Surface‐Engineering Cellulose Nanofibers via In Situ PEDOT Polymerization for Superior Thermoelectric Properties

材料科学 佩多:嘘 纳米纤维素 原位聚合 聚合 纳米纤维 复合材料 纳米技术 聚合物 化学工程 纤维素 工程类
作者
Yuxuan Xia,Jiahe Li,Ze Sheng Ji,Kexin Zhou,Yu Zhang,Ying Liu,Sai‐Wing Tsang,Ka Wai Wong,Qingyue Wang,Wenjun Wang,Andreu Cabot,Xuan Yang,Khak Ho Lim
出处
期刊:Advanced Materials [Wiley]
卷期号:37 (38): e2506338-e2506338 被引量:20
标识
DOI:10.1002/adma.202506338
摘要

Abstract Cellulose nanofibrils (CNFs) are abundant and possess exceptional mechanical strength, but their intrinsic electrical insulation limits their application in wearable electronics. In this study, a versatile methodology is presented to produce highly conductive and durable CNFs through electrostatic potential‐enhanced in situ polymerization of poly(3,4‐ethylenedioxythiophene) (PEDOT). Guided by molecular dynamics simulations, electrostatic interactions are controlled by tailoring the chain length of PEDOT, achieving homogeneous polymerization. Compared to conventional polymerization and blending methods, this approach prevented the self‐aggregation of PEDOT crystallites, which would otherwise localize charge carriers and hinder electrical transport, as confirmed by scanning Kelvin probe microscope (SKPM). These fibers can leverage nanocellulose's capillary effects to rearrange PEDOT crystallites, thereby boosting electrical conductivity by 5 orders of magnitude over suboptimal samples. The conductive nanocellulose paper achieves superior electrical conductivity (91 S cm −1 ) and durability, retaining 90% of electrical properties over 2000 bending cycles, 5000 abrasion tests, and prolonged wet‐heat aging, freezing, and UV aging, while also demonstrating stable thermoelectric performance with power factor exceeding 3.8 µW mK −2 and a promising device output of 46.6 nW. These findings advance the conventional notion that charge‐transporting nanocellulose can only be obtained by carbonization, graphitization, or physical blending with conductive components, which further boosts its potential for wearable applications.
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
芝士就是力量完成签到,获得积分10
刚刚
万能图书馆应助DM采纳,获得10
刚刚
1秒前
小马甲应助XuBo采纳,获得10
2秒前
3秒前
doctorbba发布了新的文献求助10
4秒前
7秒前
子时过完成签到,获得积分10
7秒前
Zoey完成签到,获得积分10
8秒前
9秒前
鱼羊明完成签到 ,获得积分10
11秒前
水告发布了新的文献求助10
12秒前
yy关闭了yy文献求助
13秒前
HE发布了新的文献求助10
13秒前
泪西瓜完成签到,获得积分10
13秒前
15秒前
16秒前
坚强长颈鹿完成签到 ,获得积分10
16秒前
17秒前
19秒前
19秒前
20秒前
8R60d8应助vbmc采纳,获得10
20秒前
科研通AI6.4应助絮1111采纳,获得10
21秒前
23秒前
23秒前
23秒前
礼临渊完成签到,获得积分10
24秒前
24秒前
任性的无春完成签到 ,获得积分10
25秒前
田田完成签到 ,获得积分10
25秒前
26秒前
26秒前
26秒前
26秒前
27秒前
科研小猪发布了新的文献求助10
27秒前
洼地的浮游生物完成签到 ,获得积分10
27秒前
剁椒鱼头发布了新的文献求助10
28秒前
28秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 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
Molecular Mechanisms of Photosynthesis, 4th Edition 1000
Organic Reactions, Volume 116 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Reading and Understanding Health Research 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 7252133
求助须知:如何正确求助?哪些是违规求助? 8874534
关于积分的说明 18732619
捐赠科研通 6932127
什么是DOI,文献DOI怎么找? 3199633
关于科研通互助平台的介绍 2374362
邀请新用户注册赠送积分活动 2174212