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
科研通AI6.1应助malele采纳,获得10
刚刚
billevans完成签到,获得积分10
1秒前
1秒前
科研通AI6.1应助超帅刘采纳,获得10
1秒前
yzm发布了新的文献求助10
2秒前
秘密完成签到,获得积分10
2秒前
vitor完成签到,获得积分10
3秒前
4秒前
4秒前
研友_maths完成签到 ,获得积分10
4秒前
5秒前
Easonluo8完成签到,获得积分10
5秒前
邪恶土拨鼠应助lz采纳,获得10
5秒前
王全发布了新的文献求助10
5秒前
嘤嘤怪完成签到 ,获得积分10
5秒前
深情安青应助林二车娜姆采纳,获得10
8秒前
张艺完成签到,获得积分10
9秒前
FashionBoy应助伤心小狗采纳,获得10
9秒前
11秒前
情怀应助wh采纳,获得10
11秒前
hiiamwu发布了新的文献求助10
11秒前
11秒前
mumu完成签到,获得积分10
12秒前
yu完成签到,获得积分10
13秒前
iiiio发布了新的文献求助10
14秒前
阿铭完成签到 ,获得积分10
14秒前
labi完成签到 ,获得积分10
15秒前
16秒前
superhero完成签到,获得积分10
16秒前
冷酷的鸿煊关注了科研通微信公众号
16秒前
小乖完成签到,获得积分10
17秒前
张艺发布了新的文献求助10
17秒前
17秒前
Why完成签到,获得积分10
18秒前
微笑爆米花应助空空采纳,获得10
18秒前
英俊萝完成签到,获得积分10
19秒前
19秒前
Herrily完成签到,获得积分10
20秒前
21秒前
21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
Salmon nasal cartilage-derived proteoglycan complexes influence the gut microbiota and bacterial metabolites in mice 2000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1500
Cowries - A Guide to the Gastropod Family Cypraeidae 1200
ON THE THEORY OF BIRATIONAL BLOWING-UP 666
Signals, Systems, and Signal Processing 610
LASER: A Phase 2 Trial of 177 Lu-PSMA-617 as Systemic Therapy for RCC 520
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 6382143
求助须知:如何正确求助?哪些是违规求助? 8194369
关于积分的说明 17322526
捐赠科研通 5435835
什么是DOI,文献DOI怎么找? 2875084
邀请新用户注册赠送积分活动 1851720
关于科研通互助平台的介绍 1696352