RESUMO
In this paper, we present an entirely simulation-based method to predict the performance of a complete rectenna system that includes all its components: the receiving antenna, the matching circuits between the antenna and the rectification circuit, and the load circuit. Whereas previous efforts to predict the performance of a rectenna system subdivided the system into the antenna part (radiation to AC power conversion) and the circuit part (AC power to DC power conversion), and made assumptions about the performance of the non-linear part of the rectenna based on a specified power level and frequency, in this method, the radiation part of the system is incorporated into the simulation by using Thevenin theorem. The method proposed in this work enables the rectenna designer to predict the performance of the complete rectenna system, at the design stage, for variation in the incident field's power density, angle of incidence, and operating frequency. Such performance prediction was not available before. Furthermore, the proposed method enables the rectenna designers to optimize the entire system over a portion of or the entire range of the operating frequency. Experimental results are provided to demonstrate the accuracy of the method.
RESUMO
As a result of the risks that waterborne bacteria bring to the human body, identifying them in drinking water has become a global concern. In this article, a highly sensitive surface plasmon resonance (SPR) biosensor consisting of prism, Ag, graphene, affinity layer and sensing medium is proposed for rapid detection of the waterborne bacteria. Four SPR-based sensors are first studied with the structures prism/Ag/sensing medium, prism/Ag/affinity layer/sensing medium, prism/Ag/graphene/sensing medium, and prism/Ag/graphene/affinity layer/sensing medium. The latter structure is found to have the highest sensitivity so it is considered for further investigations. Four different commonly used prisms are then demonstrated which are N-FK51A, 2S2G, SF10 and BK7. The structure with the prism N-FK51A is found to correspond to the highest sensitivity so it is considered for further investigations. The structure parameters are then optimized. The proposed SPR sensor can achieve high sensitivity of about 221.63 °/RIU for Escherichia coli and 178.12 °/RIU for Vibrio cholera bacteria with an average value of 199.87 °/RIU. We believe that the proposed structure will open a new window in the field of microorganism detections.