Results 231 to 240 of about 1,733,188 (294)

Multi‐modal Operando Analysis of Lithium–Sulfur Batteries: A Comparative Study on the Influence of Electrolyte Composition

open access: yesAdvanced Energy Materials, EarlyView.
The influence of different electrolytes on Lithium–sulfur batteries is investigated. Multimodal operando analysis, including Raman, UV–vis, and Impedance spectroscopy is used to study degradation mechanisms. The solubility of polysulfides in the electrolyte is crucial for battery capacity and lifetime.
Oliver Löhmann   +3 more
wiley   +1 more source

Electrolyte Interfacial Reactivity Regulates Alloying Anode Pulverization

open access: yesAdvanced Energy Materials, EarlyView.
Electrolyte interfacial reactivity governs the degradation of micrometer‐sized alloying anodes by dictating grain refinement and SEI growth. A high‐reactivity ester‐based electrolyte drives pulverization into fine nanoparticles encapsulated by a thick SEI, forming dense electrodes, whereas a low‐reactivity ether‐based electrolyte enables porous ...
Namhyung Kim   +21 more
wiley   +1 more source

Revealing the roles of the solid-electrolyte interphase in designing stable, fast-charging, low-temperature Li-ion batteries. [PDF]

open access: yesProc Natl Acad Sci U S A
Tao L   +18 more
europepmc   +1 more source

Decoupling Quasi‐Solid‐State Sulfur Conversion Mechanisms in Weakly Solvating and Locally High Concentration Electrolytes

open access: yesAdvanced Energy Materials, EarlyView.
Weakly solvating CME–TTE and localized high‐concentration G2–TTE electrolytes redirect lithium–sulfur chemistry toward quasi‐solid‐state conversion through distinct coordination environments. Molecular dynamics and multimodal electrochemical and spectroscopic measurements show that G2–TTE couples multidentate solvent coordination, anion participation ...
Boyi Pang   +12 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

Home - About - Disclaimer - Privacy