Ni-rich cathodes have recently gained significant attention as next-generation cathodes for lithium-ion batteries. However, their relatively high oxidative surface should be reduced to control the high surface reactivity because the capacity retention decreases rapidly in the batteries. Herein, a simple and effective method to pretreat LiNiMnCoO (NMC811) particles using a cosolvent for improving the battery performance is reported. Imitating the interfacial reaction in practical cells, an artificial layer is created via a spontaneous redox reaction between the cathode and the organic solvent. The artificial layer comprises metal-organic compounds with reduced transition-metal cations. Benefiting from the artificial layer, the cells deliver high capacity retention at a high current density and better rate capability, which might result from the low and stable interfacial resistance of the modified NMC811 cathode. Our approach can effectively reduce the high oxidative surface of most oxide cathode materials and induce a long cyclic lifespan and high capacity retention in most battery systems.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/acsami.4c00686 | DOI Listing |
Mater Horiz
January 2025
Center for Nanophotonics, AMOLF, 1098 XG, Amsterdam, The Netherlands.
Hardware neural networks could perform certain computational tasks orders of magnitude more energy-efficiently than conventional computers. Artificial neurons are a key component of these networks and are currently implemented with electronic circuits based on capacitors and transistors. However, artificial neurons based on memristive devices are a promising alternative, owing to their potentially smaller size and inherent stochasticity.
View Article and Find Full Text PDFHeliyon
January 2025
Faculty of Mechanical Engineering, University of Tehran, Iran.
In order to lower total energy consumption, this study focuses on optimizing energy use in refinery boilers. Using Aspen HYSYS simulations and modeling approaches like Artificial Neural Networks (ANNs) and Response Surface Methodology (RSM), data from 579 days of boiler operation was gathered and examined. Radial Basis Function (RBF) and Multi-Layer Perceptron (MLP) techniques were used in the ANN modeling.
View Article and Find Full Text PDFFront Bioeng Biotechnol
January 2025
Department of Rheumatology and Immunology, Beijing Hospital, National Centre of Gerontology, Beijing, China.
Background: Knee osteoarthritis (KOA) constitutes the prevailing manifestation of arthritis. Radiographs function as a common modality for primary screening; however, traditional X-ray evaluation of osteoarthritis confronts challenges such as reduced sensitivity, subjective interpretation, and heightened misdiagnosis rates. The objective of this investigation is to enhance the validation and optimization of accuracy and efficiency in KOA assessment by utilizing fusion deep learning techniques.
View Article and Find Full Text PDFACS Omega
January 2025
Department of Chemistry, Selcuk University, Konya 42130, Turkey.
The montmorillonite@iron oxide@silver (MMT@FeO@Ag) nanocomposite, which is recyclable and exhibits high catalytic activity, was evaluated for the degradation of methyl yellow (MY), a carcinogenic azo dye. For this purpose, MMT@FeO was first synthesized via the coprecipitation method and then Ag was doped to MMT@FeO via the chemical reduction method. MMT, MMT@FeO, and MMT@FeO@Ag were characterized by various techniques including scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, vibrating sample magnetometer, and thermal gravimetric analysis.
View Article and Find Full Text PDFNat Commun
January 2025
AI for Science (AI4S)-Preferred Program, Peking University Shenzhen Graduate School, Shenzhen, 518055, China.
In chemistry, empirical paradigms prevail, especially within the realm of chromatography, where the selection of separation conditions frequently relies on the chemist's experience. However, the underlying rationale for such experiential knowledge has not been established or analysed. This study explicitly elucidates how chemists use thin-layer chromatography (TLC) to determine column chromatography (CC) conditions, employing statistical analysis and machine learning techniques.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!