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


Ivan Schuller

Lead Institution

University of California, San Diego




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

BES Staff Contact

Michael Pechan, Matthias Graf, Athena Sefat