Graphene Field Effect Transistors: A Sensitive Platform for Detecting Sarin

Recent Advances on Metal Oxide Based Sensors for Environmental Gas Pollutants Detection

Optimizing materials and associated structures for detecting various environmental gas pollutant concentrations has been a major challenge in environmental sensing technology. Semiconducting metal oxides (SMOs) fabricated at the nanoscale are a class of sensor technology in which metallic species are functionalized with various dopants to modify their chemiresistivity and crystalline scaffolding properties. Studies focused on recent advances of gas sensors utilizing metal oxide nanostructures with a special emphasis on the structure-surface property relationships of some typical n-type and p-type SMOs for efficient gas detection are presented. Strategies to enhance the gas sensor performances are also discussed. These oxide material sensors have several advantages such as ease of handling, portability, and doped-based SMO sensing detection ability of environmental gas pollutants at low temperatures. SMO sensors have displayed excellent sensitivity, selectivity, and robustness. In addition, the hybrid SMO sensors showed exceptional selectivity to some CWAs when irradiated with visible light while also displaying high reversibility and humidity independence. Results showed that TiO2 surfaces can sense 50 ppm SO2 in the presence of UV light and under operating temperatures of 298-473 K. Hybrid SMO displayed excellent gas sensing response. For example, a CuO-ZnO nanoparticle network of a 4:1 vol.% CuO/ZnO ratio exhibited responses three times greater than pure CuO sensors and six times greater than pure ZnO sensors toward H2S. This review provides a critical discussion of modified gas pollutant sensing capabilities of metal oxide nanoparticles under ambient conditions, focusing on reported results during the past two decades on gas pollutants sensing.

π-Extended Porphyrin-Phthalocyanine Heterojunction Devices Exhibiting High Ammonia Sensitivity with a Remarkable Light Effect

π-Extended porphyrins represent an attractive class of organic compounds because of their unique photophysical, optoelectronic, and physicochemical properties. Herein, cross-conjugated (Ace-PQ-Ni) and linear-conjugated (AM6) porphyrins are used to build double-layer heterojunction devices by combining them with a lutetium bisphthalocyanine complex (LuPc2). The heterojunction effect at the porphyrin-phthalocyanine interface plays a key role in the charge transport properties. Both devices exhibit exceptionally high ammonia sensitivity at room temperature and under ambient relative humidity, with limit of detection values of 156 and 115 ppb for Ace-PQ-Ni/LuPc2 and AM6/LuPc2 sensors, respectively. Interestingly, the Ace-PQ-Ni/LuPc2 and AM6/LuPc2 sensors display opposite effects upon light illumination. While the former sensors show largely decreased ammonia sensitivity under light illumination, the current variation of the latter under ammonia is remarkably enhanced with a multiplication factor of 13 and a limit of detection (LOD) of 83 ppb. The striking difference in their sensing properties upon light illumination is attributed to their different π-conjugation pathways (cross-conjugation versus linear conjugation).

Pushing Down the Limit of NH3 Detection of Graphene-Based Chemiresistive Sensors through Functionalization by Thermally Activated Tetrazoles Dimerization

An easy and cost-effective method is presented to functionalize graphene through thermally activated dimerization of 2,5-diaryltetrazoles. Consistently with the experimental spectroscopic results, theoretical calculations demonstrate that during the thermal treatment a dimerization process to tetrazine is energetically more favorable than covalent grafting. Since both the functionalization method by thermal activation and the use of tetrazoles have never been considered before to prepare graphene-based chemiresistors, this represents a promising approach to develop graphene-related sensing platforms. Five different 2,5-diaryltetrazoles have been tested here for the effective functionalization of low-defect graphene layers on silicon nitride. Based on these layers, an array of sensors has been prepared for testing upon ammonia exposure. The tests on the sensing performances clearly show sensitivity to ammonia, extending the current range of ammonia detection with a graphene-based chemiresistor down to the sub-ppm range, as results from a benchmarking with data available in the literature. Furthermore, all sensors perform better than bare graphene. Density functional theory (DFT) calculations, carried out on a model of the best performing layer of the array, provided the theoretical framework to rationalize the sensing mechanism and disclose a dual role played by the tetrazine molecules, (i) acting as ammonia concentrators and (ii) mediating the electron transfer between ammonia and graphene.

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.