Quantum Materials, AI & Machine Learning

A vast array of the technologies upon which we rely are a result of the quantum mechanical behavior of materials. Magnetic memories, superconductors, strong magnets for electrical motors, and magnetic sensors exist because of the quantum mechanical nature of electrons in solids. In the 21st century it is becoming increasingly clear that these emergent functionalities are only the tip of the iceberg. Interactions between electrons can produce novel quantum states of matter with no classical counterpart. This intrinsically quantum mechanical behavior can be exploited for applications ranging from quantum information technologies to ultra-sensitive detectors. However, our ability of finding and controlling these states of matter requires interdisciplinary expertise.

A main goal of the Shull Wollan Center is to discover new quantum materials with emergent behaviors and functionalities via the application and interpretation of neutron scattering techniques. To achieve this goal, we design new ways of interrogating materials and analyzing/interpreting experimental data. This is done via the generation of interdisciplinary efforts and incubation of ideas that synergize the materials research of the University of Tennessee and Oak Ridge National Laboratory with the high-performance computing and large-scale experimental facilities of ORNL.

By bridging the gaps between areas that are crucial for the future development of quantum materials, we are laying the foundations for a new way of doing scientific research. Future scientists will be educated in an interdisciplinary environment that will hybridize different areas of knowledge. The inexorable development of artificial intelligence and the power of machine learning ─ algorithms developed to find patterns in vast data sets ─ will change scientific knowledge and speed up discovery.

Researchers

---

Recent Highlights

---

All Research Highlights ►