New method for a SEM-based quantitative microstructural clay analysis - MiCA

• Published in: Applied clay science Vol. 214; p. 106248
• Main Authors: Di Remigio, G., Rocchi, I., Zania, V.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.11.2021
• Subjects: Clay particles orientation; Clay porosity; Computer vision; Image analysis; Quantitative analysis; SEM; Computer vision; Image analysis; SEM; Clay particles orientation; Clay porosity; Quantitative analysis
• ISSN: 0169-1317; 1872-9053
• DOI: 10.1016/j.clay.2021.106248

The soil microstructure is recognised to strongly influence the mechanical behaviour of both coarse and fine geomaterials. Proper identification and tracking of the shape and position of the particles has become more and more critical to form a link between the micro and macro behaviour. Scanning Electron Microscopy (SEM) has been widely used in the last decades to study the clay fabric variation with its mechanical behaviour and physical properties. However, the particles orientation has so far been discussed only from a qualitative point of view due to the lack of updated, automatised quantification tools. Consequently, developing constitutive models that correlate the soil micro structure to its mechanical behaviour is not feasible. In order to make a step forward in this direction, an Image Analysis based code called MiCA (microstructural clay analyser) capable of quantifying the particle orientation and the porosity of clay samples through the analysis of SEM micrographs was developed in this study. The code reliability was first validated through the application to geometrical reference patterns, then to textbook micrographs illustrating typical clay fabrics (dispersed, honeycomb, flocculated and aggregated), and finally to high quality images. MiCA showed good accuracy in the results obtained, regardless of the number of lines in the image, the complexity of the geometrical shapes and the pixel size of the analysed graphs. Therefore, MiCA can be considered suitable for quantitative analysis of the particle orientation and/or pores shape in clay materials. •Quantification of clay microstructural features via a Computer Vision based code•The code quantifies the clay particles orientation and the porosity characteristics.•The results were validated against geometrical patterns and literature clay images.•The identified microstructural parameters show high accuracy and reliability.