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Diffusiophoretic transport of colloids in porous media

arXiv (Cornell University) 2024 3 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Mobin Alipour, Yiran Li, Haoyu Liu, Amir A. Pahlavan

Summary

This study is not primarily about microplastics; it investigates how chemical gradients (diffusiophoresis) change how colloidal particles move through porous media in general. Microplastic remediation is mentioned as one potential application area, but the work is fundamentally a fluid physics study.

Understanding how colloids move in crowded environments is key for gaining control over their transport in applications such as drug delivery, filtration, contaminant/microplastic remediation and agriculture. The classical models of colloid transport in porous media rely on geometric characteristics of the medium, and hydrodynamic/non-hydrodynamic equilibrium interactions to predict their behavior. However, chemical gradients are ubiquitous in these environments and can lead to the non-equilibrium diffusiophoretic migration of colloids. Here, combining microfluidic experiments, numerical simulations, and theoretical modeling we demonstrate that diffusiophoresis leads to significant macroscopic changes in the dispersion of colloids in porous media. We displace a suspension of colloids dispersed in a background salt solution with a higher/lower salinity solution and monitor the removal of the colloids from the medium. While mixing weakens the solute gradients, leading to the diffusiophoretic velocities that are orders of magnitude weaker than the background fluid flow, we show that the cross-streamline migration of colloids changes their macroscopic transit time and dispersion through the medium by an order of magnitude compared to the control case with no salinity gradients. Our observations demonstrate that solute gradients modulate the influence of geometric disorder on the transport, pointing to the need for revisiting the classical models of colloid transport in porous media to obtain predictive models for technological, medical, and environmental applications.

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