Results 91 to 100 of about 13,453,555 (238)

Computational analysis of contamination in Kojima Lake using upwind-type finite element method [PDF]

open access: yes, 1998
We have computed the phase of spreading contaminations in Kojima Lake by using the upwind-type finite element method. We have treated the two cases: the pollutant flows from the Sasagase river and from the Kurashiki River.
Sasaki, Toru   +2 more
core   +1 more source

Generalized multiscale finite element methods for space–time heterogeneous parabolic equations

open access: yesComputers & Mathematics with Applications, 2018
In this paper, we consider local multiscale model reduction for problems with multiple scales in space and time. We developed our approaches within the framework of the Generalized Multiscale Finite Element Method (GMsFEM) using space-time coarse cells. The main idea of GMsFEM is to construct a local snapshot space and a local spectral decomposition in
Chung, Eric T.   +3 more
openaire   +5 more sources

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

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

Polymer Concepts in Cellular Function

open access: yes
Advanced Science, EarlyView.
Miao Yu   +7 more
wiley   +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

Convergence analysis of the generalized finite element method with global-local enrichments [PDF]

open access: yes, 2010
Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by William Ingram (wingram2@illinois.edu) on 2010-08-31T20:04:56Z Item is restricted until 2012-08-31T20:04:44ZItem reinstated by Sarah Shreeves (sshreeve@illinois.edu) on 2012-09 ...
Gupta, Varun
core  

Finite element heterogeneous multiscale methods for the wave equation [PDF]

open access: yes, 2013
Wave phenomena appear in a wide range of applications such as full-waveform seismic inversion, medical imaging, or composite materials. Often, they are modeled by the acoustic wave equation.
Stohrer, Christian
core   +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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