Results 191 to 200 of about 878,830 (352)

Debunking Common Myths & Misconceptions About NMC Positive Electrode Materials for Li‐ion Batteries

open access: yesAdvanced Energy Materials, EarlyView.
LiNixMnyCozO2 (NMC) and LiNixCoyAlzO2 (NCA) remain the choice for high‐energy‐density lithium‐ion battery positive electrode materials, yet many myths persist surrounding them. Herein, four common misconceptions are tackled to better inform the lithium‐ion battery field.
Matthew D. L. Garayt   +10 more
wiley   +1 more source

Investigation Into the Electrochemical Performance of Micron‐ and Nanosized Tin in Diglyme and Carbonate Electrolytes in Sodium Ion Batteries

open access: yesAdvanced Energy Materials, EarlyView.
This study compares Sn particles of different sizes in NIBs using carbonate‐ and diglyme‐based electrolytes. Diglyme electrolytes enable stable cycling despite large volume changes, while carbonate electrolytes degrade rapidly, especially with nanoparticles.
Chinnasamy Murugesan   +4 more
wiley   +1 more source

A Quantitative Lithium Inventory Framework for Anode‐Free Lithium Metal Batteries

open access: yesAdvanced Energy Materials, EarlyView.
A component‐resolved lithium inventory framework quantitatively tracks Li redistribution across the cell in anode‐free NMC622||Cu pouch cells throughout cycling. Three sequential degradation stages are identified: formation‐driven cathode Li depletion, midlife inactive Li0 accumulation, and late‐stage runaway SEI thickening. The cathode, as the sole Li
Wurigumula Bao   +9 more
wiley   +1 more source

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen   +5 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

open access: yesAdvanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin   +4 more
wiley   +1 more source

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