This work presents, for the first time, an in-situ self-aligned fluidic-integrated microwave sensor for characterizing NaCl contents in NaCl-aqueous solution based on a 16-GHz bandpass combline cavity resonator. The discrimination of the NaCl concentration is achievable by determining amplitude differences and resonant frequency translations between the incident and reflected microwave signals at the input terminal of the cavity resonator based on the capacitive loading effects of the comb structure inside the cavity introduced by the NaCl solution under test. Twelve NaCl-aqueous liquid mixture samples with different NaCl concentrations ranging from 0% to 20% (0-200 mg/mL), which are generally exploited in most industrial and biomedical applications, were prepared and encapsulated inside a Teflon tube performing as a fluidic channel. The Teflon tube is subsequently inserted into the cavity resonator through two small holes, fabricated through the sidewalls of the cavity, which can be used to automatically align the fluidic subsystem inside the combline resonator considerably easing the sensor setup. Based on at least five repeated measurements, the NaCl sensor can discriminate the NaCl content of as low as 1% with the measurement accuracy of higher than 96% and the maximum standard deviation of only 0.0578. There are several significant advantages achieved by the novel NaCl sensors, e.g. high accuracy, traceability and repeatability; ease of sensor setup and integration to actual industrial and biomedical systems enabling insitu and real-time measurements; noninvasive and noncontaminative liquid solution characterization as well as superior sensor reusability due to a complete physical separation between the fluidic and microwave subsystems.

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This paper presents a 3D-printed hemispherical lens integrated with flower-shaped stub antenna for liquidmixture characterization. The proposed lens antenna is designed, fabricated, and integrated with the ultra-wideband planar antenna. A high impact polystyrene (HIPs) is selected to design the 3D-printed lens antenna by using the fused deposition modelling (FDM) technique, due to low loss 3D-printed material. The optimum the dimensions of the lens antenna are obtained by using the 3D EM Simulation CST Studio, which is used to investigate the performance of the antenna, e.g., gain, radiation pattern and reflection coefficient. To discriminate the liquid content in ethanol-water mixture, the level of the transmission coefficient (S21) is detected. The proposed sensor system offers various preferable features, e.g., non-destructive method and non-contact measurement. Five samples, e.g., 60%, 65%, 70%, 75%, and 80% ethanol in the ethanol-water mixtures, are measured and performed to generate the extraction model. The proposed sensor also offers other advantages, e.g., real-time monitoring and no life-cycle limitation.