Results 191 to 200 of about 107,571 (269)

Entropy‐Driven Innovations: Entropy Stabilized Oxides for High‐Performance Next‐Generation Lithium–Sulfur Batteries

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This article explores high‐entropy‐stabilized oxides (HEOs) as novel functional materials for addressing critical issues in lithium–sulfur (Li–S) batteries, including lithium polysulfide (LPS) shuttling, inadequate conductivity, and slow redox kinetics.
Hassan Raza, Jialiang Wei, Zhicai Wang, Zhaoyang Lv, Junye Cheng, Jia Xu, Liang An, Yuliang Liu, Sergey Ryazantsev, Shukui Li, Guangping Zheng   +10 more
wiley   +1 more source

Information-Entropy Analysis of Stellar Evolutionary Stages with Application to FS CMa Objects. [PDF]

Entropy (Basel)
Zhanabaev Z, Akniyazova A, Ashimov Y.
europepmc   +1 more source

Redistributing Cobalt and Tungsten From WC–Co Soft Scrap Toward Sustainable Cathode and Coating Materials for Lithium‐Ion Batteries

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
A sustainable upcycling strategy transforms tungsten carbide–cobalt (WC–Co) soft scrap into high‐performance cathode materials. Recycled Co with trace nickel (Ni) is resynthesized into stabilized LiCoO2 with superior high‐voltage durability, while the recovered tungsten is further utilized as tungsten trioxide to enhance Ni‐rich cathode interfaces ...
Seulgi Kim, Kyoung Sun Kim, Young‐Sang Yu, Ingyu Choi, Seungo Jeong, Eun‐Jung Shin, Seung‐Hyun Kim, Sung‐Hak Jo, Seung‐Ho Yu, Hyungsub Kim, Dongju Lee   +10 more
wiley   +1 more source

Employing deep-learning techniques for the conservative-to-primitive recovery in binary neutron star simulations. [PDF]

Eur Phys J A Hadron Nucl
Mudimadugula R, Schianchi F, Neuweiler A, Wouters T, Gieg H, Dietrich T.   +5 more
europepmc   +1 more source

Machine Learning‐Driven Classification and Production Capacity Prediction of Tight Sandstone Reservoirs: A Case Study of the Taiyuan Formation, Ordos Basin

Energy Science &Engineering, EarlyView.
On the basis of core and log data, a Bayesian‐Optimized Random Forest model achieved 92.76% accuracy in classifying tight sandstone reservoirs. A gray relational analysis‐derived evaluation index shows > 80% consistency with actual gas zones. ABSTRACT Tight sandstone gas (TSG), an unconventional oil–gas resource, has heterogeneous reservoirs ...
Yin Yuan, Haijiao Fu, Detian Yan, Gang Wang, Shuguang Yang, Mengmeng Liu, Qingling Jiang, Xiaoming Wang, Wei Wang   +8 more
wiley   +1 more source

Exploring the extremes: The cosmic laboratory. [PDF]

Innovation (Camb)
Huang Y, He S, Ge L, Li Z, Mao Y, Liu J.
europepmc   +1 more source

Harnessing deep learning to quantify microstructural complexity in confocal images of plant protein gels

Food Biomacromolecules, EarlyView.
Abstract Understanding plant protein gel microstructure is key to designing functional food systems. This study introduces a deep learning framework using a U‐Net model with a ResNet34 encoder to segment and quantify confocal laser scanning microscopy (CLSM) images of plant protein gels.
Zhi Yang
wiley   +1 more source

Neutron capture measurements for s-process nucleosynthesis: A review about CERN n_TOF developments and contributions. [PDF]

Eur Phys J A Hadron Nucl
Domingo-Pardo C, Aberle O, Alcayne V, Alpar G, Halabi MA, Amaducci S, Babiano V, Bacak M, Balibrea-Correa J, Bartolomé J, Bernardes AP, Gameiro BB, Berthoumieux E, Beyer R, Birch M, Boromiza M, Bosnar D, Brusasco B, Caamaño M, Cahuzac A, Calviño F, Calviani M, Cano-Ott D, Casanovas A, Castelluccio DM, Catlett D, Cerutti F, Cescutti G, Chiaveri E, Claps G, Colombetti P, Colonna N, Camprini PC, Cortés G, Cortés-Giraldo MA, Cosentino L, Cristallo S, D'Ottavi A, de la Fuente Rosales G, Dellmann SF, Diakaki M, Di Castro M, Di Chicco A, Dietz M, Dupont E, Durán I, Eleme Z, Eslami M, Fargier S, Fernández-Domínguez B, Finocchiaro P, Flanagan W, Furman V, Gandhi A, García-Infantes F, Gawlik-Ramiega A, Gervino G, Gilardoni S, González-Romero E, Goula S, Griesmayer E, Guerrero C, Gunsing F, Gustavino C, Heyse J, Hillman W, Jenkins DG, Jericha E, Junghans A, Kadi Y, Kaperoni K, Kelly I, Kokkoris M, Kopatch Y, Krtička M, Kyritsis N, Lederer-Woods C, Lerendegui-Marco J, Manna A, Martínez T, Martínez-Cañada M, Masi A, Massimi C, Mastinu P, Mastromarco M, Maugeri EA, Mazzone A, Mendoza E, Mengoni A, Michalopoulou V, Milazzo PM, Moldenhauer J, Mucciola R, González EM, Musumarra A, Negret A, Odusina E, Papanikolaou D, Patronis N, Pavón-Rodríguez JA, Pellegriti MG, Pérez-Maroto P, de Rada Fiol AP, Perfetto G, Perkowski J, Petrone C, Pieretti N, Piersanti L, Pirovano E, Porras I, Praena J, Quesada JM, Reifarth R, Rochman D, Romanets Y, Rooney A, Rovira G, Rubbia C, Sánchez-Caballero A, Sahoo RN, Scarpa D, Schillebeeckx P, Smith AG, Sosnin NV, Spelta M, Stamati ME, Stasiak K, Tagliente G, Tarifeño-Saldivia A, Tarrío D, Torres-Sánchez P, Tosi S, Tsiledakis G, Valenta S, Vaz P, Vecchio G, Vescovi D, Vlachoudis V, Vlastou R, Wallner A, Weiss C, Woods PJ, Wright T, Wu R, Žugec P, The n_TOF Collaboration.   +145 more
europepmc   +1 more source

Emerging single‐element ferroelectrics: From theory to experiment

InfoMat, EarlyView.
This review explores recent developments in single‐element ferroelectrics, covering mechanisms of ferroelectric behavior, their crystal structures, key preparation methods, ferroelectric performance characteristics, and promising device applications in field‐effect transistors, photodetectors, and visual perceptrons.
Run Zhao, Yuhang Zhang, Chen‐Min Dai, Fan Li, Jinlei Zhang, Ju Gao, Yucheng Jiang, Cheng‐Wei Qiu   +7 more
wiley   +1 more source

Neutron stars [PDF]

Progress in Particle and Nuclear Physics, 1981
openaire   +2 more sources