Facile Design of Highly Stretchable and Conductive Crumpled Graphene/NiS2 Films for Multifunctional Applications.

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL Small Methods Pub Date : 2025-01-09 DOI:10.1002/smtd.202401965
Kangwei Weng, Qiji Jing, Jindong Gao, Weiguo Wang, Chen Zhang, Jun Wang, Huanyu Cheng, Cheng Zhang
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引用次数: 0

Abstract

The cost-effective and scalable synthesis and patterning of soft nanomaterial composites with improved electrical conductivity and mechanical stretchability remains challenging in wearable devices. This work reports a scalable, low-cost fabrication approach to directly create and pattern crumpled porous graphene/NiS2 nanocomposites with high mechanical stretchability and electrical conductivity through laser irradiation combined with electrodeposition and a pre-strain strategy. With modulated mechanical stretchability and electrical conductivity, the crumpled graphene/NiS2 nanocomposite can be readily patterned into target geometries for application in a standalone stretchable sensing platform. By leveraging the electrical energy harvested from the kinetic motion from wearable triboelectric nanogenerator (TENG) and stored in micro-supercapacitor arrays (MSCAs) to drive biophysical sensors, the system is demonstrated to monitor human motions, body temperature, and toxic gas in the exposed environment. The material selections, design strategies, and fabrication approaches from this study provide functional nanomaterial composites with tunable properties for future high-performance bio-integrated electronics.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
期刊最新文献
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