| Autor: |
Boldman WL; Department of Materials Science and Engineering, University of Tennessee, Knoxville, TN 37996, USA., Zhang C; Department of Materials Science and Engineering, University of Tennessee, Knoxville, TN 37996, USA., Ward TZ; Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA., Briggs DP; Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA., Srijanto BR; Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA., Brisk P; Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA., Rack PD; Department of Materials Science and Engineering, University of Tennessee, Knoxville, TN 37996, USA. prack@utk.edu.; Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. prack@utk.edu. |
| Abstrakt: |
Due to the limit in computing power arising from the Von Neumann bottleneck, computational devices are being developed that mimic neuro-biological processing in the brain by correlating the device characteristics with the synaptic weight of neurons. This platform combines ionic liquid gating and electrowetting for programmable placement/connectivity of the ionic liquid. In this platform, both short-term potentiation (STP) and long-term potentiation (LTP) are realized via electrostatic and electrochemical doping of the amorphous indium gallium zinc oxide (aIGZO), respectively, and pulsed bias measurements are demonstrated for lower power considerations. While compatible with resistive elements, we demonstrate a platform based on transitive amorphous indium gallium zinc oxide (aIGZO) pixel elements. Using a lithium based ionic liquid, we demonstrate both potentiation (decrease in device resistance) and depression (increase in device resistance), and propose a 2D platform array that would enable a much higher pixel count via Active Matrix electrowetting. |
