Results 191 to 200 of about 15,689 (260)

Sustainable Carbon Fibers Enable Stable Long‐Term Lithium Metal Deposition for Prospective Zero‐Excess Lithium Metal Batteries

open access: yesAdvanced Energy Materials, Volume 16, Issue 30, 12 August 2026.
This work presents lightweight, lignin‐derived carbon fiber current collectors that enable controlled lithium deposition. Structural defects and intermediate‐sized pores stabilize pre‐nucleation quasi‐metallic lithium clusters, promoting uniform lithium plating and stripping.
Samantha L. S. Southern   +13 more
wiley   +1 more source

Current‐Driven Li2O Formation in Catalyst‐Free Solid‐State Li‐O2 Batteries Enabling Simultaneous High Energy and High Power

open access: yesAdvanced Energy Materials, Volume 16, Issue 30, 12 August 2026.
A catalyst‐free solid‐state Li‐O2 battery achieves current‐driven four‐electron Li2O formation, delivering simultaneous high‐energy and high‐power operation with 1032 Wh·kg−1 and 374 W·kg−1 in a single cell. ABSTRACT Li‐O2 batteries offer a compelling pathway toward next‐generation energy storage owing to their ultrahigh theoretical energy density ...
Shu‐Ting Ko   +9 more
wiley   +1 more source

Lecanemab use in Chinese patients with Alzheimer's disease: a 12‐month multicenter real‐world study

open access: yesAlzheimer's &Dementia, Volume 22, Issue 8, August 2026.
Abstract INTRODUCTION We evaluated lecanemab's safety and cognitive outcomes in Chinese patients with Alzheimer's disease (AD) and the utility of blood‐based biomarkers (BBMs) for treatment guidance. METHODS A multicenter, real‐world cohort enrolled 1042 patients receiving lecanemab, with 453, 359, 97 patients followed up at 3, 6, 12 months ...
Hao Wu   +35 more
wiley   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

open access: yesThe Canadian Journal of Chemical Engineering, Volume 104, Issue 8, Page 4079-4100, August 2026.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos   +3 more
wiley   +1 more source

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