Conduction mechanism analysis and modeling of different gas diffusion layers for PEMFC to improve their bulk conductivities via microstructure design

微观结构 热传导 扩散 机制(生物学) 材料科学 气体扩散 质子交换膜燃料电池 热力学 燃料电池 复合材料 化学工程 工程类 物理 量子力学
作者
Lingfeng Ye,Diankai Qiu,Linfa Peng,Xinmin Lai
出处
期刊:Applied Energy [Elsevier BV]
卷期号:362: 122987-122987 被引量:2
标识
DOI:10.1016/j.apenergy.2024.122987
摘要

Increasing the conductivity of gas diffusion layers (GDLs) is an important way to improve the output performance of polymer electrolyte membrane fuel cells (PEMFCs). However, the complex porous fiber structures of GDLs significantly enhances the difficulty of quantitatively altering their conductivity which is determined by the carbon fibers and the conduction characteristics between fibers. In addition, the microstructures of various types of GDLs are different. Thus, it is a considerable challenge to explore the conductive mechanisms of these porous materials and optimize their structures to reduce their bulk resistances. In this work, a mathematical graph theory model that applies to the through-plane (T-P) bulk resistance prediction of two types of commonly used GDLs, carbon paper and carbon felt, is established to explain their different micro conduction mechanisms in depth. In addition to the number of fiber contact points, their distribution, as well as the resistance of the carbon fibers, are all important factors affecting the T-P conductivity. Optimizing fiber density and fiber diameter can significantly improve the T-P conductivity of carbon paper. In comparison, making the structure of carbon felt more compact so that the distribution of its contact points in the T-P direction can be more uniform will be more effective for the reduction of its T-P bulk resistance. Meanwhile, the T-P bulk resistance of carbon paper can also be effectively improved by optimizing the content and distribution of the binders. A method to decline the bulk resistance of carbon paper by aggregating the binders in the in-plane (IP) direction is proposed. The simulation results show that it can reduce the T-P bulk resistance of carbon paper by about 19.9% at a compressive stress of 1.5 MPa. This study provides further guidance for optimizing the structural designs of GDLs to optimize their conduction performance.
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
Vaxer发布了新的文献求助10
刚刚
Vaxer发布了新的文献求助30
刚刚
Vaxer发布了新的文献求助10
刚刚
1秒前
gavin完成签到,获得积分10
1秒前
Vaxer发布了新的文献求助10
1秒前
Vaxer发布了新的文献求助10
1秒前
1秒前
Vaxer发布了新的文献求助10
1秒前
Vaxer发布了新的文献求助10
1秒前
1秒前
Vaxer发布了新的文献求助10
1秒前
Vaxer发布了新的文献求助10
2秒前
碧蓝的半芹完成签到,获得积分10
2秒前
3秒前
Vaxer发布了新的文献求助10
3秒前
Vaxer发布了新的文献求助10
3秒前
Vaxer发布了新的文献求助10
4秒前
汉堡包应助风趣的扬青采纳,获得10
4秒前
YLS发布了新的文献求助10
4秒前
Vaxer发布了新的文献求助10
5秒前
Vaxer发布了新的文献求助10
5秒前
5秒前
Vaxer发布了新的文献求助10
5秒前
6秒前
滕茹嫣发布了新的文献求助10
6秒前
白日梦想家完成签到,获得积分10
6秒前
贪玩的秋柔应助Dawn采纳,获得15
8秒前
方人也发布了新的文献求助30
10秒前
Bai发布了新的文献求助10
10秒前
研友_8KX15L发布了新的文献求助10
11秒前
11秒前
13秒前
秋秋完成签到 ,获得积分10
13秒前
14秒前
yi5feng完成签到,获得积分10
14秒前
HEAR应助SamYang采纳,获得10
15秒前
风趣的巨人完成签到 ,获得积分10
15秒前
热心的绿柳完成签到,获得积分20
16秒前
打打应助原野小年采纳,获得10
17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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
CLSI M100 Performance Standards for Antimicrobial Susceptibility Testing 36th edition 400
How to Design and Conduct an Experiment and Write a Lab Report: Your Complete Guide to the Scientific Method (Step-by-Step Study Skills) 333
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6363522
求助须知:如何正确求助?哪些是违规求助? 8177450
关于积分的说明 17232877
捐赠科研通 5418629
什么是DOI,文献DOI怎么找? 2867141
邀请新用户注册赠送积分活动 1844328
关于科研通互助平台的介绍 1691850