ArticlePatterns (New York, N.Y.)2022
Multivariate hyperspectral data analytics across length scales to probe compositional, phase, and strain heterogeneities in electrode materials.
Article in Patterns (New York, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Alkali-Metal Interlocking of 2D VJournal of the American Chemical Society · 2026Article
- Single Crystals of Vanadium Oxides as a Lens for Understanding Structural and Electronic Phase Transformations, Ion Transport, Chemo-Mechanical Coupling, and Electrothermal Neuronal Emulation.Chemical reviews · 2025Review
- Atomistic Origins of Conductance Switching in an ε-CuJournal of the American Chemical Society · 2024Article
- Chemomechanical damage prediction from phase-field simulation video sequences using a deep-learning-based methodology.iScience · 2024Article
- Chemistry-mechanics-geometry coupling in positive electrode materials: a scale-bridging perspective for mitigating degradation in lithium-ion batteries through materials design.Chemical science · 2023Review
- Machine learning accelerates identification of lithiated phases in X-ray images of battery hosts.Patterns (New York, N.Y.) · 2022Article
- Data science enables X-ray vision.Patterns (New York, N.Y.) · 2022Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The origins of performance degradation in batteries can be traced to atomistic phenomena, accumulated at mesoscale dimensions, and compounded up to the level of electrode architectures. Hyperspectral X-ray spectromicroscopy techniques allow for the mapping of compositional variations, and phase separation across length scales with high spatial and energy resolution. We demonstrate the design of workflows combining singular value decomposition, principal-component analysis, k-means clustering, and linear combination fitting, in conjunction with a curated spectral database, to develop high-accuracy quantitative compositional maps of the effective depth of discharge across individual positive electrode particles and ensembles of particles. Using curated reference spectra, accurate and quantitative mapping of inter- and intraparticle compositional heterogeneities, phase separation, and stress gradients is achieved for a canonical phase-transforming positive electrode material, α-V
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Registered trials
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