Industrial Gases Identification Using Graphene-based Gas Sensors: NH3 and PH3 as an Example

Shirong Huang, A. Croy, L. Panes-Ruiz, V. Khavrus, B. Ibarlucea, G. Cuniberti
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Abstract

Both ammonia (NH3) and phosphine (PH3) play a significant role in an extensive range of industrial processes, while they are harmful to human health even at very low concentration. So far, a variety of gas sensors have been developed to detect them in an industrial environment aimed to protect the health of workers at their work place. Among various types of gas sensors, chemiresistive type gas sensors have attracted considerable interest due to its characteristics, such as simple fabrication, high sensitivity, high reliability, etc. Nevertheless, there are still some limitations, such as, high power consumption resulted from high operating temperatures, and most sensors are solely dedicated to an individual gas monitoring. In this work, we present the development of highly sensitive and highly discriminative graphene-based gas sensors for gas detection and identification at room temperature. Graphene is exfoliated by a liquid phase approach and functionalized by copper phthalocyanine derivate (CuPc). Leveraging machine learning techniques, graphene-based gas sensors demonstrate an excellent gas identification performance towards NH3 and PH3 at an ultralow concentration (ppb level). This work could pave the path to design highly sensitive and smart gas sensors for a wide range of gases.
基于石墨烯气体传感器的工业气体识别:以NH3和PH3为例
氨(NH3)和磷化氢(PH3)在广泛的工业过程中起着重要作用,即使浓度很低也对人体健康有害。到目前为止,已经开发了各种气体传感器,以在工业环境中检测它们,旨在保护工作场所工人的健康。在各种类型的气体传感器中,化学型气体传感器因其制作简单、灵敏度高、可靠性高等特点而引起了人们的广泛关注。然而,仍然存在一些局限性,例如,高工作温度导致的高功耗,并且大多数传感器仅用于单个气体监测。在这项工作中,我们提出了在室温下用于气体检测和识别的高灵敏度和高判别石墨烯气体传感器的开发。石墨烯通过液相法剥离,并由酞菁铜衍生物(CuPc)功能化。利用机器学习技术,基于石墨烯的气体传感器在超低浓度(ppb水平)下对NH3和PH3具有出色的气体识别性能。这项工作可以为设计高灵敏度和智能气体传感器铺平道路,用于广泛的气体。
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