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Graphene quantum dot-based sensors have demonstrated significant promise in the detection of dangerous air pollutants that harm the environment and endanger human health. The efficient trapping and separation of numerous hazardous gases from the environment have recently garnered substantial experimental and computational attention. Nitrogen doping significantly tunes the properties of graphene quantum dots and expands their potential applications. In this study, we have investigated the sensing mechanism of pristine graphene quantum dots (GQD) along with pyridinic nitrogen-doped defective graphene systems, i.e., GQD-DV/N4, for various hazardous gases, such as arsine (AsH3), hydrogen sulfide (H2S), formaldehyde (HCHO), hydrogen cyanide (HCN), and phosphine (PH3). Our study suggests that nitrogen doping in GQDs can significantly increase the adsorption strength for these hazardous gases. Our in-depth analysis proposes that adsorption is governed by the presence of hydrogen bonds between the hydrogen in the adsorbates and the nitrogen in the adsorbents. These findings should persuade scientists to rationally and methodically modify surfaces to serve as sensors for the detection of hazardous gases. [ABSTRACT FROM AUTHOR]

In this study, a full-scale storage tank was established to investigate the potential risks of leakage accident. We have developed a series of leak scenarios that close to real accidents and have divided the ambient areas according to relevant regulations. Considering the variety and complexity of real-life accident scenarios, the presented work revealed the combined effect of source release intensity and ambient wind speed on dispersion features by classifying leakage scenarios into active or passive release. The environmental hazards in each area is evaluated under various leak scenarios. The results show that when the approaching wind speed is low, the leakage on the windward side is the most dangerous release pattern. With the increase of the wind speed, the case with jet angle perpendicular to the incoming wind produces the largest cloud volume. Top release is the least dangerous way among the studied leak scenarios. However, the results illustrate that under some release angles, the cloud volume near the tank is not sensitive to wind speed. In leak accidents, quantitatively analysis reveals that the commonly used dimensionless concentrations ( K c ) cannot be used as a suitable parameter to discuss the concentration field except under top/leeward passive release conditions. This study will be beneficial to on-site rescue and decision-making when leakage accidents occur and provide reasonable suggestions for subsequent research on the environmental impact of container leakage and the diffusion of pollutants. [ABSTRACT FROM AUTHOR]

Unsatisfactory sensing selectivity remains a challenging issue for zirconia-based gas sensors and severely restrains their wide application. In view of the response selectivity for the amperometric sensor can be simply controlled by the applied bias voltage, we proposed the following strategy: operating the sensor at various bias voltage and disparate response patterns is expected; through processing these response patterns with pattern recognition algorithm, response selectivity of the sensor would be further promoted. Interestingly, research results indicate that bias voltage remarkably affects the electrocatalytic activity to each examined hazardous gas and indirectly controls the sensing behavior of the resultant sensor. In combining with principle component analysis algorithm, the sensor operated at different bias voltage (− 75, 0, 35, and 75 mV) demonstrates acceptable performance in discriminating hazardous gas. Such satisfactory sensing behavior discloses the potential future of differentiating gas mixture with an amperometric gas sensor by simply adjusting the applied bias voltage. [ABSTRACT FROM AUTHOR]