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Updated: 2016.11.29 20:54
 
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Synaptic Transistor Mimics Human Neural Processing
[ Issue 149 Page 2 ] Thursday, November 24, 2016, 04:28:56 Juhoon Lee Junior Staff Reporter juhoonlee@kaist.ac.kr

     

   
 

     As one of the most complex biological systems, the human brain provides an ideal model for highly efficient computing systems. Following suit, a team at Gwangju Institute of Science and Technology (GIST) successfully developed a “synapstor” — a synaptic organic transistor that simulates a neuron’s short-term plasticity via imitating fluctuating signals between two nerve cells. GIST’s synapstor improved upon organic semiconductor hybrids that compromised channel conductance for memory performance. The hybrids’ rough nanoparticle layers resulted in plummeting conductance levels. To eliminate such a tradeoff, GIST devised a vacuum- processed, nanoscale metallic interlayer in the transistor that creates an ultra-flat surface for maximum electron transport. The result is a transistor that maintains high conductance while boasting an exceptional memory performance. The promising results suggest that the synapstor will accomplish more than mere high-efficiency neuromorphic computing. The synapstor has paved the road for the development of hybrid neural networks, a system of biocompatible organic devices that can communicate with actual neurons with huge application possibilities.

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