Influence of chamber design on the gas sensing performance of graphene field-effect-transistor

Design Principles From Natural Olfaction for Electronic Noses

Natural olfactory systems possess remarkable sensitivity and precision beyond what is currently achievable by engineered gas sensors. Unlike their artificial counterparts, noses are capable of distinguishing scents associated with mixtures of volatile molecules in complex, typically fluctuating environments and can adapt to changes. This perspective examines the multifaceted biological principles that provide olfactory systems their discriminatory prowess, and how these ideas can be ported to the design of electronic noses for substantial improvements in performance across metrics such as sensitivity and ability to speciate chemical mixtures. The topics examined herein include the fluid dynamics of odorants in natural channels; specificity and kinetics of odorant interactions with olfactory receptors and mucus linings; complex signal processing that spatiotemporally encodes physicochemical properties of odorants; active sampling techniques, like biological sniffing and nose repositioning; biological priming; and molecular chaperoning. Each of these components of natural olfactory systems are systmatically investigated, as to how they have been or can be applied to electronic noses. While not all artificial sensors can employ these strategies simultaneously, integrating a subset of bioinspired principles can address issues like sensitivity, drift, and poor selectivity, offering advancements in many sectors such as environmental monitoring, industrial safety, and disease diagnostics.

Effect of Measurement System Configuration and Operating Conditions on 2D Material-Based Gas Sensor Sensitivity

Gas sensors applied in real-time detection of toxic gas leakage, air pollution, and respiration patterns require a reliable test platform to evaluate their characteristics, such as sensitivity and detection limits. However, securing reliable characteristics of a gas sensor is difficult, owing to the structural difference between the gas sensor measurement platform and the difference in measurement methods. This study investigates the effect of measurement conditions and system configurations on the sensitivity of two-dimensional (2D) material-based gas sensors. Herein, we developed a testbed to evaluate the response characteristics of MoS₂-based gas sensors under a NO₂ gas flow, which allows variations in their system configurations. Additionally, we demonstrated that the distance between the gas inlet and the sensor and gas inlet orientation influences the sensor performance. As the distance to the 2D gas sensor surface decreased from 4 to 2 mm, the sensitivity of the sensor improved to 9.20%. Furthermore, when the gas inlet orientation was perpendicular to the gas sensor surface, the sensitivity of the sensor was the maximum (4.29%). To attain the optimum operating conditions of the MoS₂-based gas sensor, the effects of measurement conditions, such as gas concentration and temperature, on the sensitivity of the gas sensor were investigated.

Drone-Mountable Gas Sensing Platform Using Graphene Chemiresistors for Remote In-Field Monitoring

We present the design, fabrication, and testing of a drone-mountable gas sensing platform for environmental monitoring applications. An array of graphene-based field-effect transistors in combination with commercial humidity and temperature sensors are used to relay information by wireless communication about the presence of airborne chemicals. We show that the design, based on an ESP32 microcontroller combined with a 32-bit analog-to-digital converter, can be used to achieve an electronic response similar, within a factor of two, to state-of-the-art laboratory monitoring equipment. The sensing platform is then mounted on a drone to conduct field tests, on the ground and in flight. During these tests, we demonstrate a one order of magnitude reduction in environmental noise by reducing contributions from humidity and temperature fluctuations, which are monitored in real-time with a commercial sensor integrated to the sensing platform. The sensing device is controlled by a mobile application and uses LoRaWAN, a low-power, wide-area networking protocol, for real-time data transmission to the cloud, compatible with Internet of Things (IoT) applications.