A single-particle energy-conserving dissipative particle dynamics approach for simulating thermophoresis of nanoparticles in polymer networks

The transport of nanoparticles in polymer networks has critical implications in biology and medicine, especially through thermophoresis in response to temperature gradients. This study presents a single-particle energy-conserving dissipative particle dynamics (seDPD) method by integrating a single-particle model into the energy-conserving DPD model to simulate the mesoscopic thermophoretic behavior of nanoparticles in polymer matrices. We first validate the newly developed seDPD model through comparisons with analytical solutions for nanoparticle viscosity, thermal diffusivity, and hydrodynamic drag and then demonstrate the effectiveness of the seDPD model in capturing thermophoretic forces induced by temperature gradients. The results show that nanoparticles driven by the Soret forces exhibit unique transport characteristics, such as drift velocity and diffusivity, leading to a significant acceleration of nanoparticle diffusion in the polymer network, which has been known as the giant acceleration of diffusion. Quantifying how nanoparticles move in flexible polymer networks sheds light on the interaction dynamics of nanoparticles within polymer networks, providing insight into nanoparticle behavior in complex environments that could be leveraged in various applications from drug delivery to material design.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2024-11-08
DOI
https://doi.org/10.1063/5.0227060
Citations
2
Primary Topic
Field-Flow Fractionation Techniques
Type
article
Field-Weighted Citation Impact
0.75

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article

A single-particle energy-conserving dissipative particle dynamics approach for simulating thermophoresis of nanoparticles in polymer networks

Jun Song, Yu Lu, Guohui Hu, Zhen Li
2 citations
The Journal of Chemical Physics
Field-Flow Fractionation Techniques
0.75
article

A single-particle energy-conserving dissipative particle dynamics approach for simulating thermophoresis of nanoparticles in polymer networks

Jun Song, Yu Lu, Guohui Hu, Zhen Li
article en
2 citations

Abstract

The transport of nanoparticles in polymer networks has critical implications in biology and medicine, especially through thermophoresis in response to temperature gradients. This study presents a single-particle energy-conserving dissipative particle dynamics (seDPD) method by integrating a single-particle model into the energy-conserving DPD model to simulate the mesoscopic thermophoretic behavior of nanoparticles in polymer matrices. We first validate the newly developed seDPD model through comparisons with analytical solutions for nanoparticle viscosity, thermal diffusivity, and hydrodynamic drag and then demonstrate the effectiveness of the seDPD model in capturing thermophoretic forces induced by temperature gradients. The results show that nanoparticles driven by the Soret forces exhibit unique transport characteristics, such as drift velocity and diffusivity, leading to a significant acceleration of nanoparticle diffusion in the polymer network, which has been known as the giant acceleration of diffusion. Quantifying how nanoparticles move in flexible polymer networks sheds light on the interaction dynamics of nanoparticles within polymer networks, providing insight into nanoparticle behavior in complex environments that could be leveraged in various applications from drug delivery to material design.

The Journal of Chemical PhysicsVol. 161(18)
Shanghai University (CN), Shanghai University of Engineering Science (CN), Nantong University (CN), Clemson University (US)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 32%
Field-Flow Fractionation Techniques
0.75
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