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Exhaled breath analysis by nanosensors is a workable and rapid manner to diagnose lung cancer in the early stage. In this paper, we proposed Al-doped MoSe2 (Al–MoSe2) as a promising biosensor for sensing three typically exhaled volatile organic compounds (VOCs) of lung cancer, namely, C3H4O, C3H6O, and C5H8, using the density functional theory (DFT) method. Single Al atom is doped on the Se-vacancy site of the MoSe2 surface, which behaves as an electron-donor and enhances the electrical conductivity of the nanosystem. The adsorption and desorption performances, electronic behavior, and the thermostability of the Al–MoSe2 monolayer are conducted to fully understand its physicochemical properties as a sensing material. The results indicate that the Al–MoSe2 monolayer shows admirable sensing performances with C3H4O, C3H6O, and C5H8 with responses of −85.7, −95.6, and −96.3%, respectively. Also, the desirable adsorption performance and the thermostability endow with the Al–MoSe2 monolayer with good sensing and desorbing behaviors for the recycle detection of three VOCs. We are hopeful that the results in this paper could provide some guidance to the experimentalists fulfilling their exploration in the practical application, which can also broaden the exploration of transition-metal dichalcogenides (TMDs) in more fields as well.

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This paper describes a novel trajectory planning algorithm for an unmanned aerial vehicle (UAV) under the constraints of system positioning accuracy. Due to the limitation of the system structure, a UAV cannot accurately locate itself. Once the positioning error accumulates to a certain degree, the mission may fail. This method focuses on correcting the error during the flight process of a UAV. The improved genetic algorithm (GA) and A* algorithm are used in trajectory planning to ensure the UAV has the shortest trajectory length from the starting point to the ending point under multiple constraints and the least number of error corrections.