The Significant Influence of the pH Value on Citrate Coordination upon Modification of Superparamagnetic Iron Oxide Nanoparticles

Granath T, Mandel K, Loebmann P (2022)


Publication Type: Journal article

Publication year: 2022

Journal

DOI: 10.1002/ppsc.202100279

Abstract

Although citrates are commonly used to modify nanoparticles, attention is rarely paid to how the modification parameters affect the type of adsorption and, thus, possibly, the properties of the modified particles. The relevance of this and the significant impact it can have is demonstrated in this study by examining the effect of pH upon the modification of superparamagnetic iron oxide nanoparticles (SPIONs) with citrate, using a citrate concentration that yields a high molecular surface density but induces almost no coordination pressure. Relying first on a number of classical surfaces analyzing methods, no clear pH-dependent differences can be identified. Finally, the consideration of the thermally induced redox behavior gives a decisive clue to unravel the "citric acid mystery" and to put together the, until then, weak hints into an overall picture. This shows that the citrate carboxyl groups are linked to the oxidic surface pH dependently via hydrogen bonds to hydroxide groups or coordinatively to iron ions and, besides, also interact, to a certain extent, with ammonia that is used for pH adjustment. With these findings, it is finally possible to explain the observed differences when the citrate-modified SPIONs are coated with silica (SiO2) or redispersed after spray-drying.

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APA:

Granath, T., Mandel, K., & Loebmann, P. (2022). The Significant Influence of the pH Value on Citrate Coordination upon Modification of Superparamagnetic Iron Oxide Nanoparticles. Particle & Particle Systems Characterization. https://doi.org/10.1002/ppsc.202100279

MLA:

Granath, Tim, Karl Mandel, and Peer Loebmann. "The Significant Influence of the pH Value on Citrate Coordination upon Modification of Superparamagnetic Iron Oxide Nanoparticles." Particle & Particle Systems Characterization (2022).

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