Emulating the essential synaptic behaviors using single synaptic transistor has attracted extensive attention for building the brain-inspired neuromorphic systems. However, few reports on synaptic transistors fabricated by solution processes have been reported. In this article, the indium oxide synaptic transistors based on polyimide substrates were fabricated by a nontoxic waterinducement method at a low temperature, and lithium perchlorate (LiClO 4 ) was dissolved in polyethylene oxide as the gate electrolyte. For water-inducement process, comparable electrical properties of the synaptic transistors can be achieved by prolonging the annealing time rather than high-temperature annealing with a relatively short time. The effect of the annealing time on the electrical performance of the electrolyte-gated transistors annealed at various temperatures was investigated. It is found that the electrolyte-gated-synaptic transistor on polyimide substrate annealed at 200 °C exhibits high electrical performance and good mechanical stability. Due to the ion migration relaxation dynamics in the polymer electrolyte, various important synaptic behaviors such as the excitatory postsynaptic current, paired-pulse facilitation, high-pass filtering characteristics, and long-term memory performance were successfully mimicked. The electrolyte-gated synaptic transistors based on solution-processed In 2 O 3 exhibit great potential in neuromorphological applications.

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The cone photoreceptors in our eyes selectively transduce the natural light into spiking representations, which endows the brain with high energy-efficiency color vision. However, the cone-like device with color-selectivity and spike-encoding capability remains challenging. Here, we propose a metal oxide-based vertically integrated spiking cone photoreceptor array, which can directly transduce persistent lights into spike trains at a certain rate according to the input wavelengths. Such spiking cone photoreceptors have an ultralow power consumption of less than 400 picowatts per spike in visible light, which is very close to biological cones. In this work, lights with three wavelengths were exploited as pseudo-three-primary colors to form ‘colorful’ images for recognition tasks, and the device with the ability to discriminate mixed colors shows better accuracy. Our results would enable hardware spiking neural networks with biologically plausible visual perception and provide great potential for the development of dynamic vision sensors.

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