School of Engineering Science, Simon Fraser University, Burnaby, British Columbia, V5A 1S6, Canada.
Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, H3G 1M8, Canada.
Adv Sci (Weinh). 2023 Apr;10(10):e2205458. doi: 10.1002/advs.202205458. Epub 2023 Jan 19.
Volatile organic compounds (VOCs) sensors have a broad range of applications including healthcare, process control, and air quality analysis. There are a variety of techniques for detecting VOCs such as optical, acoustic, electrochemical, and chemiresistive sensors. However, existing commercial VOC detectors have drawbacks such as high cost, large size, or lack of selectivity. Herein, a new sensing mechanism is demonstrated based on surface interactions between VOC and UV-excited 2D germanium sulfide (GeS), which provides an effective solution to distinguish VOCs. The GeS sensor shows a unique time-resolved electrical response to different VOC species, facilitating identification and qualitative measurement of VOCs. Moreover, machine learning is utilized to distinguish VOC species from their dynamic response via visualization with high accuracy. The proposed approach demonstrates the potential of 2D GeS as a promising candidate for selective miniature VOCs sensors in critical applications such as non-invasive diagnosis of diseases and health monitoring.
挥发性有机化合物(VOC)传感器在医疗保健、过程控制和空气质量分析等领域有着广泛的应用。目前已经有多种技术可以用于检测 VOC,例如光学、声学、电化学和化学电阻式传感器。然而,现有的商用 VOC 探测器存在成本高、体积大或选择性差等缺点。在此,我们展示了一种基于 VOC 与紫外激发二维二硫化锗(GeS)表面相互作用的新型传感机制,为区分 VOC 提供了有效的解决方案。GeS 传感器对不同 VOC 种类表现出独特的时变电阻响应,有助于识别和定性测量 VOC。此外,我们还利用机器学习通过可视化来区分 VOC 种类及其动态响应,准确率高。该方法证明了二维 GeS 作为一种有前途的候选材料,有望应用于关键领域的选择性微型 VOC 传感器,例如疾病的非侵入性诊断和健康监测。