| Literature DB >> 32738286 |
Bing Wu1, Walter Chassé2, Klaus Zick3, Michael D Mantle4, Andreas Heise5, Dermot F Brougham6, Victor M Litvinov7.
Abstract
Polyacrylates are important polymers widely used in pharmaceutical industry such as drug coatings due to their low cost, processability and ease of functionalisation. Chemical functionalities (e.g. H-bonding) can be easily included to modulate the transport of low molecular weight drug-like entities through the network. Understanding how such microscopic structural modifications determine macroscopic diffusion is critical for designing next generation responsive polymers. In this study pulsed field gradient (PFG) 1H NMR measurements of the self-diffusion of a dye molecule (Eosin Y) in a series of polyacrylate networks with differing H-bonding strength were undertaken; it was found that the diffusion of Eosin Y is significantly reduced in networks with H-bonding. Detailed analyses by 1H NMR relaxometry and double quantum (DQ) NMR show that H-bonding can also reduce polymer chain mobility. Furthermore, DSC thermoporometry showed a significant increase in the average network mesh size potentially due to the pre-organization of H-bonding containing monomer during network curing. By introducing the H-bonding disrupter, LiClO4, it was found that the diffusivity of solute becomes positively correlated to the average mesh size across the series of networks. Hence, a modified diffusion model based on hydrodynamic theory is proposed to separate the direct (solute-network) H-bonding contribution to solute diffusion from the indirect contribution arising from monomer pre-ordering induced mesh size reduction. Finally, it is shown that the same direct and indirect contributions to microscopic diffusivity, arising from the H-bond strength of the co-monomers, also contribute significantly to the macroscopic membrane permeability which is similarly subject to H-bond disruption.Entities:
Keywords: Coating; DSC thermoporometry; Hydrogen bonding; Molecular self-diffusion; NMR relaxometry; Pulsed-field gradient NMR
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Year: 2020 PMID: 32738286 DOI: 10.1016/j.jconrel.2020.07.039
Source DB: PubMed Journal: J Control Release ISSN: 0168-3659 Impact factor: 9.776