Results 191 to 200 of about 6,288 (253)

Variance estimation using memory type estimators based on EWMA statistic for time scaled surveys in stratified sampling. [PDF]

Sci Rep
Tariq MU, Qureshi MN, Alamri OA, Iftikhar S, Alsaedi BSO, Hanif M.   +5 more
europepmc   +1 more source

Insights on SEI Growth and Properties in Na‐Ion Batteries via Physically Driven Kinetic Monte Carlo Model

Advanced Energy Materials, EarlyView.
The novel kinetic Monte Carlo model presented here incorporates spatially‐ and time‐dependent electrical potential, which enables the precise study of the solid electrolyte interphase formation in Na‐ion batteries. The effects of electrolyte composition and charging conditions on the growth and behavior of the solid electrolyte interphase during the ...
Kie Hankins, Miftahussurur Hamidi Putra, Janika Wagner‐Henke, Axel Groß, Ulrike Krewer   +4 more
wiley   +1 more source

Advancing stochastic 3-SAT solvers by dissipating oversatisfied constraints. [PDF]

Proc Natl Acad Sci U S A
Schwardt J, Budich JC.
europepmc   +1 more source

Fabrication of Composite Cathode for All‐Solid‐State Sodium Batteries

Advanced Energy Materials, EarlyView.
The design of composite cathodes for all‐solid‐state sodium batteries must address three critical challenges—interfacial side reactions, interfacial delamination, and highly tortuous transport pathways. This work outlines structural and interfacial strategies to optimize ion transport and mechanical stability, enabling durable, and high‐performance ...
Gaoming Sun, Yuan Ma, Hehe Zhang, Shengan Wu, Shiyong Chu, Stefano Passerini, Yanjiao Ma   +6 more
wiley   +1 more source

A natural language processing-driven map of the aging research landscape. [PDF]

Aging (Albany NY)
Perez-Maletzki J, Sanz-Ros J.
europepmc   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Considering AEWMA control chart applied to Gamma-distributed data with fixed and variable sampling intervals. [PDF]

Sci Rep
Lu SL, Chen MC, Chen JH, Yang SF, Chatterjee K.   +4 more
europepmc   +1 more source

Comparative Insights and Overlooked Factors of Interphase Chemistry in Alkali Metal‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review presents a comparative analysis of Li‐, Na‐, and K‐ion batteries, focusing on the critical role of electrode–electrolyte interphases. It especially highlights overlooked aspects such as SEI/CEI misconceptions, binder effects, and self‐discharge relevance, emphasizing the limitations of current understanding and offering strategies for ...
Changhee Lee, Zachary T. Gossage, Shinichi Kumakura, Shinichi Komaba   +3 more
wiley   +1 more source

Patient-based pre-classified real-time quality control with neural network (PCRTQC-NN). [PDF]

Pract Lab Med
Zhou B, Li X, Cheng S, Zhou Z, Kang H.
europepmc   +1 more source