报告主题：Bio-voltage memristor: Performance, Mechanism, and Applications
Neuromorphic systems built from memristors that emulate bioelectrical information processing in the brain may overcome the limitations of traditional computing architectures. However, functional emulation alone may still not attain all the merits of bio-computation, which uses action potentials of 50–120 mV at least ten times lower than signal amplitude in conventional electronics to achieve extraordinary power efficiency and effective functional integration. In this talk, we demonstrate a type of bio-voltage memristor whose operation voltage is as low as the biological amplitude (e.g., 50-120 mV). The device is made of silver active electrodes, together with dielectric protein nanowires harvested from microbe G. Sulfurreducens, which is considered the key factor for bio-voltage switching, possibly attributed to the protein nanowires catalyze metallization. With the advantage of low-voltage switching, we develop parameter-matched artificial neurons for the wearable bio-electronic interface. In addition, we also propose a new strategy to address the sneak-path issue by utilizing the bio-voltage memristor’s retention property. The unidirectional current flow in the bio-voltage memristor suppresses the sneak-path current, whereas the transient-retention window is exploited for bidirectional programming. This methodology was also extended to other technology-matured diodes for high-efficient in-situ neuromorphic computing by exploring diode’s reverse recovery.
Dr. Tianda Fu is an upcoming postdoc scholar at University of Chicago (Professor Sihong Wang’s group). He holds Ph.D. degree in Electrical and Computer Engineering from University of Massachusetts Amherst (2023) and B.S. degree in Precious Instrument from Chongqing University (2017). His research interest is in neuromorphic devices & computing, wearable electronics, and sensory devices. He received Chinese Government Award for Outstanding Students Abroad Fellowship and Harvey Fellowship in 2023. He won 1st place in 3-Minute-Thesis (3MT) competition at UMass Amherst (2021) and 1st place in National Environmental-friendly Science & Technology Competition in China (2016).