Tag: Machine Learning

Researchers at the University of Florida’s Department of Materials Science & Engineering have developed a machine-learning framework that could revolutionize the way high-temperature superconductors are discovered.  Superconductors are materials capable of conducting electricity without resistance, a property that could transform energy transmission, transportation, and medical technologies. However, finding new superconductors has been a slow, expensive […]

Tori Miller, Ph.D., assistant professor in the Department of Materials Science & Engineering at the University of Florida, has been named a National Science Foundation (NSF) Faculty Early Career Development (CAREER) Program Award winner. Her research will utilize statistical methods and machine learning to investigate the micro-scale structure of materials during manufacture. “When metals are […]

Amanda Krause, Ph.D., assistant professor in the UF Department of Materials Science & Engineering, is employing artificial intelligence methods to track and catalogue data for her abnormal grain growth research, and thanks to new a $1.2 million research award from the National Science Foundation’s (NSF) Major Research Instrumentation (MRI) program, she will bring a cutting-edge, […]

Ceramics have been used for everything from wall tiles and glassware to artificial hip joints, cruise missiles and the thermal tiles for NASA’s space shuttle. It should come as no surprise, as a long list of benefits including low electrical conductivity, high melting points and exceptional resistance to chemicals make ceramic materials ideally suited for […]