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Information Entropy as a Reliable Measure of Nanoparticle Dispersity.

ABSTRACT: Nanoparticle size impacts properties vital to applications ranging from drug delivery to diagnostics and catalysis. As such, evaluating nanoparticle size dispersity is of fundamental importance. Conventional approaches, such as standard deviation, usually require the nanoparticle population to follow a known distribution and are ill-equipped to deal with highly poly- or heterodisperse populations. Herein, we propose the use of information entropy as an alternative and assumption-free method for describing nanoparticle size distributions. This measure works equally well for mono-, poly-, and heterodisperse populations and represents an unbiased route to evaluation and optimization of nanoparticle synthesis. We provide intuitive software tools for analysis and supply guidelines for interpretation with respect to known standards.

SUBMITTER: Mac Fhionnlaoich N

PROVIDER: S-EPMC7304839 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Information Entropy as a Reliable Measure of Nanoparticle Dispersity.

Mac Fhionnlaoich Niamh N Guldin Stefan S

Chemistry of materials : a publication of the American Chemical Society 20200413 9

Nanoparticle size impacts properties vital to applications ranging from drug delivery to diagnostics and catalysis. As such, evaluating nanoparticle size dispersity is of fundamental importance. Conventional approaches, such as standard deviation, usually require the nanoparticle population to follow a known distribution and are ill-equipped to deal with highly poly- or heterodisperse populations. Herein, we propose the use of information entropy as an alternative and assumption-free method for ...[more]

PMID: 32581425

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