Results 211 to 220 of about 196,483 (296)

Empirical Mode Decomposition and its application to Palm Tree Mode analysis [PDF]

, 2011
Gennrich, F., Hoffmann, Mathias, Juul Rasmussen, Jens, Maszl, Ch., Naulin, Volker, Schrittwieser, R.   +5 more
core  

Resolving Oxidative and Corrosive Calendar‐Aging via Electrolyte Engineering for Stable Lithium Metal Batteries

Advanced Energy Materials, EarlyView.
A weakly solvating ether solvent, 1,2‐dimethoxypropane (DMP), is proposed for use in localized high‐concentration electrolytes (LHCEs) for lithium metal batteries (LMBs). These DMP‐based LHCEs simultaneously suppress lithium metal corrosion and cathode degradation—two interrelated processes that accelerate calendar aging of LMBs.
Jisub Kim, Ihnkyung Jung, Kyunam Lee, Insu Hwang, Minkwan Kim, Eunseok Park, Dongmin Park, Hayoung Park, Yonggoon Jeon, Gaeun Park, Hyo Chul Ahn, Jihoon Oh, Jungwon Park, Ali Coskun, Jang Wook Choi   +14 more
wiley   +1 more source

Research on a Sound Source Localization Method for UAV Detection Based on Improved Empirical Mode Decomposition. [PDF]

Sensors (Basel)
Chen T, Yu J, Yang Z.
europepmc   +1 more source

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

Off-Grid Underwater Acoustic Source Direction-of-Arrival Estimation Method Based on Iterative Empirical Mode Decomposition Interval Threshold. [PDF]

Sensors (Basel)
Xing C, Tan G, Dong S.
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Improved complete ensemble empirical mode decomposition with adaptive noise and composite multiscale permutation entropy for denoising blast vibration signal. [PDF]

Heliyon
Kang YZ, Yao YK, Dong RL, Jia YS, Xie QM, Wang JN.   +5 more
europepmc   +1 more source

Recent Advances in Nano‐Microstructured Catalysts for Electrochemical Seawater Electrocatalysis

Advanced Energy Materials, EarlyView.
This review highlights advances in nano‐ and microstructured catalysts for electrochemical seawater conversion. It elucidates design principles, mechanistic understanding, and machine‐learning‐assisted discovery, and outlines key challenges and future opportunities toward efficient, selective, and durable seawater electrocatalysis.
Xiaodong Shao, Mengfang Liang, Xiaotong Han, Xu Yu, Huan Pang, Ho Seok Park   +5 more
wiley   +1 more source

Analyzing individual rent price ratios in eastern German agricultural land markets: A GAMLSS approach

Agribusiness, EarlyView.
Abstract This study explores the rent price ratio in agricultural land markets, crucial for evaluating market efficiency, policy needs, and farmer decision‐making. Traditionally, the analyses faced challenges due to the absence of concurrent sale and rent data for the same land, potentially leading to biased results.
Marius Michels, Cord‐Friedrich von Hobe, Miryam Sarah Merk, Thomas Kneib, Oliver Musshoff   +4 more
wiley   +1 more source

Random Convolutional Kernel Transform with Empirical Mode Decomposition for Classification of Insulators from Power Grid. [PDF]

Sensors (Basel)
Klaar ACR, Seman LO, Mariani VC, Coelho LDS.   +3 more
europepmc   +1 more source