Ferroelectric Schottky barrier transistor for neuromorphic application

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Neuromorphic computing relies on both synapses and neurons. Developing energy-efficient, highly scalable, and compact devices or circuits is therefore in high demand. We demonstrate the implementation of both artificial synapses and neurons using a single type of ferroelectric Schottky barrier FET (Fe-SBFET). The Fe-SBFET exhibits synaptic properties. The ambipolar switching of the device enables realization of both excitatory and inhibitory neurons with the same device. We also developed a device with a dual-gate architecture. With such design we can achieve more synaptic functions including modulatory neuron function. Notably, we achieve an efficient thalamic neuron using only five Fe-SBFETs, demonstrating leakage-integration-fire and burst (LIFB) functions with low energy consumption. Additionally, a LIF neuron can be realized with just two Fe-SBFETs.


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  • Date: 31 Mar 2025
  • Time: 02:00 PM UTC to 03:30 PM UTC
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  • Beijing, Beijing
  • China
  • Peking University,ED15
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Qing-Tai Zhao

Biography:

Qing-Tai Zhao completed his PhD in physics at Peking University in 1993. He then joined the Institute of Microelectronics at Peking University as lecturer and associate professor, where he focused on the research of SOI materials and devices. In 1997, he was awarded a Humboldt Research Fellowship, which led him to Forschungszentrum Julich in Germany, where he currently leads a research group specializing in nanoelectronic devices. His primary research interests include Si-Ge-Sn based high mobility devices and technology, FDSOI and nanowire devices for low power applications, as well as ferroelectric-based neuromorphic devices and cryogenic electronics for quantum computing. Since 2020, he has served as a governing board member of the SINANO Institute, a European academic and scientific association for nanoelectronics. He has authored and co-authored around 300 peer-reviewed publications and holds over 40 patents.