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Computational modeling of passive transport of functionalized nanoparticles. | LitMetric

AI Article Synopsis

  • Functionalized nanoparticles (NPs) exhibit diverse structures in different systems; thus, their modeling often simplifies them to spherical shapes to understand their behaviors.
  • At the nanoscale, complex interactions arise from changes in particle morphology, especially near confinement or walls, impacting diffusion characteristics that require detailed modeling beyond basic approximations.
  • The study uses the Rigid Multi-Blob (RMB) method to analyze the transport of these nanoparticles, finding that their functional groups and morphology significantly affect their diffusion and mobility, which has implications for applications in biomedical fields and materials science.

Article Abstract

Functionalized nanoparticles (NPs) are complex objects present in a variety of systems ranging from synthetic grafted nanoparticles to viruses. The morphology and number of the decorating groups can vary widely between systems. Thus, the modeling of functionalized NPs typically considers simplified spherical objects as a first-order approximation. At the nanoscale label, complex hydrodynamic interactions are expected to emerge as the morphological features of the particles change, and they can be further amplified when the NPs are confined or near walls. Direct estimation of these variations can be inferred via diffusion coefficients of the NPs. However, the evaluation of the coefficients requires an improved representation of the NPs morphology to reproduce important features hidden by simplified spherical models. Here, we characterize the passive transport of free and confined functionalized nanoparticles using the Rigid Multi-Blob (RMB) method. The main advantage of RMB is its versatility to approximate the mobility of complex structures at the nanoscale with significant accuracy and reduced computational cost. In particular, we investigate the effect of functional groups' distribution, size, and morphology over nanoparticle translational and rotational diffusion. We identify that the presence of functional groups significantly affects the rotational diffusion of the nanoparticles; moreover, the morphology of the groups and number induce characteristic mobility reduction compared to non-functionalized nanoparticles. Confined NPs also evidenced important alterations in their diffusivity, with distinctive signatures in the off-diagonal contributions of the rotational diffusion. These results can be exploited in various applications, including biomedical, polymer nanocomposite fabrication, drug delivery, and imaging.

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Source
http://dx.doi.org/10.1063/5.0136833DOI Listing

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