-assembly of nanoparticle films with a desired number of layers.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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