DOI: 10.3390/min16111122 ISSN: 2075-163X

Automated Nondestructive Quality and Purity Assessment of Natural Flake Graphite: A Perspective Review on Microstructural Integrity, Multimodal Microscopy, and AI-Driven Fusion

Rui Huang, Soo Siang Teoh, Hui Wang, Haidi Ibrahim

Natural flake graphite is a critical anode material for lithium-ion batteries, demanding both ultrahigh chemical purity and preserved large-flake microstructural integrity. However, conventional bulk assays (e.g., chemical titration and combustion) are destructive, time-lagged, and obscure localized impurity distributions. While commercial automated mineralogy systems (e.g., MLA and QEMSCAN) have long enabled routine modal analysis, their application to high-purity graphite is constrained by low backscattered electron contrast in light-element matrices, high detection limits, and an inability to quantify intra-flake mechanical cleavage damage. This perspective review conceptualizes an end-to-end, dual-track paradigm for nondestructive graphite quality screening that decouples microstructural damage evaluation from chemical impurity identification. First, we review the physicochemical baseline of low-temperature plasma modification via Raman and X-ray photoelectron spectroscopy to confirm bulk sp2 lattice preservation. Second, to quantify morphological degradation without conflating voids with mineral inclusions, we propose two mechanics-inspired geometric indicators—the Defect Area Ratio (DAR) and Structural Damage Index (SDI)—as segmentation targets for lightweight CNN–Transformer networks. Third, to resolve Z-contrast ambiguity and topographic noise during mid-stream purification screening (90.0–99.8 wt.% C), we outline the Spatial Image-Spectrum Transformation and Interactive Fusion Design (SISTIFD) framework, followed by a high-dimensional vector database roadmap and quantitative validation protocols.

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