Results 81 to 90 of about 28,001 (222)

Bioinspired Hierarchical Architecture with Water Transport Channels for Strong Adhesion at the Sweating Interface

open access: yesAdvanced Science, EarlyView.
To address adhesion failure in sweaty epidermal electronics, this study proposes a cross‐species, multi‐scale biomimetic interface. By modeling staged wet adhesion, it integrates self‐regulating liquid bridges with directional drainage. This design ensures stable, high‐performance flexible sensing in complex physiological environments, offering a ...
Jieliang Zhao   +12 more
wiley   +1 more source

Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design

open access: yesAdvanced Science, EarlyView.
ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang   +15 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

Online conservative generalized multiscale finite element method for flow models

open access: yes, 2020
In this paper, we consider an online enrichment procedure using the Generalized Multiscale Finite Element Method (GMsFEM) in the context of a two-phase flow model in heterogeneous porous media. The coefficient of the elliptic equation is referred to as the permeability and is the main source of heterogeneity within the model.
Wang, Yiran   +3 more
openaire   +2 more sources

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

open access: yesAdvanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian   +12 more
wiley   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong   +5 more
wiley   +1 more source

Adaptive ACMS: A robust localized Approximated Component Mode Synthesis Method

open access: yes, 2017
We consider finite element methods of multiscale type to approximate solutions for two-dimensional symmetric elliptic partial differential equations with heterogeneous $L^\infty$ coefficients.
Madureira, Alexandre L., Sarkis, Marcus
core  

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

open access: yesAdvanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin   +4 more
wiley   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan   +3 more
wiley   +1 more source

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