Deep-Eutectic Solvent As a Solvent and Precursor for the Synthesis of a Carbon-Coated Na3V2(PO4)2F3-yOy Material.

Gaël Minart, Runhe Fang,Christine Labrugère-Sarroste,François Weill,Sonia Buffière,Sophie Cassaignon,Laurence Croguennec,Jacob Olchowka

ACS applied materials & interfaces（2025）

CNRS

Cited 0|Views3

Abstract

Deep eutectic solvents (DES) are well-known as cost-effective and environmentally friendly "designer solvents" for controlling the size and morphology of nanomaterials. In this study, we leverage DES not only as a solvent for the topochemical synthesis of Na3V2(PO4)2F3-yOy (0 ≤ y ≤ 2) but also as a precursor for a uniform and thin carbon coating. After solvothermal synthesis in a green deep eutectic solvent composed of a mixture of choline chloride, citric acid, and water (3:1:3 molar ratio), XRD refinements and FTIR, XPS, and TEM analyses confirmed the obtention of a pure Na3V2(PO4)2F3-yOy (0 ≤ y ≤ 2) phase encapsulated in an organic layer derived from a residual deep eutectic solvent. Subsequent sintering at 600 °C under an argon atmosphere produced a homogeneous nitrogen-doped carbon coating without the need for additional carbon sources. Electrochemical tests in galvanostatic conditions demonstrated that this material exhibits excellent performance in terms of capacity retention and rate capabilities, with specific capacities exceeding 110 mAh/g at 2C versus Na metal and 68 mAh/g at 10C in full cells versus hard carbon.

Translated text

求助PDF

上传PDF

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Upload PDF to Generate Summary

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper

Data Disclaimer

The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn

Chat Paper

【要点】：本研究创新性地利用深共晶溶剂（DES）既作为溶剂也作为前驱体，合成了碳包覆的Na3V2(PO4)2F3-yOy材料，展现出优异的电化学性能。

【方法】：通过在由胆碱氯化物、柠檬酸和水（3:1:3摩尔比）组成的绿色深共晶溶剂中进行溶剂热合成，以及后续在氩气氛围下600°C烧结，制备了氮掺杂的均匀碳包覆层。

【实验】：在绿色深共晶溶剂中进行溶剂热合成，使用XRD、FTIR、XPS和TEM分析确认了Na3V2(PO4)2F3-yOy (0 ≤ y ≤ 2)相的纯度及有机层包裹，并在电化学测试中表现出高容量保持率和速率性能，具体容量在2C和10C下分别超过110 mAh/g和68 mAh/g。