Results 141 to 150 of about 7,413 (263)

Degradation Pathways of Silicon‐Based Anodes in Lithium‐Ion Batteries

Advanced Energy Materials, EarlyView.
Silicon‐based anodes undergo degradation through five primary pathways: (1) mechanical and structural deterioration of the active material, (2) loss of electrode integrity and electrical contact, (3) mechanical instability of the solid electrolyte interphase (SEI), characterized by repetitive fracture and deformation, (4) chemical instability of the ...
Yoon Jeong Choi, Ji‐Youn Bae, Ga‐On Park, Seung‐Ho Yu   +3 more
wiley   +1 more source

Experimental Study on the Erosion-Corrosion Characteristics of Desulfurization Slurry on Stainless Steel Pipe Materials. [PDF]

ACS Omega
Fan G, Zhang J, Yuan T, Wang C, Hou Y, Gao X, Xu J, Che D.   +7 more
europepmc   +1 more source

Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries

Advanced Energy Materials, EarlyView.
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu, Huaping Zhao, Lizhuang Chen, Weidong Shi, Guosheng Shao, Yong Lei   +5 more
wiley   +1 more source

Streamlined V3.5+ Electrolyte Production by Leveraging Chemical and Catalytic Reductions

Advanced Energy Materials, EarlyView.
A tuned catalytic process for V3.5+ electrolyte production is shown to streamline the conventional chemical‐to‐catalytic sequence by extending catalysis into the rate‐determining reduction regime. This study shows that initiating catalysis in this regime shortens the overall production time by 67% based on rigorous thermodynamic and kinetic analysis of
Kyunghwa Seok, Minseong Kang, Hee‐Tak Kim   +2 more
wiley   +1 more source

Cavitation erosion-corrosion properties of as-cast TC4 and LPBF TC4 in 0.6 mol/L NaCl solution: A comparison investigation. [PDF]

Ultrason Sonochem
Yang Z, Li L, Qiao Y, Li C, Zhang L, Cui J, Ren D, Ji H, Zheng Y.   +8 more
europepmc   +1 more source

Organic Photoelectrochemical Cells Beyond Performance: Interface and Catalyst Engineering for Durability

Advanced Energy Materials, EarlyView.
Organic photoelectrochemical cells based on π‐conjugated semiconductors offer a versatile platform for solar fuel generation. This review outlines operating principles, device architectures, and key metrics, and highlights advances in p‐ and n‐type photoelectrodes, interfacial engineering, and catalyst integration.
Jaehyeong Kim, Jung Min Ha, Yeonjeong Lee, Seung Won Oh, Wangyeon Lee, Munsu Kwon, Soonyong Lee, Jin Young Kim, Han Young Woo   +8 more
wiley   +1 more source

Redefining Crystalline Silicon: Unlocking New Horizons in Transparent and Flexible Photovoltaics

Advanced Energy Materials, EarlyView.
Crystalline silicon is presented as a platform for transparent and flexible photovoltaics. This review article outlines design principles for optical strategies to fabricate transparent silicon solar cells, mechanical strategies that mitigate silicon brittleness, and emerging concepts such as singlet‐fission spectral conversion and tandem architectures,
Kangmin Lee
wiley   +1 more source

Erosion-Corrosion of 30°, 60°, and 90° Carbon Steel Elbows in a Multiphase Flow Containing Sand Particles. [PDF]

Materials (Basel), 2019
Khan R, Ya HH, Pao W, Khan A.
europepmc   +1 more source

Challenges and enablers in fluidization technology

AIChE Journal, EarlyView.
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source