Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu +5 more
wiley +1 more source
A novel Ti/TiAl laminated composite with excellent shear properties. [PDF]
Chen Z +5 more
europepmc +1 more source
A Quantitative Lithium Inventory Framework for Anode‐Free Lithium Metal Batteries
A component‐resolved lithium inventory framework quantitatively tracks Li redistribution across the cell in anode‐free NMC622||Cu pouch cells throughout cycling. Three sequential degradation stages are identified: formation‐driven cathode Li depletion, midlife inactive Li0 accumulation, and late‐stage runaway SEI thickening. The cathode, as the sole Li
Wurigumula Bao +9 more
wiley +1 more source
Efficient detection of deformation-induced microstructural modifications in polycrystalline micropillars using scanning X-ray nanodiffraction. [PDF]
Davydok A, Singh K, Rout SS, Krywka C.
europepmc +1 more source
Calendering‐Dependent Electrochemical and Cost‐Energy Tradeoffs in Layered – Olivine Blend Cathodes
Blends comprised of LiNi0.9Mn0.05Co0.05O2 (NMC) and LiMn0.7Fe0.3PO4 (LMFP) are investigated to assess the performance – cost tradeoffs. Their rate‐capability benefit is retained only under uncalendered‐to‐moderately calendered states. Although blends reduce voltage decay and improve energy retention, they do not deliver measureable improvement in ...
Huyen T. K. Nguyen, Arumugam Manthiram
wiley +1 more source
Prediction of Final Rolling Temperature for TiAl Alloy Hot Rolling Based on Machine Learning. [PDF]
Lian W, Du F, Pei Q.
europepmc +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Sustainable Materials for Energy. [PDF]
Agresti F +33 more
europepmc +1 more source
Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh +3 more
wiley +1 more source
Design of CoNiCrFeCu-xSc High-Entropy Alloy Fillers for Braze-Welding of WC-Co to Steel. [PDF]
Xu P, Sun S, Li B, Li L.
europepmc +1 more source

