arXiv subjects

François Cadiou

Publications and source records attributed to François Cadiou.

3 recordsLinked to original sources

arXiv2026

AI-Driven Phase Identification from X-ray Hyperspectral Imaging of cycled Na-ion Cathode Materials

Na-ion batteries have emerged as viable candidates for large-scale energy storage applica- tions due to resource abundance and cost advantages. The constraints imposed on their performance and durability, for instance, by complex phase transformations in positive electrode materials during electrochemical cycling, can be addressed and are thus not detrimental to their development. However, diffusion-limited Na-ion transport can drive spatially heterogeneous phase nucleation and propagation, leading to multiphase coexis- tence and locally non-uniform electrochemical activity, generating complex reaction path- ways that challenge both mechanistic understanding and predictive material optimization. These challenges can be addressed by investigating single-crystalline regions of materials, i.e. down to the scale of individual particles, although such analyses are often constrained by energetically and/or spatially sparse hyperspectral datasets. Here, we developed an AI-driven method to process hyperspectral data under sparse sampling conditions and generate multiphase maps with nanometer-scale resolution over a micrometer-scale field of view. We applied this processing on scanning transmission X-ray microscopy (STXM) data to determine the distribution and coexistence of phases in individual particles of NaxV2(PO4)2F3 cathode materials, at different states of charge. The methodology relies on a workflow which combines a Gaussian mixture variational autoencoder (GMVAE) algorithm with the Pearson corre- lation coefficient to identify the sodium content and map their spatial distribution. Our approach reveals nanoscale phase heterogeneity and evolution within individual particles, and improves the reliability of phase detection by identifying ambiguity zones, false assign- ments, and transition phases localized at grain boundaries.

cond-mat.mtrl-sci↗

arXiv2026

A large scale multi-modal workflow for battery characterization: from concept to implementation

The development of material acceleration platforms in battery research requires integrating complementary techniques and correlating heterogeneous experimental datasets. Here, this challenge is tackled in a large-scale multimodal program involving fifteen laboratories and facilities across Europe. Coordinated multi-site experiments are performed on state-of-the-art graphite / LiNiO2 Li-ion full cells to address two archetypal scientific questions: is the electrolyte composition impacting electrode properties, and how do electrode materials evolve when cells are cycled to their end-of-life? A fully standardized and centralized workflow is demonstrated, from sample production and delivery, to metadata and data handling, generating seventy-five concatenated datasets shared among all partners. Their integrated analysis shows that scientific conclusions depend critically on both the observable chosen to describe electrode properties, and the measurement technique employed. Individual experiments provide detailed information into specific aspects, such as crystal structures, redox activity, surface processes, morphology, etc., but can also function as binary diagnostic tool. Two-dimensional observable-technique patterns are introduced, in which each pixel encodes a yes, no or uncertain answer to a given scientific question. These patterns serve as multi-property metaviews, e.g. visual genotypes, enabling to classify material behavior and technique suitability according to predefined user demand and criteria, highlighting the interdependencies between measurement choices, extracted parameters and scientific interpretation. This multimodal workflow establishes a proof-of-concept for correlative analysis and underscores challenges toward fully integrated, automated and holistic approaches in energy material science.

physics.app-ph↗

arXiv2022

Morphological Evolution of NMC Secondary Particles Through in situ electrochemical FIB/SEM experiment

Microstructural evolution of NMC secondary particles during the battery operation drives the electrochemical performance and impacts the Li-ion battery lifetime. In this work, we develop an in situ methodology using the FIB/SEM instrument to cycle single secondary particles of NMC active materials while following the modifications of their 3D morphology. Two types of secondary particles, i.e. low and high gradient NMC, were studied alongside morphological investigations in both pristine state and different number of cycles. The quantification of initial inner porosity and cracking evolution upon electrochemical cycling reveals a clear divergence depending on the type of gradient particles. An unexpected enhancement of the discharge capacity is observed during the first cycles concurrently to the appearance of inner cracks. At the first stages, impedance spectroscopy shows a charge transfer resistance reduction that suggests a widening of the crack network connected to the surface, which leads to an increase of contact area between liquid electrolyte and NMC particle. 3D microstructure of individual secondary particles after in situ cycles were investigated using FIB/SEM and nano-XCT. The results suggest a strong impact of the initial porosity shape on the degradation rate.

physics.chem-ph↗