Optimizing porous medium electrode suspension drying: A numerical simulation

物理 多孔介质 悬挂(拓扑) 机械 多孔性 电极 复合材料 同伦 数学 量子力学 材料科学 纯数学
作者
Xin Ye,Zhiming Yang,Xijiang Liu,Qian Lu,Shuai Yuan,Fengze Jiang
出处
期刊:Physics of Fluids [American Institute of Physics]
卷期号:36 (7) 被引量:5
标识
DOI:10.1063/5.0215134
摘要

The drying process of porous medium electrodes is crucial for optimizing the performance of lithium-ion batteries. Among various drying methods, convection drying has been proven to be an effective double-sided and contactless technique for these electrodes, enhancing manufacturing quality and efficiency. This study investigates the impact of different drying parameters on the drying process of porous medium electrodes by establishing a coupling model for convective drying. The particle swarm algorithm optimized the drying parameters to minimizing drying time and energy consumption. As a result of this optimization, the optimal drying temperature and Reynolds number were found to be 104.77 °C and 3082.55, respectively. Furthermore, implementing a multi-stage drying process effectively prevents internal binder migration within the porous medium and ensures even distribution of components, thereby enhancing electrode performance. This study examines the effects of different multi-stage drying schemes on the drying time and energy consumption of porous medium electrodes based on the optimal drying parameters. The optimal multi-stage drying scheme, characterized by temperature profiles of 104.77 (0–15 s) − 90 (15–44 s) − 104.77 (>44 s) °C, was proposed to achieve both reduced drying time and low energy consumption. With this scheme, the drying process of porous medium electrodes achieved a suitable drying time of 137.50 s and a low energy consumption of 285 110.09 kJ/m3. The proposed model explores the drying process and provides valuable theoretical guidance for establishing appropriate drying parameters in the actual production of lithium-ion battery electrodes.
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
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
福满財多发布了新的文献求助10
刚刚
文献狗完成签到,获得积分10
刚刚
刚刚
刚刚
安静一曲发布了新的文献求助10
刚刚
wuyuzegang应助高1采纳,获得20
刚刚
lisitian发布了新的文献求助10
1秒前
Lucas应助接受小饼干采纳,获得10
1秒前
1秒前
科研通AI6.2应助支妙采纳,获得10
1秒前
花酒发布了新的文献求助10
2秒前
NexusExplorer应助忘记的微笑采纳,获得10
2秒前
上山打老虎完成签到,获得积分10
2秒前
2秒前
2秒前
甜美小蕊发布了新的文献求助10
2秒前
和谐的强炫完成签到,获得积分10
2秒前
深情安青应助合适的半青采纳,获得10
3秒前
乐正乘风完成签到,获得积分10
3秒前
虚幻的黄蜂完成签到,获得积分10
3秒前
庾觅松发布了新的文献求助30
3秒前
3秒前
luckyhan发布了新的文献求助10
3秒前
三年科研完成签到,获得积分10
3秒前
sdad完成签到,获得积分10
4秒前
lore完成签到,获得积分10
4秒前
善学以致用应助地球采纳,获得10
4秒前
4秒前
RR发布了新的文献求助20
4秒前
Oliver完成签到,获得积分10
4秒前
4秒前
leo7发布了新的文献求助10
5秒前
liyang发布了新的文献求助10
5秒前
清新的慕凝完成签到,获得积分10
5秒前
6秒前
英俊的铭应助润润轩轩采纳,获得30
6秒前
6秒前
小马葳蕤完成签到,获得积分10
6秒前
yulinhai发布了新的文献求助10
6秒前
sdad发布了新的文献求助10
7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
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 2000
Digital Twins of Advanced Materials Processing 2000
Social Cognition: Understanding People and Events 1200
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6036384
求助须知:如何正确求助?哪些是违规求助? 7754330
关于积分的说明 16214284
捐赠科研通 5182446
什么是DOI,文献DOI怎么找? 2773519
邀请新用户注册赠送积分活动 1756745
关于科研通互助平台的介绍 1641243