Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C)

Director
Ivan Schuller
Lead Institution
University of California, San Diego
Class
2018-2022
Mission
To lay down the quantum-materials-based foundation for the development of an energy-efficient, fault-tolerant computer that is inspired and works like the brain (“neuromorphic”).
Research Topics
thermal conductivity, bio-inspired, defects, charge transport, magnetism and spin physics, neuromorphic science, microelectronics, mesoscale science, materials and chemistry by design, mesostructured materials, synthesis (novel systems), synthesis (predictive)
Systems Studied
Systems: metal, oxide, ceramic
Interfaces: inorganic/inorganic, solid/solid
Nanostructured: 1D, 2D, 3D
Experimental and Theoretical Methods
X-ray diffraction and scattering, X-ray imaging, X-ray spectroscopy, electron microscopy, scanning probe microscopy, near-field microscopy, surface science, ultrafast science, molecular dynamics (MD), density functional theory (DFT), dynamical mean field theory (DMFT), monte carlo (MC), finite element methods, mesoscale modeling, multiscale modeling, machine learning

Partner Institutions
- Brookhaven National Laboratory
- National Center for Scientific Research
- National Institute of Standards and Technology
- New York University
- Northwestern University
- Purdue University
- University of California, Davis
- University of California, San Diego
- University of California, Santa Barbara
- University of Chicago
- University of Illinois Urbana-Champaign
- University of Maryland