Abstract
Nanoparticle diffusion is a fundamental process that ubiquitously exists in life science and engineering technology. Recent studies demonstrate the potential of harnessing mechanical deformation to program nanoparticle diffusion in hydrogels, offering an expanded spectrum of nanoparticle diffusivities with precise and on-demand control. Here, we develop a mechano-diffusion characterization platform (MDCP) that integrates a mechanical system to apply controlled tension and torsion loads to deformable mediums, and an imaging system to capture spatiotemporal diffusion profiles of nanoparticles. Employing the MDCP, we study the impact of mechanical deformation on nanoparticle diffusion in hydrogels subjected to controlled stress states and loading rates.
Graphical abstract
![](http://media.springernature.com/lw685/springer-static/image/art%3A10.1557%2Fs43579-024-00596-7/MediaObjects/43579_2024_596_Figa_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1557%2Fs43579-024-00596-7/MediaObjects/43579_2024_596_Fig1_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1557%2Fs43579-024-00596-7/MediaObjects/43579_2024_596_Fig2_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1557%2Fs43579-024-00596-7/MediaObjects/43579_2024_596_Fig3_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1557%2Fs43579-024-00596-7/MediaObjects/43579_2024_596_Fig4_HTML.png)
Data availability
Data will be made available on reasonable request.
References
S. Patel et al., Naturally-occurring cholesterol analogues in lipid nanoparticles induce polymorphic shape and enhance intracellular delivery of mRNA. Nat. Commun. 11, 983 (2020). https://doi.org/10.1038/s41467-020-14527-2
M. Liu et al., Real-time visualization of clustering and intracellular transport of gold nanoparticles by correlative imaging. Nat. Commun. 8, 15646 (2017). https://doi.org/10.1038/ncomms15646
M.I. Pino-Argumedo et al., Elastic mucus strands impair mucociliary clearance in cystic fibrosis pigs. Proc. Natl. Acad. Sci. U.S.A. 119, e2121731119 (2022). https://doi.org/10.1073/pnas.2121731119
H. Gu et al., Artificial microtubules for rapid and collective transport of magnetic microcargoes. Nat. Mach. Intell. 4, 678–684 (2022). https://doi.org/10.1038/s42256-022-00510-7
A. Mateu-Regue et al., Single mRNP analysis reveals that small cytoplasmic mRNP granules represent mRNA singletons. Cell Rep. 29, 736–748 (2019). https://doi.org/10.1016/j.celrep.2019.09.018
S. Hu et al., A mussel-inspired film for adhesion to wet buccal tissue and efficient buccal drug delivery. Nat. Commun. 12, 1689 (2021). https://doi.org/10.1038/s41467-021-21989-5
S. Basu et al., Numerical evaluation of spray position for improved nasal drug delivery. Sci. Rep. 10, 10568 (2020). https://doi.org/10.1038/s41598-020-66716-0
H.S. Muddana, S. Sengupta, T.E. Mallouk, A. Sen, P.J. Butler, Substrate catalysis enhances single-enzyme diffusion. J. Am. Chem. Soc. 132, 2110–2111 (2010)
Y. Qin et al., Hollow mesoporous metal–organic frameworks with enhanced diffusion for highly efficient catalysis. ACS Catal. 10, 5973–5978 (2020)
S. Raju et al., Improved methodology to determine the fate and transport of microplastics in a secondary wastewater treatment plant. Water Res. 173, 115549 (2020). https://doi.org/10.1016/j.watres.2020.115549
S. Freeman et al., Between source and sea: the role of wastewater treatment in reducing marine microplastics. J. Environ. Manage. 266, 110642 (2020). https://doi.org/10.1016/j.jenvman.2020.110642
H. Zhang et al., In situ formation of gold nanoparticles decorated Ti3C2 MXenes nanoprobe for highly sensitive electrogenerated chemiluminescence detection of exosomes and their surface proteins. Anal. Chem. 92, 5546–5553 (2020)
S. Lin et al., Natural perspiration sampling and in situ electrochemical analysis with hydrogel micropatches for user-identifiable and wireless chemo/biosensing. ACS Sens. 5, 93–102 (2020). https://doi.org/10.1021/acssensors.9b01727
C.C. Miller, The Stokes–Einstein law for diffusion in solution. Proc. R. Soc. London Ser. A, Containing Papers Math. Phys. Charact. 106, 724–749 (1924)
Q. Liu, S. Huang, Z. Suo, Brownian motion of molecular probes in supercooled liquids. Phys. Rev. Lett. 114, 224301 (2015). https://doi.org/10.1103/PhysRevLett.114.224301
J. Liu, S. Lin, Strain-engineered particle diffusion in uniaxially deformed polymer networks. J. Mechan. Phys. Solids (2024). https://doi.org/10.1016/j.jmps.2024.105732
