Results 151 to 160 of about 127,737 (299)

Dynamic crushing and energy absorption of bio-inspired shear thickening fluid-filled origami metastructure

Engineering structures
Lalin Lam, Wensu Chen, Hong Hao, Zhejian Li   +3 more
semanticscholar   +1 more source

Surface Energy Modulated Self‐Assembly of Percolative Gallium Nanodroplet Films for Stretchable Electronics

Advanced Electronic Materials, EarlyView.
Surface‐energy guided self‐assembly of liquid metals enables the transformation of liquid metal micro/nanodroplets into continuous perocolative films on elastomeric substrates. By tailoring interfacial energetics and wetting behavior, uniform, conductive, and stretchable films are achieved, offering scalable pathways for high‐performance soft ...
Alwar Samy Ramasamy, Gayatri Subhalaxmi, Sneha Banerjee, Mark Vailshery, Renu Raman Sahu, Sivakumar K.S, Ajisha Chathyattu, Tapajyoti Das Gupta   +7 more
wiley   +1 more source

Intrinsic Mechanical Parameters and their Characterization in Solid‐State Lithium Batteries

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
This review focuses on the intrinsic mechanical parameters and their associated characterization in solid‐state batteries. The physical significance of mechanics parameters is introduced with exhaustive classifications by elastic, plastic deformations and fracture in bulk, adhesion, friction at interfaces, and mechanical fatigue in cells ...
Shuai Hao, Qianyi Zhang, Xiangkang Kong, Zhaoxiang Wang, Xue‐Ping Gao, Paul R. Shearing   +5 more
wiley   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Solid particles focusing, orienting, and de‐focusing in planar Poiseuille flow

AIChE Journal, EarlyView.
Abstract Three‐dimensional, time‐dependent lattice‐Boltzmann simulations of neutrally buoyant particles in planar Poiseuille flow have been performed. The particles are spherical or cylindrical (the latter with a length over diameter ratios in the range 1/3 to 2) and have volume fraction ranging from virtually zero (one particle) to 0.15. The channel's
J. J. Derksen
wiley   +1 more source

Dynamic responses of shear thickening fluid-filled lattice structures

International Journal of Impact Engineering
Qifang Hu, Guoxing Lu, K. Tse
semanticscholar   +1 more source

A Computational Approach for Biomimetic Design of Liver‐On‐A‐Chip

Advanced Intelligent Discovery, EarlyView.
A biomimetic liver‐on‐a‐chip with antiparallel perfusion was designed using COMSOL‐guided simulation to replicate hepatic acinus transport. Full‐scale modelling revealed diffusion‐dominated, length‐dependent nutrient gradients and low‐shear conditions.
Zhenxu Yang, Qiankun Yin, Qingxin Liu, Zhejun Xu, Ye Zhang, Christopher Vega‐Sánchez, Xiaochen Liu, Daniele Vigolo, Jiao Jiao Li, Ken‐Tye Yong   +9 more
wiley   +1 more source

Design of shear thickening fluid/polyurethane foam skeleton sandwich composite based on non-Newtonian fluid solid interaction under low-velocity impact

Materials & Design (1980-2015), 2021
F. Zhao, Liwei Wu, Zhenqian Lu, Jia‐Horng Lin, Q. Jiang   +4 more
semanticscholar   +1 more source

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source