Memory-augmented synaptic transistor based on mechano-sensitive ion dynamics
발표자
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초록
내용
Due to memory ability of skin, human can distinguish familiar objects by touch and consistently address them in proper way. To emulate the biological memory, methods to connect pressure sensor, signal converters, and ion gel-gated transistor, or to fabricate dual gated-ion gel transistor have been developed; however, these suffer from a lack of long-term memory owing to ion equilibrium behavior. Here, we report mechano-sensitive ion dynamics, in which free ion density and migration are controlled by pressure and electric-field independently. By utilizing the proposed ion behavior, tactile perception and learning can be realized simultaneously in a single device, and robust long-term memory (retention time > 30 min) was obtained. Based on this, robotic hand system mimicking memory-induced human motion was demonstrated. We believe that the novel concept of ion dynamics will provide new insight into developing synaptic electronics for neural prosthetics and soft robotics.