P.J. Moncure, Z.C. Simon, J.E. Millstone, J.E. Laaser, Relationship between gel mesh and particle size in determining nanoparticle diffusion in hydrogel nanocomposites. J. Phys. Chem. B 126, 4132–4142 (2022). https://doi.org/10.1021/acs.jpcb.2c00771
Y. Gu, M.E. Distler, H.F. Cheng, C. Huang, C.A. Mirkin, A general DNA-gated hydrogel strategy for selective transport of chemical and biological cargos. J. Am. Chem. Soc. 143, 17200–17208 (2021)
J. Floury, M.-N. Madec, F. Waharte, S. Jeanson, S. Lortal, First assessment of diffusion coefficients in model cheese by fluorescence recovery after photobleaching (FRAP). Food Chem. 133, 551–556 (2012)
Y.G. Anissimov, X. Zhao, M.S. Roberts, A.V. Zvyagin, Fluorescence recovery after photo-bleaching as a method to determine local diffusion coefficient in the stratum corneum. Int. J. Pharm. 435, 93–97 (2012)
H.H. Park, B. Wang, S. Moon, T. Jepson, K. Xu, Machine-learning-powered extraction of molecular diffusivity from single-molecule images for super-resolution map**. Commun. Biol. 6, 336 (2023)
A.B. Andrews, R.E. Guerra, O.C. Mullins, P.N. Sen, Diffusivity of asphaltene molecules by fluorescence correlation spectroscopy. J. Phys. Chem. A 110, 8093–8097 (2006)
R. Pecora, Dynamic light scattering measurement of nanometer particles in liquids. J. Nanopart. Res. 2, 123–131 (2000)
G. Costantini, S. Capuani, F.A. Farrelly, A. Taloni, A new perspective of molecular diffusion by nuclear magnetic resonance. Sci. Rep. 13, 1703 (2023)
A.J. Grodzinsky, Fields, forces, and flows in biological systems (CRC Press, Boca Raton, 2011)
H. Yuk, T. Zhang, S. Lin, G.A. Parada, X. Zhao, Tough bonding of hydrogels to diverse non-porous surfaces. Nat. Mater. 15, 190–196 (2016)
A. Gole, C.J. Murphy, Seed-mediated synthesis of gold nanorods: role of the size and nature of the seed. Chem. Mater. 16, 3633–3640 (2004)
Kafadar, Ö. & Sondaş, A. in 2016 20th National Biomedical Engineering Meeting (BIYOMUT). 1–4 (IEEE).
M. Divya, K. Saravanan, G.N. Balaji, S.C. Pandian, Light weight & low cost power bank based on LM7805 regulator for hand held applications. Int. J. Latest Technol. Eng. Manage. Appl. Sci. (IJLTEMAS) 7, 201–205 (2018)
Brooks, R. A. An electronic compass for small autonomous robots, Citeseer, (1993)
C. Bharatiraja, J. Munda, I. Vaghasia, R. Valiveti, P. Manasa, Low cost real time centralized speed control of DC motor using lab view-NI USB 6008. Int. J. Power Electron. Drive Syst. 3, 656–664 (2016)
Z. Sun, J. Fan, H. Li, H. Jiang, Current status of single particle imaging with X-ray lasers. Appl. Sci. 8, 132 (2018)
P.J. Moncure, Z.C. Simon, J.E. Millstone, J.E. Laaser, Relationship between gel mesh and particle size in determining nanoparticle diffusion in hydrogel nanocomposites. J. Phys. Chem. B 126, 4132–4142 (2022)
S. Lin, Y. Mao, R. Radovitzky, X. Zhao, Instabilities in confined elastic layers under tension: fringe, fingering and cavitation. J. Mech. Phys. Solids 106, 229–256 (2017)
S.H. Kim et al., The effect of ζ-potential and hydrodynamic size on nanoparticle interactions in hydrogels. Part. Part. Syst. Charact. 36, 1800292 (2019)
L.H. Cai, S. Panyukov, M. Rubinstein, Hop** diffusion of nanoparticles in polymer matrices. Macromolecules 48, 847–862 (2015). https://doi.org/10.1021/ma501608x
Michael Rubinstein, R. H. C. Polymer Physics. (2003)
Y.J. Yang, D.J. Mai, S. Li, M.A. Morris, B.D. Olsen, Tuning selective transport of biomolecules through site-mutated nucleoporin-like protein (NLP) hydrogels. Biomacromol 22, 289–298 (2021)
Acknowledgments
We thank Alicia Withrow for help with transmission electron microscopy imaging and Wei Zhang and Romilly Benedict for help with the dynamic light scattering characterization.
Funding
This research was funded by NSF-CBET-2320716.
Author information
Authors and Affiliations
Contributions
CY: Methodology, Data acquisition, Writing-original draft. SL: Conceptualization, Supervision, Writing-review and editing.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Supplementary file2 (MOV 25473 KB)
Supplementary file3 (MOV 4566 KB)
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Ye, C., Lin, S. A mechano-diffusion characterization platform for probing strain-programmable nanoparticle diffusion in hydrogels. MRS Communications (2024). https://doi.org/10.1557/s43579-024-00596-7
Received:
Accepted:
Published:
DOI: https://doi.org/10.1557/s43579-024-00596-7