RESUMEN
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.
RESUMEN
In this paper, we report multiplex SERS based VOCs detection with a leaning nano-pillar substrate. The VOCs analyte molecules adsorbed at the tips of the nano-pillars produced SERS signal due to the field enhancement occurring at the localized surface plasmon hot spots between adjacent leaning nano-pillars. In this experiment, detections of acetone and ethanol vapor at different concentrations were demonstrated. The detection limits were found to be 0.0017 ng and 0.0037 ng for ethanol and acetone vapor molecules respectively. Our approach is a non-labeling method such that it does not require the incorporation of any chemical sensing layer for the enrichment of gas molecules on sensor surface. The leaning nano-pillar substrate also showed highly reproducible SERS signal in cyclic VOCs detection, which can reduce the detection cost in practical applications. Further, multiplex SERS detection on different combination of acetone and ethanol vapor was also successfully demonstrated. The vibrational fingerprints of molecular structures provide specific Raman peaks for different VOCs contents. To the best of our knowledge, this is the first multiplex VOCs detection using SERS. We believe that this work may lead to a portable device for multiplex, specific and highly sensitive detection of complex VOCs samples that can find potential applications in exhaled breath analysis, hazardous gas analysis, homeland security and environmental monitoring.