Defect Engineered Few Layered MoS2 for Human-Machine Interface.

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Raksha D Salian, Subhendu Mishra, Chinmayee Chowde Gowda, Ranjan Kumar Barik, Abhishek Kumar Singh, Chandra Sekhar Tiwary, Partha Kumbhakar
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引用次数: 0

Abstract

Ultrasensitive flexible devices have huge applications in many areas, like healthcare monitoring, human-machine interaction, and wearable technology. However, improving the sensitivity of these devices is still challenging. In the current study, a flexible non-contact sensing system is designed with a human-machine interface using defect-engineered, few-layered Molybdenum disulfide (MoS2). The fabricated sensors show high sensitivity when monitoring proximity, humidity, and in-plane applied strain. The output performance demonstrates the influence of surface defects, which greatly impact the average surface charge of the nanosheets. The experimental measurements and in-detail density functional theoretical (DFT) calculation further reveal surface charge variations on the basal planes that correlate with topographic defects and increase sensitivity. The electrical signals for different gestures of human hands are used to illustrate the identification of multidirectional bending and sliding events. These findings will contribute to understanding the effect of surface defects that play an important role in sensing applications with human-machine interface.

人机界面设计缺陷少层MoS2。
超灵敏的柔性设备在许多领域都有巨大的应用,比如医疗监控、人机交互和可穿戴技术。然而,提高这些设备的灵敏度仍然具有挑战性。在目前的研究中,采用缺陷工程、少层二硫化钼(MoS2)设计了一个灵活的非接触式传感系统,具有人机界面。该传感器在监测接近度、湿度和面内施加应变时具有很高的灵敏度。输出性能表明,表面缺陷对纳米片的平均表面电荷有很大的影响。实验测量和详细的密度泛函理论(DFT)计算进一步揭示了基面上的表面电荷变化与地形缺陷相关,并增加了灵敏度。用不同手势的电信号来说明多向弯曲和滑动事件的识别。这些发现将有助于理解在人机界面传感应用中起重要作用的表面缺陷的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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.
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