Hydrodynamic voltammetry of Fe2+/3+ in aqueous deep eutectic solvents towards redox flow batteries

氧化还原 化学 电解质 氯化胆碱 乙二醇 电化学 线性扫描伏安法 化学工程 共晶体系 无机化学 循环伏安法 水溶液 电极 有机化学 物理化学 合金 工程类
作者
Desiree Mae Prado,Xiaochen Shen,Robert F. Savinell,Clemens Burda
出处
期刊:Electrochimica Acta [Elsevier]
卷期号:467: 143082-143082 被引量:8
标识
DOI:10.1016/j.electacta.2023.143082
摘要

Deep eutectic solvents (DESs) have recently attracted much attention as potential green electrolyte solvents for redox flow batteries. DESs are considered not only as environmentally sustainable but also economically attractive electrolytes because they can be resourced from biological feedstock (alcohols, urea, choline) and are earth-abundant and of low toxicity. Despite these advantages, DESs still have limitations in important aspects such as reactant and ion transport, which is inhibited due to hydrogen-bonding-induced viscosity. Thus, improving the transport properties of redox species in DESs is essential. In addition, we explore the quantitative addition of water to ethaline (a 1:2 choline chloride: ethylene glycol mixture) in order to understand its influence on the kinetics and mass transport properties of DESs. In this work, we show that DESs can be made more fluid and less dense, while avoiding most of the electrochemical instabilities of water. Herein, we investigate the effects of gradually increasing amounts of water to the redox system of Fe2+/3+in ethaline. Our study shows that systematic addition of water leads to a three-fold increase in ionic conductivity and decrease in viscosity that enhances the mass transport and kinetics of DES-based electrolytes while still maintaining an electrochemical window of approximately 1.90 V. The use of environmentally benign electrolyte components together with the observed increase in conductivity will result in a more efficient redox flow battery (RFB) that operates at higher power density without relying on harmful solvents and fossil fuel-based processes.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
OVO发布了新的文献求助10
1秒前
大模型应助孤巷的猫采纳,获得10
1秒前
123zzzzzz发布了新的文献求助10
1秒前
2秒前
善学以致用应助xk采纳,获得10
2秒前
一只布丁发布了新的文献求助30
2秒前
雨天有伞发布了新的文献求助10
2秒前
帅玉玉发布了新的文献求助10
3秒前
李玲玲完成签到,获得积分10
3秒前
榴莲完成签到,获得积分10
3秒前
小芒果完成签到 ,获得积分10
4秒前
4秒前
郝123完成签到,获得积分10
5秒前
dd发布了新的文献求助10
5秒前
5秒前
量子星尘发布了新的文献求助10
5秒前
5秒前
李爱国应助163采纳,获得10
6秒前
6秒前
weiwei1991完成签到,获得积分10
7秒前
UY发布了新的文献求助10
7秒前
7秒前
kdwsb发布了新的文献求助10
8秒前
科目三应助戴苏采纳,获得10
8秒前
栀鸢发布了新的文献求助10
8秒前
小李发布了新的文献求助10
9秒前
情怀应助YN3585采纳,获得10
9秒前
桐桐应助调皮惜天采纳,获得10
10秒前
CodeCraft应助糟糕的便当采纳,获得10
10秒前
10秒前
一休完成签到,获得积分10
11秒前
11秒前
英姑应助坚定的藏花采纳,获得10
11秒前
英俊的铭应助killer采纳,获得10
12秒前
12秒前
lyb发布了新的文献求助10
13秒前
13秒前
一休发布了新的文献求助10
14秒前
15秒前
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1001
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Washback Research in Language Assessment:Fundamentals and Contexts 400
Haematolymphoid Tumours (Part A and Part B, WHO Classification of Tumours, 5th Edition, Volume 11) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5469155
求助须知:如何正确求助?哪些是违规求助? 4572311
关于积分的说明 14335054
捐赠科研通 4499131
什么是DOI,文献DOI怎么找? 2464938
邀请新用户注册赠送积分活动 1453493
关于科研通互助平台的介绍 1428006