Results 211 to 220 of about 386,741 (313)

THE LOON WING [PDF]

open access: yesEvolution, 1958
openaire   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

open access: yesAdvanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan   +12 more
wiley   +1 more source

Permissive and instructive <i>Hox</i> codes govern limb positioning. [PDF]

open access: yesElife
Wang Y   +19 more
europepmc   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

open access: yesAdvanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park   +19 more
wiley   +1 more source

A Highly Hydrophilic Air Electrode With Water‐Induced Surface Reconstruction for Efficient Reversible Protonic Ceramic Cell at Low Water Partial Pressures

open access: yesAdvanced Energy Materials, EarlyView.
This work demonstrates a new strategy for reversible protonic ceramic cells (R‐PCCs). By developing highly hydrophilic oxides, efficient operation is achieved under low water vapor pressures while maintaining high performance and stability. This approach addresses the challenge of hydrogen production in freshwater‐scarce regions.
Nai Shi   +15 more
wiley   +1 more source

Mechanisms of Alkali Ionic Transport in Amorphous Oxyhalides Solid State Conductors

open access: yesAdvanced Energy Materials, EarlyView.
Large‐scale machine learning‐based molecular dynamics simulations are used to investigate isovalent amorphous oxyhalides, revealing a remarkable chemically independent ionic conductivity. A rigorous analysis of alkali residence times across different metal–anion environments identifies divalent anions as key diffusion bottlenecks.
Luca Binci   +3 more
wiley   +1 more source

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