Engineering doctoral student Abiola Oloye is on the hunt for better superconducting materials

Abiola Temidayo Oloye is a doctoral student in materials science at the FAMU-FSU College of Engineering. Originally from Lagos, Nigeria, she received her bachelor’s and first master’s degree from the Southwest State University in Kursk, Russia, in electronic engineering and telecommunications. She also holds a master’s in materials science. 

Researchers at CAPS and Georgia Tech collaborate to detect faults in superconducting cables using machine learning

In a new study, engineering researchers are developing a novel machine learning tool that may increase the reliability of high-temperature superconductor (HTS) power systems. The method finds early indicators of series faults in HTS cables. 

High-temperature superconductor power systems can carry 100 times more electricity than conventional wires. They are lightweight and require less space to power electric aircraft and ships.