2 results match your criteria: "Shanghai Jiao Tong University Shanghai 200240 China gang.liu@sjtu.edu.cn.[Affiliation]"

Brain-inspired neuromorphic computing has become one of the critical technologies to overcome the bottleneck of von Neumann architecture. It is a vital step to construct a brain-like neuromorphic computing system at the hardware level by utilizing artificial synaptic devices. Compared with electronic synaptic devices, optoelectronic synaptic devices have the advantages of low power consumption, low crosstalk, and high bandwidth.

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Memristors, which feature small sizes, fast speeds, low power, CMOS compatibility and nonvolatile modulation of device resistance, are promising candidates for next-generation data storage and in-memory computing paradigms. Compared to the binary logics enabled by memristor devices, ternary logics with larger information-carrying capacity can provide higher computation efficiency with simple operation schemes, reduced circuit complexity and smaller chip areas. In this study, we report the fabrication of memristor devices based on nano-columnar crystalline ZnO thin films; they show symmetric and reliable multi-level resistive switching characteristics over three hundred cycles, which benefits the implementation of univariate ternary logic operations.

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