Highly NH Sensitive and Selective TiCO-Based Gas Sensors: A Density Functional Theory-NEGF Study.

Ammonia (NH) detection at the early stage is an important precaution for human health and agricultural production. However, conventional sensing materials are difficult to achieve all the targeted operational performances such as low power consumption and high selectivity. MXenes are a type of graphene-like emergent material equipped with abundant surface sites benefiting gas-sensing applications. In the work, we discuss the sensing performance of TiCO to anticipate harmful and polluting NH gases by density functional theory and nonequilibrium Green's function. The adsorption geometry, charge difference density, and partial density of states are discussed to understand the nature of interactions between gas molecules and TiCO. The theoretical results show that only NH adsorbs onto the nanosheet through chemisorption. Then, a two-electrode TiCO-based gas sensor device is built to unravel the transport properties. Current under different bias voltages indicates the TiCO-based sensor could maintain extremely high sensitivity, demonstrating that TiCO has great potential for the NH sensor with high selectivity, excellent sensitivity, and low energy consumption. Upon external electric fields, the adsorption energy and charge transfer can be tuned effectively, suggesting that TiCO is a versatile agent as an ammonia-sensing material.