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

