Electrostatically modulated magnetophoretic transport of functionalised iron-oxide nanoparticles through hydrated networks
Source abstract
Abstract
Factors that determine magnetophoretic transport of magnetic nanoparticles (MNPs) through hydrated polymer networks under the influence of an external magnetic field gradient were studied. Functionalised iron oxide cores (8.9 nm core diameter) were tracked in real-time as they moved through agarose gels under the influence of an inhomogeneous magnetic field. Terminal magnetophoretic velocities were observed in all cases, these were quantified and found to be highly reproducible and sensitive to the conditions. Increasing agarose content reduced magnetophoretic velocity, we attribute this to increasingly tortuous paths through the porous hydrated polymer network and propose a new factor to quantify the tortuosity. The impact of MNP surface functionalisation, charge, network fixed charge content, and ionic strength of the aqueous phase on velocity were studied to separate these effects. For MNPs functionalised with polyethylene glycol (PEG) increasing chain length reduced velocity but the tortuosity extracted, which is a function of the network, was unchanged; validating the approach. For charged citrate- and arginine-functionalised MNPs, magnetophoretic velocities were found to increase for particles with positive and decrease for particles with negative zeta potential. In both cases these effects could be moderated by reducing the number of agarose anionic residues and/or increasing the ionic strength of the aqueous phase; conditions under which tortuosity again becomes the critical factor. A model for MNP transport identifying the contributions from the tortuous pore network and from electrostatic effects associated with the pore constrictions is proposed.
Source: europepmc · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Nanopore and Nanochannel Transport Studies · Electrostatics and Colloid Interactions · Microfluidic and Bio-sensing Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Insight SFI Research Centre For Data Analytics; National Centre for Sensor Research; School of Chemical Sciences
Dublin City University
Ireland
School of Chemistry
University College Dublin
Trinity College Dublin
Funding
Science Foundation Ireland
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