Emergence of MXene–Polymer Hybrid Nanocomposites as High‐Performance Next‐Generation Chemiresistors for Efficient Air Quality Monitoring

化学电阻器 MXenes公司 纳米技术 材料科学 灵活性(工程) 纳米材料 计算机科学 系统工程 工艺工程 工程类 统计 数学
作者
Vishal Chaudhary,Naveed Ashraf,Mohammad Khalid,Rashmi Walvekar,Ya Yang,Ajeet Kaushik,Yogendra Kumar Mishra
出处
期刊:Advanced Functional Materials [Wiley]
卷期号:32 (33) 被引量:126
标识
DOI:10.1002/adfm.202112913
摘要

Abstract Air contamination is one of the foremost concerns of environmentalists worldwide, which has elevated global public health concerns for monitoring air contaminants and implementing appropriate safety policies. These facts have generated nascent global demand for exploring sustainable and translational strategies required to engineer affordable, intelligent, and miniaturized sensors because commercially available sensors lack lower detection limits, room temperature operation, and poor selectivity. The state‐of‐the‐art sensors are concerned with architecting advanced nanomaterials to achieve desired sensing performance. Recent studies demonstrate that neither pristine metal carbides/nitrides (MXenes) nor polymers (P) can address these practical challenges. However, synergistic combinations of various precursors as hybrid‐nanocomposites (MXP‐HNCs) have emerged as superior sensing materials to develop next‐generation intelligent environmental, industrial, and biomedical sensors. The expected outcomes could be manipulative due to optimizing physicochemical and morphological attributes like tunable interlayer‐distance, optimum porosity, enlarged effective surface area, rich surface functionalities, mechanical flexibility, and tunable conductivity. This review intends to detail a comprehensive summary of the advancements in state‐of‐the‐art MXP‐HNCs chemiresistors. Moreover, the underlying sensing phenomenon, chemiresistor architecture, and their monitoring performance are highlighted. Besides, an overview of challenges, potential solutions, and prospects of MXP‐HNCs as next‐generation intelligent field‐deployable sensors with the integration of IoT and AI are outlined.

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
Dwen发布了新的文献求助10
刚刚
小晖晖完成签到,获得积分10
刚刚
小狮子完成签到 ,获得积分10
1秒前
KJ驳回了果果123应助
1秒前
沐沐发布了新的文献求助10
1秒前
及时的大麦非常完成签到,获得积分10
1秒前
坚定尔曼完成签到,获得积分10
1秒前
lanlan完成签到,获得积分10
2秒前
2秒前
3秒前
帅气36发布了新的文献求助10
3秒前
3秒前
ggg发布了新的文献求助20
3秒前
摘希完成签到,获得积分10
4秒前
sanmu完成签到,获得积分10
4秒前
lin完成签到,获得积分10
4秒前
兴奋的煎饼完成签到 ,获得积分10
4秒前
Fred发布了新的文献求助30
5秒前
lanlan发布了新的文献求助10
5秒前
淡然梦柏完成签到,获得积分10
5秒前
七七七完成签到,获得积分10
5秒前
嘿嘿完成签到,获得积分10
5秒前
6秒前
yiyiii发布了新的文献求助10
6秒前
7秒前
科研通AI6.4应助切克闹采纳,获得10
7秒前
8秒前
可乐完成签到,获得积分10
8秒前
果冻发布了新的文献求助10
8秒前
四观人完成签到,获得积分10
8秒前
shain完成签到,获得积分10
8秒前
9秒前
fff发布了新的文献求助10
10秒前
10秒前
10秒前
10秒前
害羞擎宇完成签到,获得积分10
11秒前
77发布了新的文献求助10
11秒前
excellent发布了新的文献求助10
11秒前
11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
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Navigating Normative Orders. Interdisciplinary Perspectives 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 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 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7761400
求助须知:如何正确求助?哪些是违规求助? 9306418
关于积分的说明 20294439
捐赠科研通 7345946
什么是DOI,文献DOI怎么找? 3313135
关于科研通互助平台的介绍 2463437
邀请新用户注册赠送积分活动 2327377