Results 91 to 100 of about 24,647,611 (261)

Progress towards commercially viable Li-S battery cells

, 2015
A broad overview of how experimental parameters affect the performance of Li-S batteries is presented here, extending the view on these batteries beyond sophisticated conductive sulfur hosts, which have been the primary focus of many studies in recent ...
Novák, Petr (author), Poux, Tiphaine (author), Urbonaite, Sigita (author)   +2 more
core   +1 more source

S@NiS Hollow Spheres as Cathode Materials for LithiumSulfur Batteries

International Journal of Electrochemical Science, 2019
Severe capacity fading substantially hinders the employment of lithium-sulfur batteries in the electric vehicles. This is primarily due to the shuttle effect of the polysulfide in the electrolyte. Therefore, the most efficient method to improve the cycle
Bing Che, Dong Wang, Xiaochun Xu
doaj   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Effects of Mg on Microstructure and Solidification of a Hypereutectic Zn–8 wt.%Al Alloy

Advanced Engineering Materials, EarlyView.
An appreciable set of results involving thermal data, microstructure, chemical composition, and microstructural growth laws is reported for ZnAlMg alloys. Such results demonstrate that ZnAlMg alloys have high potential for applications in automotive self‐lubricating components, batteries, and electrical systems.
Raí B. de Sousa, Jeverton L. Paixão, Daylla S. Silva, Bruno S. Sobral, Mucio D. de Medeiros, José E. Spinelli, Bismarck L. Silva   +6 more
wiley   +1 more source

Regulating liquid and solid-state electrolytes for solid-phase conversion in Li–S batteries

, 2022
The solid-phase conversion mechanism in lithium–sulfur (Li–S) batteries has emerged with many attractive advantages such as avoiding the parasitic “shuttle effect” of soluble polysulfides and allowing lean electrolyte operating conditions.
Chao Xing, Ameer Nizami, Hao Chen, Zhang, S, Shanqing Zhang, Xing, C, Nizami, A, Lai, C, Shangshu Qian, Chao Lai, Xia Li, Qian, S, Wu, Z, Li, X, Chen, H, Zhenzhen Wu   +15 more
core   +1 more source

Hierarchical Carbon Interlayer Design as Interfacial Stabilizer and In-Situ Solid-Electrolyte Infiltrate for High-Performance Solid-State Li–S Batteries

Chem & Bio Engineering
A great deal of attention has been paid to lithium–sulfur (Li–S) batteries due to their high energy density (>2600 Wh kg–1), elemental abundance, and environmental friendliness, which show great application prospects in a wide range of energy storage ...
Ludi Pan, Wenbin Zhao, Liqing Zhai, Ruiqi Guo, Yuying Zhao, Xinran Wang, Chuan Wu, Ying Bai   +7 more
doaj   +1 more source

Ti4O7 Layer Coated Sulfur Composite as High-Performance Cathode Material for Lithium-Sulfur Battery

International Journal of Electrochemical Science, 2019
The application of Li-S battery is hindered mainly due to the shuttle effect of the polysulfide, which is produced via discharge process. Most recently, metal oxides are applied for inhibiting this shuttle effect.
Zhao Jinguo, Liu Shoufa
doaj   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns, Lateef Abdul, Stephan Barth, Martin Glauer, Manuel Günther, Fabian Neuhaus, Jan‐Ole Perschewski, Thomas Bjarsch, Henrik Abel, Johannes Bosch, Niklas Meyer, Peter Hofmann, Marc Drechsler, Alexander Dyck, Dhanunjaya Kumar Nerella, Marvin Tegeler, Oleg Shchyglo, Ingo Steinbach, Timo Klecker, Henk Birkholz, Ehsan Borzabadi Farahani, Bernard Fedelich, Cetin Haftaoglu, Tarakeshwar Lakshmipathy, Elena Garcia Trelles, Christoph Schweizer, Reza Darvishi Kamachali, Lukas Koschmieder, Janin Eiken, Markus Apel, Sung‐Min Wi, Jiangdong Zhao, Andreas Fezer, Nicolas Christ, Patrick Schneider, Eldor Urinov, Veit Königer, Volker Knoblauch, Janik Harter, Thomas Seifert, Thitichai Janpheng, Florian Fuchs, Fabian Teichert, Jörg Schuster, Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann, Felix Wentzien, Heike Wittek, Benjamin Klie, Alexander Röhrs, Ludger Overmeyer, Achraf Atila, Marcel Sadowski, Leopold Talirz, Jan Janssen, Jesper R. Pedersen, Peter Beck, Tejs Vegge, Ivano E. Castelli, Wolfgang Wenzel, Tilmann Hickel, Jörg Schaarschmidt   +67 more
wiley   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source

Failure analysis of some Toyota Prius battery packs and potential for recovery [PDF]

, 2011
The Toyota Prius battery pack consists of 38 individual battery blades, each blade contains 6 NiMH cells in series. This means that each pack contains 228 NiMH cells. Each cell has the potential to fail.
Leijen, Peter, Scott, Jonathan B.
core   +1 more source