The detection and monitoring of air-polluting gases such as carbon monoxide (CO), nitrogen oxides (NOx), and sulfur oxides (SOx) are very important because these gases are toxic and harmful to ecosystems and human health. Therefore, there is a need to develop high-performance gas sensors to detect toxic gases. In this sense, graphene-based materials are promising for use as toxic gas sensors. Researchers do their best to build sensors with low detection limits, high sensitivity, and high selectivity. In this project, we use high-throughput density functional computation to screen the sensor properties of target gases adsorbed on functionalized graphene. Three different analyzes were used, including electron work function, excess depletion, and Bader charge analysis. We conclude that there is a strong correlation between oxygen concentration and gas binding energy. Also, changes in work function and total charge on gas absorption show similar trends.
The detection and monitoring of air-polluting gases such as carbon monoxide (CO), nitrogen oxides (NOx), and sulfur oxides (SOx) are very important because these gases are toxic and harmful to ecosystems and human health. Therefore, there is a need to develop high-performance gas sensors to detect toxic gases. In this sense, graphene-based materials are promising for use as toxic gas sensors. Researchers do their best to build sensors with low detection limits, high sensitivity, and high selectivity. In this project, we use high-throughput density functional computation to screen the sensor properties of target gases adsorbed on functionalized graphene. Three different analyzes were used, including electron work function, excess depletion, and Bader charge analysis. We conclude that there is a strong correlation between oxygen concentration and gas binding energy. Also, changes in work function and total charge on gas absorption show similar trends.