Electronic modulation with high-valence metal doping towards high-rate Na4Fe3(PO4)2P2O7 cathode in sodium-ion batteries.

Preparation and properties of short blade sodium ion batteries with Mg/Ti Co-Doped P2-type cathode materials

Organically modified NbSe2 as cathode material for magnesium-lithium hybrid batteries

The toxicity differences of lithium-ion battery cathode materials, lithium iron phosphate (LFP) and lithium cobalt oxide (LCO) to zebrafish(Danio rerio): Mechanisms and environmental impacts.

A Bacillus mucilaginosus - ascorbic acid synergistic leaching system for selective lithium recovery from lithium iron phosphate.

Mechanistic insight into the coupled influence of electrolyte and cathode materials on the thermal stability of nickel-rich lithium-ion batteries

A novel strategy of bulk-surface Al/Ti continuous modification for improving structural stability and electrochemical performance of ultra-high-nickel cathode materials

Engineered hollow cubic structures CoS/NiS heterojunctions enable high-performance magnesium-ion batteries.

Advancing direct recycling of lithium-ion batteries: An efficient recovery of NMC cathode particles using high-intensity magnetic separation.

Synthesis of LiNi0.6Mn0.3Co0.1O2 (NMC 631) cathode materials using co-precipitation method: Study on the effect of calcination temperature and Li excess on structural properties

Construction of NiS/(Fe, Ni)S2 composite as cathode material for high-temperature thermal batteries

Single-crystal layer-structured metal oxide cathode material for high-voltage sodium ion batteries

Salt-triggered electroactive dressing with controlled drug release for enhanced healing of exudative wounds.

Regulating oxygen vacancies and electron localization density to construct ultra-low strain Fe-Mn-based layered oxide cathode materials

Synergistic optimization of ion migration and electron transfer in sodium-ion battery cathode materials

Ag-doped BaCo0.4Fe0.4Zr0.1Y0.1O3-δ as a promising cathode material for proton-conducting solid oxide fuel cells

High-rate and long-cycling P2-type cathode material for sodium-ion batteries

Upcycling of degraded LiFePO4 into next-generation phosphate-based cathode materials via solid-state redox and lattice reconstruction

Degradation of the cathode catalyst layer (CCL) limits the durability of polymer electrolyte membrane fuel cells (PEMFCs) by reducing the electrochemically active surface area and impairing oxygen transport. These co-occurring effects are difficult to disentangle with standard electrochemical diagnostics. In this study, we used impedance-based analysis to quantify the individual contributions of catalyst and carbon support degradation in PEMFCs subjected to accelerated stress tests (ASTs): low-potential cycling (0.6–0.95 V, 55 000 cycles) and high-potential cycling (1.0–1.5 V, 50 000 cycles). In-operando electrochemical impedance spectroscopy under H 2 /air and impedance data analysis using the distribution of relaxation times and transmission line modeling were combined with complementary diagnostic techniques. This approach separated the ohmic, charge transfer, CCL ionomer, and mass transport resistances and tracked their evolution during ASTs. Low-potential cycling increased the charge transfer resistance by 29–56%, consistent with a loss of active surface area. High-potential cycling resulted in increased charge transfer, mass transport, and ohmic resistances, with a 77% reduction in CCL thickness, indicating severe carbon corrosion and collapse of the CCL structure. The resulting framework provides a practical tool to screen cathode materials and operating strategies by quantitatively linking specific degradation modes to electrochemical loss processes. • In-operando EIS with DRT separates kinetic, ionomer, and mass transport losses. • TLM quantifies charge transfer, ionomer and mass transport resistances during ASTs. • Low-potential cycling primarily raises kinetic losses consistent with ECSA loss. • High-potential cycling raises kinetic/transport losses due to structural degradation. • Ex-situ diagnostics validate impedance-derived resistance evolution and mechanisms.

A deep learning model is employed to address the challenging problem of V 2 O 5 nanoparticle segmentation and the correlation between the chemical composition and the geometrical features of lithiated V 2 O 5 nanoparticles as an exemplar of a phase-transforming battery cathode material. First, the deep learning-enabled segmentation model is integrated with the singular value decomposition technique and a spectral database to generate accurate composition and phase maps capturing lithiation heterogeneities as imaged using scanning transmission X-ray microscopy. These phase maps act as the output properties for correlation analysis. Subsequently, the quantitative influences of the geometrical features of nanoparticles such as the particle size (i.e., projected perimeter and area), the aspect ratio, circularity, convexity, and orientation on the lithiation phase maps are revealed. These findings inform strategies to improve lithiation uniformity and reduce stress in phase-transforming lithium battery materials via optimized particle geometry. • Achieved nanoparticle segmentation in STXM data using a deep learning model. • Generated particle-wise lithiation composition maps from spectral deconvolution. • Revealed strong correlations between particle geometries and lithiation features. • Provided insights into electrode performance enhancement via structural design.