Results 201 to 210 of about 347,004 (298)

Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries

open access: yesAdvanced Energy Materials, EarlyView.
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 Quantitative Lithium Inventory Framework for Anode‐Free Lithium Metal Batteries

open access: yesAdvanced Energy Materials, EarlyView.
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

Calendering‐Dependent Electrochemical and Cost‐Energy Tradeoffs in Layered – Olivine Blend Cathodes

open access: yesAdvanced Energy Materials, EarlyView.
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

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
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]

open access: yesNanomaterials (Basel)
Agresti F   +33 more
europepmc   +1 more source

Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

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