Results 131 to 140 of about 19,277,069 (274)

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

open access: yesAdvanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali   +3 more
wiley   +1 more source

Finite difference method and finite volume method for solving navier-stokes equation in sea water movement [PDF]

open access: yes, 2013
This project proposed the Navier-Stokes equation of sea water modeling. The mathematical modeling consists of momentum , heat and salinity equations. The three parameters influence on sea water movement are momentum, temperature and salinity.
Mohamed, Nur Syahida
core  

Degradation Pathways of Silicon‐Based Anodes in Lithium‐Ion Batteries

open access: yesAdvanced Energy Materials, EarlyView.
Silicon‐based anodes undergo degradation through five primary pathways: (1) mechanical and structural deterioration of the active material, (2) loss of electrode integrity and electrical contact, (3) mechanical instability of the solid electrolyte interphase (SEI), characterized by repetitive fracture and deformation, (4) chemical instability of the ...
Yoon Jeong Choi   +3 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

open access: yesAdvanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen   +4 more
wiley   +1 more source

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 control volume-based finite element method for plane micropolar elasticity [PDF]

open access: yes, 2008
This paper describes the development of a numerical procedure for predicting deformations and stresses in a loaded two-dimensional membrane exhibiting micropolar or Cosserat constitutive behaviour. The procedure employs a conventional finite element (FE)
Wheel, M.A.
core  

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

Redesigning Interlayers for Anode‐Free Batteries: Harnessing Continuity and Metal Inventory

open access: yesAdvanced Energy Materials, EarlyView.
Interlayers for anode‐free batteries must provide continuous interfacial coverage while remaining thin enough to preserve the finite cathode‐derived active‐metal inventory. This Perspective couples thin‐film closure with stoichiometric active‐metal consumption to reveal practical design windows across chemistry, substrate roughness, cathode loading ...
Rosalía Cid, Lorenzo Fallarino
wiley   +1 more source

From Top to Bottom: Manufacturing Process‐Context Aware Resolution of Energy Device Electrodes Through a 3D Diffusion Generative Model

open access: yesAdvanced Energy Materials, EarlyView.
The application of a generative diffusion model, enhanced with a training data augmentation pipeline retaining the manufacturing process context of electrode microstructures, leads to improved fidelity of the through‐plane tortuosity factor in the AI generated samples.
Victor Ramirez‐Camacho   +5 more
wiley   +1 more source

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