Learning through ferroelectric domain dynamics in solid-state synapses

In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging,…

• UD
  U.S. Department of Energy

  Award: ER-46612
• EC
  European Commission

  Awards: 732642, 267579
• AN
  Agence Nationale de la Recherche

  Awards: reference: ANR-10-LABX-0035, Labex NanoSaclay, reference: ANR-10-LABX-0035, ANR-10-LABX-0035, ANR-10
• DA
  Defense Advanced Research Projects Agency

  Award: HR0011-15-2-0038
• BE
  Basic Energy Sciences

  Award: ER-46612