Results 151 to 160 of about 9,903 (254)

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

Mode hybridisation strategies for subwavelength sound attenuation in miniaturised Helmholtz resonators. [PDF]

Sci Rep
Domingo-Roca R, Feeney A, Jackson-Camargo JC, Windmill JFC.   +3 more
europepmc   +1 more source

Challenges and enablers in fluidization technology

AIChE Journal, EarlyView.
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley   +1 more source

Wearable ultrasound: a review of core technologies and clinical applications in cardiovascular monitoring. [PDF]

Microsyst Nanoeng
Yan M, Wang Z, Li Z, Wang P, Wu P, Chen X, Chen X, Du L, Wang Y, Song J, Fang Z.   +10 more
europepmc   +1 more source

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

Advanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz, Gisya Abdi, Andrzej Sławek, Marlena Gryl, Konrad Szaciłowski   +4 more
wiley   +1 more source

Physics-based simulation of ultrasound propagation from MRI volumes for cross-modal breast imaging. [PDF]

J Biol Eng
Muthukumar A, Zapata I, Brooks A.
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced 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, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Smart Flexible Tactile Sensors: Recent Progress in Device Designs, Intelligent Algorithms, and Multidisciplinary Applications

Advanced Intelligent Discovery, EarlyView.
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang, Ming Dong, Rongrong Bao, Caofeng Pan   +3 more
wiley   +1 more source

Editorial for Special Issue "Research on Friction, Wear and Corrosion Properties of Materials". [PDF]

Materials (Basel)
Liu Y, Ma Y.
europepmc   +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