Abstract
Macroscopic phenomena, such as fracture, corrosion, and degradation of materials, are associated with various reactions which progress heterogeneously. Thus, material properties are generally determined not by their averaged characteristics but by specific features in heterogeneity (or ‘trigger sites’) of phases, chemical states, etc., where the key reactions that dictate macroscopic properties initiate and propagate. Therefore, the identification of trigger sites is crucial for controlling macroscopic properties. However, this is a challenging task. Previous studies have attempted to identify trigger sites based on the knowledge of materials science derived from experimental data (‘empirical approach’). However, this approach becomes impractical when little is known about the reaction or when large multi-dimensional datasets, such as those with multiscale heterogeneities in time and/or space, are considered. Here, we introduce a new persistent homology approach for identifying trigger sites and apply it to the heterogeneous reduction of iron ore sinters. Four types of trigger sites, ‘hourglass’-shaped calcium ferrites and ‘island’- shaped iron oxides, were determined to initiate crack formation using only mapping data depicting the heterogeneities of phases and cracks without prior mechanistic information. The identification of these trigger sites can provide a design rule for reducing mechanical degradation during reduction.
Highlights
Trigger sites are specific regions or features of heterogeneity in a material where key reactions initiate and take place in systems
Once we accurately describe the evolution of chemical states and microstructures during reduction, machine learning can be used to identify the trigger sites of crack formation caused by their evolution
The iron oxide states (Fe(III) and Fe(II)) and oxide phases in samples corresponding to different stages of the reduction process were mapped in two dimensions using X-ray absorption near-edge structure (XANES) and X-CT measurements
Summary
Trigger sites are specific regions or features of heterogeneity in a material where key reactions initiate and take place in systems. Fundamental materials-science notions such as dislocation theory and micromechanics are used to analyse these microscopic data and empirically identify the trigger sites These empirical approaches become impractical in more complicated systems such as composite materials (e.g. iron ore sinters and carbon fibre reinforced plastics (CFRP)), batteries, and catalysts, where the heterogeneity of the microstructure and/or chemical states are substantially different depending on their locations in a material, and the features evolve during a period of www.nature.com/scientificreports/. The identification of trigger sites using conventional computational techniques such as finite-element methods to calculate the stress field[7,8] is not a feasible option This is because such calculations require parameters such as the Young’s moduli and Poisson’s ratios of all phases as well as the details of the microstructure, and both change from their initial values according to the progress of the process. A key contribution towards this goal may come from topological data analysis[16,17]
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