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Title: How to accurately predict solution-phase gold nanostar stability.

Authors: Xi, Wenjing; Phan, Hoa T; Haes, Amanda J

Published In Anal Bioanal Chem, (2018 Sep)

Abstract: Unwanted nanoparticle aggregation and/or agglomeration may occur when anisotropic nanoparticles are dispersed in various solvents and matrices. While extended Derjaguin-Landau-Verwey-Overbeek (DLVO) theory has been successfully applied to predict nanoparticle stability in solution, this model fails to accurately predict the physical stability of anisotropic nanostructures; thus limiting its applicability in practice. Herein, DLVO theory was used to accurately predict gold nanostar stability in solution by investigating how the choice of the nanostar dimension considered in calculations influences the calculated attractive and repulsive interactions between nanostructures. The use of the average radius of curvature of the nanostar tips instead of the average radius as the nanostar dimension of interest increases the accuracy with which experimentally observed nanoparticle behavior can be modeled theoretically. This prediction was validated by measuring time-dependent localized surface plasmon resonance (LSPR) spectra of gold nanostars suspended in solutions with different ionic strengths. Minimum energy barriers calculated from collision theory as a function of nanoparticle concentration were utilized to make kinetic predictions. All in all, these studies suggest that choosing the appropriate gold nanostar dimension is crucial to fully understanding and accurately predicting the stability of anisotropic nanostructures such as gold nanostars; i.e., whether the nanostructures remain stable and can be used reproducibly, or whether they aggregate and exhibit inconsistent results. Thus, the present work provides a deeper understanding of internanoparticle interactions in solution and is expected to lead to more consistent and efficient analytical and bioanalytical applications of these important materials in the future. Graphical abstract ᅟ.

PubMed ID: 29748758 Exiting the NIEHS site

MeSH Terms: No MeSH terms associated with this publication

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