The DOI matches its Crossref record.
Solute Diffusion within Hydrogels. Mechanisms and Models
Abstract
Solute diffusion in hydrogels is important in many biotechnology fields. Solute behavior in hydrogels has been explained in terms of reduction in hydrogel free volume, enhanced hydrodynamic drag on the solute, increased path length due to obstruction, and a combination of hydrodynamic drag and obstruction effects. In this article the various mathematical models derived to explain and predict solute diffusion in hydrogels are reviewed and tested against literature data. These models can be divided into those applicable to hydrogels composed of flexible polymer chains (i.e., homogeneous hydrogels) and those composed of rigid polymer chains (i.e., heterogeneous hydrogels). For homogeneous hydrogels it was determined that a scaling hydrodynamic model provided the best explanation for solute diffusion, while for heterogeneous hydrogels obstruction models were more consistent with the experimental data. Both the scaling hydrodynamic model and the most appropriate obstruction model contain undefined parameters which must be clarified in order for these models to gain widespread acceptance.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Designing hydrogels for controlled drug delivery
Li, J., & Mooney, D. J. (2016) · Nature Reviews Materials · doi:10.1038/natrevmats.2016.71 · Cited by 4,832
Hydrogels in regenerative medicine
Slaughter, B. V., Khurshid, S. S., Fisher, O. Z., Khademhosseini, A., & Peppas, N. A. (2009) · Advanced Materials · doi:10.1002/adma.200802106 · Cited by 2,703
Hydrogels in controlled release formulations: Network design and mathematical modeling
Lin, C.-C., & Metters, A. T. (2006) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2006.09.004 · Cited by 1,768
Stimulus-responsive hydrogels: theory, modern advances, and applications
Koetting, M. C., Peters, J. T., Steichen, S. D., & Peppas, N. A. (2015) · Materials Science and Engineering: R: Reports · doi:10.1016/j.mser.2015.04.001 · Cited by 1,191
Liu, X., Liu, J., Lin, S., & Zhao, X. (2020) · Materials Today · doi:10.1016/j.mattod.2019.12.026 · Cited by 1,023
Physicochemical Foundations and Structural Design of Hydrogels in Medicine and Biology
Peppas, N. A., Huang, Y., Torres-Lugo, M., Ward, J. H., & Zhang, J. (2000) · Annual Review of Biomedical Engineering · doi:10.1146/annurev.bioeng.2.1.9 · Cited by 1,016
Brady, J. P., Farber, P. J., Sekhar, A., Lin, Y.-H., Huang, R., Bah, A., Nott, T. J., Chan, H. S., Baldwin, A. J., Forman-Kay, J. D., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1706197114 · Cited by 533
Stimuli-responsive hydrogels in drug delivery and tissue engineering
Sood, N., Bhardwaj, A., Mehta, S., & Mehta, A. (2016) · Drug Delivery · doi:10.3109/10717544.2014.940091 · Cited by 426
Richbourg, N. R., & Peppas, N. A. (2020) · Progress in Polymer Science · doi:10.1016/j.progpolymsci.2020.101243 · Cited by 367
Supramolecular engineering of hydrogels for drug delivery
Bernhard, S., & Tibbitt, M. W. (2021) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2021.02.002 · Cited by 363
Therapeutic applications of hydrogels in oral drug delivery
Sharpe, L. A., Daily, A. M., Horava, S. D., & Peppas, N. A. (2014) · Expert Opinion on Drug Delivery · doi:10.1517/17425247.2014.902047 · Cited by 354
Properties of Water Bound in Hydrogels
Gun’ko, V., Savina, I., & Mikhalovsky, S. (2017) · Gels · doi:10.3390/gels3040037 · Cited by 322
McClements, D. J. (2017) · Advances in Colloid and Interface Science · doi:10.1016/j.cis.2016.12.005 · Cited by 267
Pepsin diffusivity in whey protein gels and its effect on gastric digestion
Luo, Q., Borst, J. W., Westphal, A. H., Boom, R. M., & Janssen, A. E. M. (2017) · Food Hydrocolloids · doi:10.1016/j.foodhyd.2016.11.046 · Cited by 123
Ma, L., Barker, J., Zhou, C., Li, W., Zhang, J., Lin, B., Foltz, G., Küblbeck, J., & Honkakoski, P. (2012) · Biomaterials · doi:10.1016/j.biomaterials.2012.02.054 · Cited by 83
3D fluid-dynamic ovarian cancer model resembling systemic drug administration for efficacy assay
Marrella, A. (2020) · ALTEX · doi:10.14573/altex.2003131 · Cited by 36
Gerola, A. P., Silva, D. C., Matsushita, A. F. Y., Borges, O., Rubira, A. F., Muniz, E. C., & Valente, A. J. M. (2016) · European Polymer Journal · doi:10.1016/j.eurpolymj.2016.03.041 · Cited by 26
Drug susceptibility of matrix‐encapsulated Candida albicans nano‐biofilms
Srinivasan, A., Gupta, C. M., Agrawal, C. M., Leung, K. P., Lopez‐Ribot, J. L., & Ramasubramanian, A. K. (2014) · Biotechnology and Bioengineering · doi:10.1002/bit.25120 · Cited by 11
“P A A uthor M anuscript long fibers, rg ~200 nm, and ϕ ~0.01, the Ogston equation yields De ~0.9D0 (Mu et al. 2007) Since alginate forms gel only by crosslinking, rg ~0.6–0.8 nm, and ϕ ~0.01, the Ogston equation yields the De ~0.8D0 (Amsden 1998).”
BackgroundInfluential
Metadata
- Authors
- Amsden, B.
- Venue
- Macromolecules
- Publisher
- American Chemical Society (ACS)
- Published
- 1998-10-20
- Volume
- 31
- Issue
- 23
- Pages
- 8382-8395
- ISSN
- 0024-9297 (ISSN-L)
- 1520-5835
- OpenAlex
- W2029375419
- Cited by
- 942
- References
- 0
- FWCI
- 5.09
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
