Results 121 to 130 of about 28,102 (266)

Sulfide‐Based Electrolytes for All‐Solid‐State Sodium Batteries

Advanced Energy Materials, EarlyView.
This review covers the structural features and synthesis strategies of sulfide‐based solid electrolytes, as well as critical challenges related to conductivity, interfacial and moisture stability, and scaling‐up for practical application in Sodium‐based All Solid‐State Batteries.
Han Yang, Luca Weckelmann, Baolin Wu, Chih‐Long Tsai, Luc Raijmakers, Rüdiger‐A. Eichel, Anna Windmüller   +6 more
wiley   +1 more source

Role of Wadsley Defects and Cation Disorder to Enhance MoNb12O33 Diffusion

Advanced Energy Materials, EarlyView.
Wadsley‐Roth niobates are high‐rate capable and durable anode materials for lithium‐ion batteries. Defect‐tailoring of MoNb12O33 is shown to substantially enhance lithium diffusion. Computational models were used to separate the effects of cation disorder and Wadsley defects to identify that both led to the occupation of fast diffusion sites at lower ...
CJ Sturgill, Manish Kumar, Nima Karimitari, Iva Milisavljevic, Coby S. Collins, Aaron Hegler, Hsin‐Yun Joy Chao, Santosh Kiran Balijepalli, Scott T. Misture, Christopher Sutton, Morgan Stefik   +10 more
wiley   +1 more source

Large phase-shifting channel spacing phased array antenna with triangular grid

Tongxin xuebao
Phased arrays with large channel spacing could reduce costs and improve compatibility, but they significantly limit scanning performance. A phased array antenna with a channel spacing of λ0 was designed.
PAN Yangyi, HUANG Zhicheng, LIAO Shaowei
doaj  

Reconfiguration of labeled matchings in triangular grid graphs

This paper introduces a new reconfiguration problem of matchings in a triangular grid graph. In this problem, we are given a nearly perfect matching in which each matching edge is labeled, and aim to transform it to a target matching by sliding edges one by one. This problem is motivated to investigate the solvability of a sliding-block puzzle called ``
Kakimura, Naonori, Mishima, Yuta
openaire   +4 more sources

Universal Oxychlorination Strategy in Halide Solid Electrolytes for All‐Solid‐State Batteries

Advanced Energy Materials, EarlyView.
A WO2Cl2‐driven oxychlorination strategy enables bulk oxygen incorporation into close‐packed LixMCl6 (M = Zr, Y, Er, In) halide lattices. Oxygen is selectively anchored by W6+ as lattice‐integrated [WO2Cl4]2− units, regulating the anionic framework, diversifying Li coordination, and weakening Li–Cl interactions.
Jae‐Seung Kim, Heeju Park, Hae‐Yong Kim, Eunryeol Lee, Heewon Kim, Soeul Lee, Jinyeong Choe, Jiwon Seo, Hyeon‐Jong Lee, Hojoon Kim, Jemin Yeon, Yoon Seok Jung, Kyung‐Wan Nam, Dong‐Hwa Seo   +13 more
wiley   +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

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 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

Preferential sacral fracture sites in fragility fractures of the pelvis type IVb and comparison of internal fixation methods: CT-based morphological mapping and finite element analysis. [PDF]

Eur J Trauma Emerg Surg
Naniwa S, Yorimitsu M, Hasegawa T, Ando T, Okuda R, Fukuoka S, Mochizuki Y, Yamakawa Y, Nakahara R, Hanakawa S, Ozaki T.   +10 more
europepmc   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source