UC Riverside

Superconducting devices provide unique properties and new potential for future electronics. Magnetometers and gradiometers based on superconducting materials such as Superconducting Quantum Interference Devices (SQUIDs) are amongst the most sensitive detectors of magnetic field. They have been widely used in geological, biomedical, and electromagnetic analysis. More and more, applications require superconductor sensors with large dynamic ranges and high slew-rates. Additionally, the capability of parallel processing many sensors in high demand. This dissertation reports on the experimental results of several high temperature superconductor based magnetometers and the further analysis of their electronic properties, followed by a novel approach using high-speed digital electronics to control some of the sensors.

Currently, commercialized control systems based on analog flux-locked loops (FLL) are mainly designed for low-transition temperature SQUIDs. Distinct analog circuits have to be designed or customized to each type of SQUID sensor with different electrical properties for optimal performance. The rapid advancement in the performance of high-frequency digital components, driven by the mobile communication industry, motivates the further development of digital FLL (DFLL). In order to develop a system with adjustable features for different types of SQUIDs, we used Field Programmable Gate Arrays (FPGA) to implement the new DFLL. This approach can be easily scaled up to support a large number of sensors instead of having multiple analog circuits. The reprogrammable feature of the FPGA gives the system the capability to modify the FLL for SQUID sensors in real time. The system combines both traditional FLL with flux jump and counting together to provide a much larger dynamic range. At the same time, algorithms have been developed for analyzing and tracking in order to achieve an accurate lock on both SQUIDs. This approach is also a potential electronics system that can operate other magnetometers such as long junctions. Additional digital signal processing (DSP) can be used for SQUID data analysis, including parallel processing, digital gradiometer subtraction, and SQUID imaging.