Shape-memory and self-healing properties of sustainable cellulosic nanofibers-based hybrid materials for novel applications

IF 5.4 1区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
GIANT Pub Date : 2024-06-05 DOI:10.1016/j.giant.2024.100299
Muhammad Yasir Khalid , Zia Ullah Arif , Ans Al Rashid , Syed Muhammad Zubair Shah Bukhari , Mokarram Hossain , Muammer Koç
{"title":"Shape-memory and self-healing properties of sustainable cellulosic nanofibers-based hybrid materials for novel applications","authors":"Muhammad Yasir Khalid ,&nbsp;Zia Ullah Arif ,&nbsp;Ans Al Rashid ,&nbsp;Syed Muhammad Zubair Shah Bukhari ,&nbsp;Mokarram Hossain ,&nbsp;Muammer Koç","doi":"10.1016/j.giant.2024.100299","DOIUrl":null,"url":null,"abstract":"<div><p>In the era of smart and sustainable technology driven by naturally occurring materials, various nanocellulose-based materials play a crucial role. Shape memory behaviour and self-healing capabilities of nanocelluloses are emerging as focal points in numerous research domains. Nanocellulose and its derivatives such as cellulose nanocrystals (CNC) and cellulose nanofibers (CNF), are currently in the limelight due to their excellent shape-memory and self-healing properties, making them suitable for multifunctional devices. In this regard, CNF, as a cutting-edge material, has spurred researchers to explore its potential in developing contemporary multifunctional and personalized health devices. Therefore, a timely and comprehensive review is essential to gain deep insights into the effectiveness of shape-memory and self-healing capabilities of CNF for multifunctional devices. Herein, we first provide a brief introduction to all nanocellulose materials. This review also depicts recent advancements and breakthroughs in the large and effective synthesis of CNF-based hybrid materials. Next, focusing on their self-healing and shape-memory performance, this review sheds new light on the advanced applications of CNF materials. Finally, perspectives on the current challenges and opportunities in this field are summarized for future researchers to gain an in-depth understanding of CNF-based smart and sustainable materials.</p></div>","PeriodicalId":34151,"journal":{"name":"GIANT","volume":"19 ","pages":"Article 100299"},"PeriodicalIF":5.4000,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666542524000638/pdfft?md5=698e0a718ccfcff0f5325d34004623f9&pid=1-s2.0-S2666542524000638-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GIANT","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666542524000638","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

In the era of smart and sustainable technology driven by naturally occurring materials, various nanocellulose-based materials play a crucial role. Shape memory behaviour and self-healing capabilities of nanocelluloses are emerging as focal points in numerous research domains. Nanocellulose and its derivatives such as cellulose nanocrystals (CNC) and cellulose nanofibers (CNF), are currently in the limelight due to their excellent shape-memory and self-healing properties, making them suitable for multifunctional devices. In this regard, CNF, as a cutting-edge material, has spurred researchers to explore its potential in developing contemporary multifunctional and personalized health devices. Therefore, a timely and comprehensive review is essential to gain deep insights into the effectiveness of shape-memory and self-healing capabilities of CNF for multifunctional devices. Herein, we first provide a brief introduction to all nanocellulose materials. This review also depicts recent advancements and breakthroughs in the large and effective synthesis of CNF-based hybrid materials. Next, focusing on their self-healing and shape-memory performance, this review sheds new light on the advanced applications of CNF materials. Finally, perspectives on the current challenges and opportunities in this field are summarized for future researchers to gain an in-depth understanding of CNF-based smart and sustainable materials.

Abstract Image

用于新型应用的可持续纤维素纳米纤维基混合材料的形状记忆和自愈合特性
在由天然材料驱动的智能和可持续技术时代,各种以纳米纤维素为基础的材料发挥着至关重要的作用。纳米纤维素的形状记忆行为和自愈能力正成为众多研究领域的焦点。纳米纤维素及其衍生物,如纤维素纳米晶体(CNC)和纤维素纳米纤维(CNF),因其优异的形状记忆和自愈性能,使其成为多功能设备的理想材料,目前正备受瞩目。在这方面,CNF 作为一种前沿材料,促使研究人员探索其在开发当代多功能和个性化健康设备方面的潜力。因此,为了深入了解 CNF 在多功能设备中的形状记忆和自修复功能的有效性,及时进行全面综述至关重要。在此,我们首先简要介绍了所有纳米纤维素材料。这篇综述还描述了最近在大规模有效合成 CNF 基混合材料方面取得的进展和突破。接下来,本综述将重点关注 CNF 材料的自愈合和形状记忆性能,为 CNF 材料的先进应用提供新的启示。最后,本综述总结了该领域当前面临的挑战和机遇,供未来研究人员深入了解基于 CNF 的智能和可持续材料。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
GIANT
GIANT Multiple-
CiteScore
8.50
自引率
8.60%
发文量
46
审稿时长
42 days
期刊介绍: Giant is an interdisciplinary title focusing on fundamental and applied macromolecular science spanning all chemistry, physics, biology, and materials aspects of the field in the broadest sense. Key areas covered include macromolecular chemistry, supramolecular assembly, multiscale and multifunctional materials, organic-inorganic hybrid materials, biophysics, biomimetics and surface science. Core topics range from developments in synthesis, characterisation and assembly towards creating uniformly sized precision macromolecules with tailored properties, to the design and assembly of nanostructured materials in multiple dimensions, and further to the study of smart or living designer materials with tuneable multiscale properties.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信