All-in-one metal-oxide heterojunction artificial synapses for visual sensory and neuromorphic computing systems

An all-in-one artificial synapse integrating central nervous and sensory nervous functions utilizing low-dimensional metal-oxide heterojunction is demonstrated in this work. With an ion-electrolyte gate, synaptic emulations modulated by electrical and photonic stimulus have been integrated into one high-performance three-terminal artificial synapse. Various long-term and short-term synaptic plasticity functions have been achieved by altering the electrolyte-gate stimulus amplitude/width/frequency/number. The emulated synaptic plasticity and maintained synaptic weight states enable artificial synapses for neuromorphic computing. Simulated artificial neural network based on the artificial synapses achieved Covid-19 chest image recognition (>85%). The photo-sensitive metal-oxide heterojunction enables the synaptic functions mimicking the biological visual sensory functions responding to optical and UV stimulus. Photonic synaptic plasticity modulations responding to photonic stimulus wavelength/power/width/number are investigated, and short-term/long-term synaptic plasticity transition was achieved. Dual-mode synaptic modulation combining photonic stimulus and gate stimulus was examined. Finally, an artificial neural network was demonstrated based on the synapses with dual-mode synaptic weight modulation, indicating the potential of the artificial synapse for compact artificial intelligence systems combing neuromorphic computing and visual sensory nervous functions. [Display omitted] •An all-in-one device artificial device utilizing metal-oxide heterojunction integrating both sensory nervous functions and central nervous functions.•Photo-stimulus-modulated synaptic plasticity and gate-stimulus-modulated synaptic plasticity in both long-term and short-term.•The artificial synapse shows superior electrical performance.•An eco-friendly fabrication processbased on water precursor.•Artificial neural network based on artificial synapses for Covid-19 image recognition and a dual-mode modulated artificial neural network based on the all-in-one artificial synapses.