98%
921
2 minutes
20
Background: Sodium vanadium fluorophosphate is a sodium ion superconductor material with high sodium ion mobility and excellent cyclic stability, making it a promising cathode material for sodium-ion batteries. However, most of the literature and patents report preparation through traditional methods, which involve complex processes, large particle sizes, and low electronic conductivity, thereby limiting development progress.
Objective: Aiming at the limitation of high cost and poor performance of vanadium sodium fluorophosphate cathode material, the low temperature and high-efficiency nano preparation technology was developed.
Methods: This study uses a homogenizer with high dispersion and shear force to directionally control the collision of sodium vanadium fluorophosphate nanoparticles with higher specific surface energy during the initial nucleation stage, forming nanosheet structures.
Results: The growth mechanism of these nanosheets was analyzed using SEM, XRD, AFM, and DFT simulation. Results indicate that the crystal surfaces with higher surface energy undergo directional collisions in the early nucleation stage, gradually reducing the surface energy and stabilizing the system, resulting in sodium vanadium fluorophosphate nanosheets.
Conclusion: Due to the larger specific surface area and pore structure, these nanosheets exhibit excellent rate performance and cycle stability, making them suitable for application and promotion in the field of fast-charging energy storage.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.2174/0118722105340055241022051936 | DOI Listing |
Cell Mol Biol (Noisy-le-grand)
September 2025
Associate Professor, School of Pharmacy, Desh Bhagat University, Mandi Gobindgarh-Punjab 147301, India.
Alcoholic fatty liver disease (AFLD) is a leading cause of chronic liver disease worldwide, contributing to significant morbidity and mortality. Despite its growing prevalence, no FDA-approved pharmacological treatments exist, leaving lifestyle modifications as the primary intervention. AFLD pathogenesis involves a complex interplay of lipid accumulation, oxidative stress, insulin resistance, and inflammation, highlighting the need for innovative therapeutic approaches.
View Article and Find Full Text PDFActa Crystallogr E Crystallogr Commun
September 2025
University of the Free State, Chemistry Department, Bloemfontein, South Africa.
The crystal structure of a nitrate anion caged in spherical vanadium and oxygen structure surrounded by sodium hy-droxy and water solvent mol-ecules, systematic name poly[[hepta-deca-aqua-tetra-deca-oxidonona-sodium][penta-cosa-aqua-nitratoundeca-oxido-penta-deca-vanadium]], HNNaOV is reported. The complex crystallizes in the non-centrosymmetric space group and exhibits many inter- and intra-molecular hydrogen-bonding inter-actions. The complex contains V and V centres, which are six-coordinate or octa-hedrally coordinated.
View Article and Find Full Text PDFAdv Sci (Weinh)
August 2025
School of Chemistry and Chemical Engineering, and Key Laboratory of Advanced Biomaterials and Nanomedicine in Universities of Shandong, Linyi University, Linyi, 276000, China.
Sodium vanadium fluorophosphate (NaV(PO)F, NVPF), a promising cathode material for sodium-ion batteries, exhibits high energy density and a stable voltage plateau, yet its practical application is hindered by intrinsic low electronic conductivity. Here, a medium-entropy engineering strategy is introduced to address this limitation by developing a novel NaFeMnCoNiV(PO)F@CNTs (ME-NVPF@CNTs) composite. The medium-entropy design synergistically optimizes structural stability and charge transport kinetics, while carbon nanotubes (CNTs) coating enhances surface conductivity.
View Article and Find Full Text PDFJACS Au
August 2025
College of Chemistry, Key Laboratory of Theoretical & Computational Photochemistry of Ministry of Education, Beijing Normal University, Beijing 100875, People's Republic of China.
Graph neural networks for crystal property prediction typically require precise atomic positions and types, limiting their applicability for novel materials with unknown structures. To address this limitation, we introduce BatteryFormer, a versatile machine learning model that employs average interatomic radius distance instead of precise bond lengths as edge embedding, enabling rapid, high-throughput material screening based solely on composition and structural prototypes. BatteryFormer demonstrates robust predictive performance across a wide range of intervals.
View Article and Find Full Text PDFChemSusChem
August 2025
Institute for Technology Assessment and Systems Analysis (ITAS), KIT, 76021, Karlsruhe, Germany.
Sodium-ion batteries (SIBs) are considered the most promising candidate for electrochemical storage after lithium-ion batteries (LIBs) to meet the globally growing energy storage demand. Assessments to identify environmental hotspots and address them in further development at regular intervals are inevitable to ensure low environmental impact of SIBs in the future. However, the number of studies assessing the environmental impacts of SIBs is limited, and existing studies are mostly based on theoretical models and few limited sources.
View Article and Find Full Text PDF