Cook, K.R. orcid.org/0009-0008-5534-2813, Head, D. orcid.org/0000-0003-0216-6787 and Dougan, L. orcid.org/0000-0002-2620-5827 (2023) Modelling network formation in folded protein hydrogels by cluster aggregation kinetics. Soft Matter, 19 (15). pp. 2780-2791. ISSN 1744-683X
Abstract
Globular folded protein-based hydrogels are becoming increasingly attractive due to their specific biological functionality, as well as their responsiveness to stimuli. By modelling folded proteins as colloids, there are rich opportunities to explore network formation mechanisms in protein hydrogels that negate the need for computationally expensive simulations which capture the full complexity of proteins. Here we present a kinetic lattice-based model which simulates the formation of irreversibly chemically crosslinked, folded protein-based hydrogels. We identify the critical point of gel percolation, explore the range of network regimes covering diffusion-limited to reaction-limited cluster aggregation (DLCA and RLCA, respectively) network formation mechanisms and predict the final network structure, fractal dimensions and final gel porosity. We reveal a crossover between DLCA and RLCA mechanisms as a function of protein volume fraction and show how the final network structure is governed by the structure at the percolation point, regardless of the broad variation of non-percolating cluster masses observed across all systems. An analysis of the pore size distribution in the final network structures reveals that, approaching RLCA, gels have larger maximal pores than the DLCA counterparts for both volume fractions studied. This general kinetic model and the analysis tools generate predictions of network structure and concurrent porosity over a broad range of experimentally controllable parameters that are consistent with current expectations and understanding of experimental results.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Royal Society of Chemistry 2023. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Food Science and Nutrition (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Physics and Astronomy (Leeds) > Molecular & Nanoscale Physics The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Computation Science & Engineering |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 Jan 2025 13:23 |
Last Modified: | 16 Jan 2025 15:44 |
Status: | Published |
Publisher: | Royal Society of Chemistry (RSC) |
Identification Number: | 10.1039/d3sm00111c |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:221618 |