Mechano-diffusion of Particles in Stretchable Hydrogels

Abstract

Precise control over particle diffusion is promising for diverse modern technologies. Traditionally, particle diffusion is governed by the inherent properties of liquid medium, limiting versatility and controllability. Here, we report a mechano-diffusion mechanism that harnesses mechanical deformation to control particle diffusion in stretchable hydrogels with a significantly enlarged tuning ratio and highly expanded tuning freedom. The working principle is to leverage the mechanical deformation of stretchable hydrogels for modulating the polymer network’s geometric transformation and the polymer chain’s energy, which synergistically tunes the energy barrier for particle diffusion. Using a model particle-hydrogel material system and a customized mechano-diffusion characterization platform, we demonstrate that tension loads can enhance the diffusivity of gold nanoparticles up to 22 times, far exceeding that in traditional liquid medium and by external fields. Additionally, we show particle diffusion in hydrogels can be manipulated spatiotemporally by controlling the hydrogels’ stress state and loading rate. To further push the limit of the mechano-diffusion, we use experiment, theory, and simulation to explore particle diffusion in biaxially stretched hydrogels, simultaneously expanding the mesh size and reducing the energy barrier. The enlarged tuning ratio and expanded tuning freedom enable a model-guided drug delivery system for pressure-controlled release of drug molecules. Understanding this spatiotemporal mechano-diffusion mechanism will provide insights pertinent to a broad range of biological and synthetic soft materials.

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Article information

Article type
Paper
Submitted
23 Dec 2024
Accepted
17 Feb 2025
First published
18 Feb 2025
This article is Open Access
Creative Commons BY-NC license

Soft Matter, 2025, Accepted Manuscript

Mechano-diffusion of Particles in Stretchable Hydrogels

S. Lin, C. Ye, C. Wei, J. Liu, T. H. Wong, X. Liu, Z. Song, C. Wu and Z. Li, Soft Matter, 2025, Accepted Manuscript , DOI: 10.1039/D4SM01522C

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