Nanoscience

Information Entropy as a Reliable Measure of Nanoparticle Dispersity

Authors

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 illequipped 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 approach works equally well for mono-, poly- and heterodisperse populations and provides an unbiased route to evaluation and optimisation of nanoparticle synthesis. We provide an intuitive tool for analysis with a user-friendly macro and provide guidelines for interpretation with respect to known standards.

Version notes

Version 1 pre-submission for peer review.

Content

Thumbnail image of MacFhionnlaoich et al_Information entropy for nanoparticle dispersity_Manuscript.pdf

Supplementary material

Thumbnail image of MacFhionnlaoich et al_Information entropy for nanoparticle dispersity_SI.pdf
MacFhionnlaoich et al Information entropy for nanoparticle dispersity SI
Thumbnail image of MacFhionnlaoich et al_Information entropy for nanoparticle dispersity_Macro.zip
MacFhionnlaoich et al Information entropy for nanoparticle dispersity Macro