Enhanced comprehensive magnetic refrigeration performance in La0.8Ce0.2Fe11.7Si1.3H by incorporation of graphene

石墨烯 磁制冷 制冷 材料科学 纳米技术 磁场 热力学 物理 磁化 量子力学
作者
Zhishuai Wang,Naikun Sun,Shilin Yu,Xinguo Zhao,Jiaohong Huang,Yingde Zhang,Yingwei Song,Zhidong Zhang
出处
期刊:Journal of Rare Earths [Elsevier BV]
卷期号:43 (5): 1003-1009 被引量:4
标识
DOI:10.1016/j.jre.2024.06.009
摘要

Thus far, metal-bonding has presented high efficacy in improving the mechanical, thermal conductive, and anti-corrosion properties of La(Fe,Si)13-based hydrides. However, to ensure high performance, the proportion of metal bonders has to be as high as 20 wt%, thereby significantly weakening the magnetocaloric effect (MCE). In this work, small amounts of graphene nanosheets (up to 2 wt%) with high thermal conductivity and specific surface area were incorporated into the La0.8Ce0.2Fe11.7Si1.3Hy matrix through a cold-pressing and sintering process. X-ray diffraction analysis indicates that carbon from graphene can easily diffuse into the lattice of La(Fe,Si)13 main phase as an interstitial atom, resulting in a significant increase of the lattice constant accompanied by a significant decrease of the Curie temperature and H content of the composites. While 0.3 wt% graphene doping only has minor improvements in the thermal conductivity λ and corrosion resistance of the parent La0.8Ce0.2Fe11.7Si1.3Hy, further increase of graphene content to 1 wt% causes a significant increase of λ from 1.4 W/(m·K) for the parent material to ∼2 W/(m·K) and a decrease of corrosion current density from 1.43×10‒5 to 9.63×10‒6 A/cm2. When the graphene content is lower than 0.3 wt%, the large MCE does not significantly deteriorate. In 0–1.5 T, the maximal magnetic-entropy change ΔSm of 11.5 J/(kg·K) at 336 K for the parent material decreases to 8.2 J/(kg·K) at 306 K for the 2 wt% graphene-doped composite.
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
111发布了新的文献求助10
刚刚
1秒前
guogou完成签到,获得积分10
2秒前
2秒前
jingjing发布了新的文献求助20
2秒前
dde发布了新的文献求助10
2秒前
2秒前
2秒前
123发布了新的文献求助10
3秒前
5秒前
香蕉觅云应助SPt采纳,获得10
6秒前
Akim应助Tsuki采纳,获得10
6秒前
程雪霞完成签到,获得积分10
6秒前
半夏微凉发布了新的文献求助10
7秒前
张欢馨应助CC采纳,获得10
7秒前
小二郎应助CC采纳,获得10
7秒前
8秒前
大模型应助有我ID随机吗采纳,获得10
8秒前
8秒前
9秒前
张欢馨应助stupid采纳,获得10
10秒前
linlan发布了新的文献求助30
10秒前
Julie完成签到 ,获得积分0
10秒前
稍息门牙发布了新的文献求助20
12秒前
12秒前
nnnn发布了新的文献求助10
12秒前
opp完成签到,获得积分10
12秒前
13秒前
火星上藏鸟完成签到,获得积分10
13秒前
14秒前
顾矜应助xxrj采纳,获得10
14秒前
luheian发布了新的文献求助10
14秒前
CipherSage应助夏侯初采纳,获得10
14秒前
阿诺发布了新的文献求助10
15秒前
15秒前
15秒前
15秒前
15秒前
15秒前
15秒前
高分求助中
Markov Chain Monte Carlo 10000
(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
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7583250
求助须知:如何正确求助?哪些是违规求助? 9161970
关于积分的说明 19605650
捐赠科研通 7165315
什么是DOI,文献DOI怎么找? 3266226
关于科研通互助平台的介绍 2431164
邀请新用户注册赠送积分活动 2257588