Title

Understanding The Adsorption Interface Of Polyelectrolyte Coating On Redox Active Nanoparticles Using Soft Particle Electrokinetics And Its Biological Activity

Keywords

catalase activity; cerium oxide nanoparticles; colloidal dispersion; Gibbs free energy; polymer coating; soft particle electrokinetics

Abstract

The application of cerium oxide nanoparticles (CNPs) for therapeutic purposes requires a stable dispersion of nanoparticles in a biological environment. The objective of this study is to tailor the properties of polyelectrolyte coated CNPs as a function of molecular weight to achieve a stable and catalytic active dispersion. The coating of CNPs with polyacrylic acid (PAA) has increased the dispersion stability of CNPs and enhanced the catalytic ability. The stability of PAA coating was analyzed using the change in the Gibbs free energy computed by the Langmuir adsorption model. The adsorption isotherms were determined using soft particle electrokinetics which overcomes the challenges presented by other techniques. The change in Gibbs free energy was highest for CNPs coated with PAA of 250 kg/mol indicating the most stable coating. The change in free energy for PAA of 100 kg/mol coated CNPs was 85% lower than the PAA of 250 kg/mol coated CNPs. This significant difference is caused by the strong adsorption of PAA of 100 kg/mol on CNPs. Catalytic activity of PAA-CNPs is assessed by the catalase enzymatic mimetic activity of nanoparticles. The catalase activity was higher for PAA coated CNPs as compared to bare CNPs which indicated preferential adsorption of hydrogen peroxide induced by coating. This indicates that the catalase activity is also affected by the structure of the coating layer. © 2014 American Chemical Society.

Publication Date

4-23-2014

Publication Title

ACS Applied Materials and Interfaces

Volume

6

Issue

8

Number of Pages

5472-5482

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1021/am405250g

Socpus ID

84899542744 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84899542744

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