Mesoporous inorganic thin films are promising materials architectures for a variety of applications, including sensing, catalysis, protective coatings, energy generation and storage. In many cases, precise control over a bicontinuous...

2D colloidal assembly is a vital process in the fabrication of nanostructured devices and remains of widespread interest in fundamental research. Characterising the ordering is crucial to develop an understanding of the driving forces behind the assembly and to optimise processing conditions. Image analysis offers a direct evaluation pathway, typically via the radial distribution function or the 2D-fast Fourier transform. Both methods have inherent limitations; the former provides no angular dependence while the latter is challenged when confronted with imperfection on the mean size, spacing and coverage of the building blocks. Here, we introduce the 2D spatial distribution function (SDF) as an alternative pathway to evaluate colloidal ordering. We benchmark the method in case studies of prominent examples and provide a tool-kit for implementation, either as imageJ plugin or standalone software. Application and interpretation is straightforward and particularly powerful to analyse and compare colloidal assemblies with limited order. File list (3) download file view on ChemRxiv SDF_MacFhionnlaoich_et_al_submitted.pdf (1.36 MiB) download file view on ChemRxiv SI_SDF_MacFhionnlaoich_et_al_submitted.pdf (4.50 MiB) download file view on ChemRxiv SDF_PlugIn.zip (638.09 KiB)

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.

Thin-layer chromatography (TLC) is one of the basic analytical procedures in chemistry and allows the demonstration of various chemical principles in an educational setting. An often-overlooked aspect of TLC is the capability to quantify isolated target compounds in an unknown sample. Here, we present a suitable route to implement quantitative analysis in a lesson plan. We provide both a stand-alone software and an online webapp that allow students to obtain quantitative information from a developed TLC plate and present two suitable experiments, namely, the absorbance-based quantification of the colorant Sudan IV and the fluorescence-based quantification of rhodamine 6G, a fluorophore widely used in biotechnology. Students conduct TLC experiments following established protocols, take pictures of their TLC plates with mobile phones, and subsequently quantify the different compounds in the separate bands they observe.

A cross-method comparison for quasi-monodisperse, polydisperse and bimodal gold nanoparticles of 2–7 nm in diameter between conventional image analysis of transmission electron micrographs and small-angle X-ray scattering with form-free Monte Carlo fitting.