High performance silicon nanoparticle anode in fluoroethylene carbonate-based electrolyte for Li-ion batteries.

Chem Commun (Camb)

Department of Chemical Engineering, Center for Electrochemistry, Texas Materials Institute, University of Texas at Austin, 1 University Station, C0400 Austin, TX 78712-0231, USA.

Published: July 2012

Electrodes composed of silicon nanoparticles (SiNP) were prepared by slurry casting and then electrochemically tested in a fluoroethylene carbonate (FEC)-based electrolyte. The capacity retention after cycling was significantly improved compared to electrodes cycled in a traditional ethylene carbonate (EC)-based electrolyte.

Download full-text PDF

Source
http://dx.doi.org/10.1039/c2cc31712eDOI Listing

Publication Analysis

Top Keywords

high performance
4
performance silicon
4
silicon nanoparticle
4
nanoparticle anode
4
anode fluoroethylene
4
fluoroethylene carbonate-based
4
carbonate-based electrolyte
4
electrolyte li-ion
4
li-ion batteries
4
batteries electrodes
4

Similar Publications

Adding secondary cognitive tasks to drop vertical jumps alters the landing mechanics of athletes with anterior cruciate ligament reconstruction.

J Biomech

January 2025

Department of Community Medicine and Rehabilitation, Unit of Physiotherapy, Umeå University, Umeå, Sweden. Electronic address:

Anterior cruciate ligament (ACL) reinjury rates among athletes remain very high despite screening protocols designed to assess readiness for return to sport. To better identify biomechanical risk factors for ACL injury, combining neurocognitive challenges and high-impact tasks would more closely resemble sporting demands. We investigated the influence of secondary cognitive tasks on landing mechanics during bilateral drop vertical jumps (DVJs) among athletes following ACL reconstruction and whether sex affected these results.

View Article and Find Full Text PDF

SLC7A5 is required for cancer cell growth under arginine-limited conditions.

Cell Rep

January 2025

Department of Biochemistry, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA. Electronic address:

Tumor cells must optimize metabolite acquisition between synthesis and uptake from a microenvironment characterized by hypoxia, lactate accumulation, and depletion of many amino acids, including arginine. We performed a metabolism-focused functional screen using CRISPR-Cas9 to identify pathways and factors that enable tumor growth in an arginine-depleted environment. Our screen identified the SLC-family transporter SLC7A5 as required for growth, and we hypothesized that this protein functions as a high-affinity citrulline transporter.

View Article and Find Full Text PDF

Introduction: Laryngeal chondrosarcoma (CS) is a rare indolent malignant tumor. High-grade (G3), dedifferentiated (DD), and myxoid (MY) CSs are considered more aggressive subtypes due to their metastatic potential and relatively poor outcomes. The aim of this systematic review is to evaluate treatment modalities and survival outcomes in patients affected by these rarer CS subtypes.

View Article and Find Full Text PDF

Background: Knee injuries resulting in purely cartilaginous defects are rare, and controversy remains regarding the reliability of chondral-only fixation.

Purpose: To systematically review the literature for fixation methods and outcomes after primary fixation of chondral-only defects within the knee.

Study Design: Systematic review; Level of evidence, 5.

View Article and Find Full Text PDF

Weighted Echo State Graph Neural Networks Based on Robust and Epitaxial Film Memristors.

Adv Sci (Weinh)

January 2025

College of Physics Science & Technology, School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei University, Baoding, 071002, China.

Hardware system customized toward the demands of graph neural network learning would promote efficiency and strong temporal processing for graph-structured data. However, most amorphous/polycrystalline oxides-based memristors commonly have unstable conductance regulation due to random growth of conductive filaments. And graph neural networks based on robust and epitaxial film memristors can especially improve energy efficiency due to their high endurance and ultra-low power consumption.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!