Sensing Food Quality by Free‐Standing Silicene Nanosheets: A Combined Density Functional Theory and Nonequilibrium Green's Function Method Study

Volatile organic compounds (VOCs) emitted by food products are considered markers for assessing food quality. In this work, first‐principles density functional theory and nonequilibrium green's function (NEGF) methods have been employed to model chemoresistive gas sensors based on 2D free‐standing silicene‐based nanosheets that can sense the six different VOCs emitted by standard food products. The calculations with unpassivated and fluorine passivated silicene (F‐silicene) sheets as sensor materials show that fluorine passivated silicene has significantly better sensitivity toward all six VOC molecules (acetone, dimethylsulfide, ethanol, methanol, methylacetate, and toluene). Moreover, the fluorinated silicene sensor is found to be capable of separately recognizing four VOCs, a much better performance than the r‐GO used in a recent experiment. The microscopic picture influencing the sensing capabilities of unpassivated and fluorinated silicene is analyzed from the perspectives of adsorption energy, charge transfer, and changes in the electronic structure. It is found that the better sensing ability of fluorinated silicene nanosheets can be correlated with the changes in the electronic structures near the Fermi level upon adsorption of different VOCs. The results imply that passivated silicene can work better as a sensor than r‐GO in the case of generic food VOCs. The results are important since the modeling of various 2D nanosensors can be done in a similar way for the detection of more complex VOCs emitted by specific food products.