Issue 45, 2023

Quantitative imaging methods for heterogeneous multi-component films

Abstract

The drying of multi-component dispersions is a common phenomenon in a variety of everyday applications, including coatings, inks, processed foods, and cosmetics. As the solvent evaporates, the different components may spontaneously segregate laterally and/or in depth, which can significantly impact the macroscopic properties of the dried film. To obtain a quantitative understanding of these processes, high-resolution analysis of segregation patterns is crucial. Yet, current state-of-the-art methods are limited to transparent, non-deformable labeled colloids, limiting their applicability. In this study, we employ three techniques that do not require customized samples, as their imaging contrast relies on intrinsic variations in the chemical nature of the constituent species: confocal Raman microscopy, cross-sectional Raman microscopy, and a combination of scanning electron microscopy and energy dispersive X-ray analysis (SEM–EDX). For broad accessibility, we offer a thorough guide to our experimental steps and data analysis methods. We benchmark the capabilities on a film that dries homogeneously at room temperature but exhibits distinct segregation features at elevated temperature, notably self-stratification, i.e., autonomous layer formation, due to a colloidal size mismatch. Confocal Raman microscopy offers a direct means to visualize structures in three dimensions without pre-treatment, its accuracy diminishes deeper within the film, making cross-sectional Raman imaging and SEM–EDX better options. The latter is the most elaborate method, yet we show that it can reveal the most subtle and small-scale microseparation of the two components in the lateral direction. This comparative study assists researchers in choosing and applying the most suitable technique to quantify structure formation in dried multi-component films.

Graphical abstract: Quantitative imaging methods for heterogeneous multi-component films

Supplementary files

Article information

Article type
Paper
Submitted
12 Sep 2023
Accepted
02 Nov 2023
First published
06 Nov 2023
This article is Open Access
Creative Commons BY license

Soft Matter, 2023,19, 8871-8881

Quantitative imaging methods for heterogeneous multi-component films

E. Hooiveld, M. Dols, J. van der Gucht, J. Sprakel and H. M. van der Kooij, Soft Matter, 2023, 19, 8871 DOI: 10.1039/D3SM01212C

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