Results 81 to 90 of about 1,498,610 (256)

Investigating the Mechanism of Ion Concentration Polarization Within Nanofluidic Hydrogel Membranes: Experiment and Simulation

Advanced Materials Interfaces, EarlyView.
Molecular dynamics simulations are employed to model ion concentration polarization (ICP) at the nanoscale, revealing fundamental electrokinetic behaviors that align with experimental observations. The study demonstrates how membrane charge, ionic strength, and electric fields affect ion localization and biomolecule trapping, providing mechanistic ...
Hiba Aljayyousi, Jongmin Kim, Serdal Kirmizialtin, Yong‐Ak Song   +3 more
wiley   +1 more source

Inverse Design of Highly Deformable Mechanical Metamaterial Based on Partitional Semi‐Random Optimization

Advanced Science, EarlyView.
This research presents a novel optimization method for the inverse design of flexible mechanical metamaterials, enhancing traditional strategies by evaluating deformation in subregions. Combining simulated annealing with a genetic algorithm, it improves design efficiency and enables customizable deformation paths.
Xueqing Cao, Zeang Zhao, Panding Wang, Shengyu Duan, Hongshuai Lei   +4 more
wiley   +1 more source

Machine‐Learning‐Assisted Understanding of Depth‐Dependent Thermal Conductivity in Lithium Niobate Induced by Point Defects

Advanced Electronic Materials, EarlyView.
Thermal conductivity, a fundamental property of lithium niobate, plays a pivotal role in determining its device performance. By integrating experiments with machine‐learning‐assisted simulations, this study demonstrates that oxygen vacancies induced by thermal reduction result in a pronounced suppression of thermal conductivity and a marked depth ...
Yunjia Bao, Tao Chen, Zhuo Miao, Weidong Zheng, Puqing Jiang, Kunfeng Chen, Ruiqiang Guo, Dongfeng Xue   +7 more
wiley   +1 more source

DSSY 비순응유한요소와 멀티스케일 방법에 대한 적용 [PDF]

, 2020
학위논문(박사)--서울대학교 대학원 :자연과학대학 수리과학부,2020. 2. 신동우.We first consider nonparametric DSSY nonconforming quadrilateral element introduced. The element satisfies the mean value property on each edge and shows optimal convergence for second-order elliptic ...
조강훈
core  

Designing Memristive Materials for Artificial Dynamic Intelligence

Advanced Intelligent Discovery, EarlyView.
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley   +1 more source

Generalized Multiscale Finite Element Methods with energy minimizing oversampling

International Journal for Numerical Methods in Engineering, 2018
SummaryIn this paper, we propose a general concept for constructing multiscale basis functions within Generalized Multiscale Finite Element Method, which uses oversampling and stable decomposition. The oversampling refers to using larger regions in constructing multiscale basis functions and stable decomposition allows estimating the local errors.
Eric Chung, Yalchin Efendiev, Wing Tat Leung   +2 more
openaire   +3 more sources

Harnessing Deep Learning of Point Clouds for Morphology Mimicking of Universal 3D Shape‐Morphing Devices

Advanced Intelligent Systems, EarlyView.
Soft robots capable of morphing into various 3D shapes are crucial for applications like human‐machine interfaces and biological manipulation. However, controlling 3D shape‐morphing robots with soft actuators remains a challenge. This work introduces a machine learning model that maps complex 3D deformations to control inputs, enabling robots to mimic ...
Jue Wang, Dhirodaatto Sarkar, Jiaqi Suo, Alex Chortos   +3 more
wiley   +1 more source

Constraint energy minimization generalized multiscale finite element method in mixed formulation for parabolic equations [PDF]

arXiv, 2020
In this paper, we develop the constraint energy minimization generalized multiscale finite element method (CEM-GMsFEM) in mixed formulation applied to parabolic equations with heterogeneous diffusion coefficients. The construction of the method is based on two multiscale spaces: pressure multiscale space and velocity multiscale space.
arxiv  

Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media [PDF]

, 2014
It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very
arxiv   +1 more source

Applied Artificial Intelligence in Materials Science and Material Design

Advanced Intelligent Systems, EarlyView.
AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material ...
Emigdio Chávez‐Angel, Martin Børstad Eriksen, Alejandro Castro‐Alvarez, Jose H. Garcia, Marc Botifoll, Oscar Avalos‐Ovando, Jordi Arbiol, Aitor Mugarza   +7 more
wiley   +1 more source