Master's Theses

A microstrip line split ring resonator (SRR) sensor is introduced for liquid profiling applications. Three sensors design are made to compatible with 2.4 GHz, 3.5 GHz, and 5 GHz frequencies, broadening its usability across different frequency ranges. The sensor is designed and simulated using ANSYS HFSS by implementing a microstrip transmission line with two identical SRRs on its sides. Differential permittivity sensing is performed by loading different dielectric liquid samples onto the SRRs. For fabrication, 3D-printing stereolithography (SLA) technology is employed due to its simplicity, low cost, and the ability to use high-temperature resin. Once printed, the sensor undergoes a metallization process by depositing a titanium and copper seed layer, followed by copper electroplating. Various Ti-Cu sputtering times are studied to determine the optimal deposition parameters for sensor creation. During the testing phase, the effects of different titanium sputtering time periods on the electrical conductivity, deposited conductive layer thickness and surface roughness of the 3Dprinted substrate are investigated. This step is crucial for establishing the optimized fabrication process required to produce high-quality SRR sensors. The sensor's working frequency is tested via vector network analyzed VNA and compared with the simulation results to validate the design accuracy. Following this, the resonance frequency response of the sensor when loaded with different dielectric materials is analyzed. This testing phase aims to study the sensor's sensitivity and its capability to distinguish between various dielectric materials for material profiling application. The sensors only necessitate a minimal sample volume for detection during testing. Any changes in the sample loading induce a shift in the resonance frequency of the SRRs, which is meticulously monitored to profile the samples. Experimental results demonstrate that the proposed 3D-printed SRR sensors exhibit excellent performance and sensitivity. Fabricated using an optimized process involving 35 minutes of Ti deposition, 30 minutes of Cu deposition, and 30 minutes of electroplating, these sensors achieved high electrical conductivity (2.198x107 S/m) and precise sensing capabilities. The sensors exhibited strong performance, distinguishing between chemicals like methanol, IPA, and silicone oil based on resonance frequency shifts, with the 3.5 GHz sensor achieving the highest sensitivity (1.09%). Thus, the utilization of additive manufacturing techniques for producing 3D-printed sensors can effectively meet the demand for quick and cost-effective microwave sensors and devices.