Dendritic nanoparticle self-assembly from drying a sessile nanofluid droplet

Literature Information

Publication Date 2021-06-29
DOI 10.1039/D1CP01181B
Impact Factor 3.676
Authors

Junheng Ren, Alexandru Crivoi, Fei Duan


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Abstract

The pattern formation left by a drying nanofluid droplet is related to the evaporation induced particle self-assembly. The experimental results demonstrate the formation of dendritic particle deposition after the liquid phase of unpinned sessile nanofluid droplets is fully evaporated. The dried-in particle assemblies exhibit the dendritic patterns connecting the sprawling branches with a central core structure. The branched structures are formed by particles merging in the receding front. A three-dimensional lattice-gas kinetic Monte Carlo model is developed to simulate the particle self-assembling behaviour in a drying particle-laden droplet with the dewetting three-phase line. The parameter study is carried out to demonstrate the trend of the dendritic pattern formation. The various patterns are simulated by varying the chemical potentials and the interaction energies among particles, liquids, and substrates. The dendritic particle depositions are measured in three dimensions after the nanofluid droplet is completely dried. Qualitative agreement is observed between the experimental and the numerical results. Thicker branches and larger central cores are observed with an increase of particle concentrations.

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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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