ABSTRACT
Fluorescent sensors are resistant to electromagnetic interference and are electrically insulated, allowing for highly accurate measurements. Quantum dots (QDs) serve as outstanding sensing materials owing to the unique optical properties such as tunable photoluminescence (PL), excellent visible light activity, and high chemical and physical stability. In this paper, we develop an optical humidity sensor based on a QDs nanocomposite film. The film is made of polyvinyl alcohol (PVA), SiO2 microsphere (SM), and QDs through the layer-by-layer self-assembly method. The mechanism of humidity detection is moisture-induced quenching of the QDs fluorescence intensity. The results reveal that our sensor shows a good linear response to relative humidity in the range of 5% to 97%, a fast response-recovery time of 25 s and 20 s, and good repeatability for more than 50 cycles as well as high stability for over 180 days. Possessing the remarkable property, optical humidity sensors are envisaged for great potential applications in environmental monitoring.
ABSTRACT
For an energy-efficient induction machine, the life-cycle cost (LCC) usually is the most important index to the consumer. With this target, the optimization design of a motor is a complex nonlinear problem with constraints. To solve the problem, the authors introduce a united random algorithm. At first, the problem is divided into two parts, the optimal rotor slots and the optimization of other dimensions. Before optimizing the rotor slots with genetic algorithm (GA), the second part is solved with TABU algorithm to simplify the problem. The numerical results showed that this method is better than the method using a traditional algorithm.
