Results 231 to 240 of about 144,259 (309)

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

Research on the influence of loading rate on the dynamic initiation fracture toughness of CMDB propellant. [PDF]

Sci Rep
Zheng J, Wu X, Sun Z, Guo Z, Zhang M, Chen X.   +5 more
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

Fracture Toughness of Winding Carbon Plastics Based on Epoxy Matrices and Reinforced by Polysulfone Film. [PDF]

Polymers (Basel)
Dzhangurazov EB, Petrova TV, Shapagin AV, Tretyakov IV, Korokhin RA, Kireynov AV, Alexeeva OV, Solodilov VI, Yurkov GY, Berlin AA.   +9 more
europepmc   +1 more source

Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles

Advanced Intelligent Systems, EarlyView.
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov, Hanzhi Ma, Junbo Peng, Huifeng Dong, Jiangshan Zhuo, Mengke Shi, Lvting Wang, Shengchao Jiang, Ye Shi   +8 more
wiley   +1 more source

Artificial Intelligence in Autonomous Mobile Robot Navigation: From Classical Approaches to Intelligent Adaptation

Advanced Intelligent Systems, EarlyView.
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella, Angelo Cardellicchio, Cosimo Patruno, Massimiliano Nitti, Nicola Pedrocchi, Vito Renò   +5 more
wiley   +1 more source

Covalent Network Formation Rate Controls Depletion‐Induced Supramolecular Assembly in Hybrid Double Network Hydrogels

Angewandte Chemie, EarlyView.
Tuning the rate of covalent network formation in hybrid double network hydrogels regulates whether supramolecular filaments retain their low‐nm structures or depletion‐induced supramolecular assembly takes place forming bundles. This kinetic handle programs the mesoscale architecture and toughness of the hydrogels, establishing a link between ...
Mertcan Özel, Sebastian Novosedlik, Tingxian Liu, Lucía López‐Gandul, Heleen Duijs, Hari Veera Prasad Thelu, Ciqing Tong, Roxanne E. Kieltyka   +7 more
wiley   +2 more sources

Low-Velocity Impact Analysis in Composite Plates Incorporating Experimental Interlaminar Fracture Toughness. [PDF]

Materials (Basel)
Lee GH, Yang JY, Kim SW, Lee SY.
europepmc   +1 more source

Natural Aging of Biomaterials in Ambient and Physiological Environments

Advanced NanoBiomed Research, EarlyView.
Biomaterials used in biomedical applications can change their physical properties over time, even under ambient and physiological conditions. This review highlights key studies on the natural aging of materials ranging from soft hydrogels to metals and ceramics, emphasizing how time‐dependent changes influence function and performance.
Shuyu Zhang, Anne E. Staples
wiley   +1 more source

Enhancing Fracture Toughness of Dental Zirconia through Incorporation of Nb into the Surface. [PDF]

Materials (Basel)
Ban S, Yasuoka Y.
europepmc   +1 more source