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Multisensory Ferroelectric Semiconductor Synapse for Neuromorphic Computing
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DOI：10.1002/adfm.202313010.png)
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Abstract
En 中文
Integrated multifunctionality in visual information processing is crucial in the artificial intelligence era. Compared to the parallel human vision system, current bionic vision devices exhibit a complex structure with single functionality, challenging intelligent processing and integration. Here, a multisensory artificial synapse with a crossbar structure comprising graphene/alpha-In2Se3/graphene layers is demonstrated, merging sensing, memory, and computing while mimicking various synaptic properties. The Schottky barrier height is modulated by the polarization of ferroelectric semiconductor alpha-In2Se3, enabling reconfigurable device conductance and photoresponsivity. This conductance emulates synaptic short-term and long-term plasticity through electrical pulse modulation, boasting a rapid 40 ns programming speed. The device also exhibits linearly regulated photoresponsivity under illumination, with synaptic plasticity from optical pulses. The fusion of electronic and optoelectronic devices enables both image front-end processing and advanced post-processing. In-sensor front-end processing enhances subsequent processing efficiency, with pattern recognition accuracy reaching 97%. This design fosters the advancement of multisensory and highly integrated neuromorphic vision systems. This work demonstrates a multisensory synapse with a graphene/alpha-In2Se3/graphene crossbar structure. The ferroelectric alpha-In2Se3 modulates the Schottky barrier height, regulating the conductance (G) and photoresponsivity (R). This enables simulating various electronic and optoelectronic synaptic characteristics, featuring linearly tunable electrical and optical weights. Such features facilitate in-sensor front-end processing and advanced processing, achieving a recognition accuracy rate of 97%.image
Keywords:
electronic and optoelectronic synapses
ferroelectric semiconductors
multisensory
neuromorphic vision systems
reconfigurable
Journal
IF:
19
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3.4W
Citations:
32.1W