biostudies-literatureFu XMinistry of Education and Science of the Russian Federation (Minobrnauka)Science and Technology Commission of Shanghai MunicipalityHangzhou Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaMinistry of Education and Science of the Russian FederationScience and Technology Commission of Shanghai Municipality (Shanghai Municipal Science and Technology Commission)National Key Research and Development Program of ChinaShanghai Institute of Technology physicsAnhui Provincial Key R&D ProgramNational Natural Science Foundation of China (National Science Foundation of China)39https://www.ebi.ac.uk/biostudies/studies/S-EPMC9905593biostudies-literatureUnknown12(1)Conventional artificial intelligence (AI) machine vision technology, based on the von Neumann architecture, uses separate sensing, computing, and storage units to process huge amounts of vision data generated in sensory terminals. The frequent movement of redundant data between sensors, processors and memory, however, results in high-power consumption and latency. A more efficient approach is to offload some of the memory and computational tasks to sensor elements that can perceive and process the optical signal simultaneously. Here, we proposed a non-volatile photomemristor, in which the reconfigurable responsivity can be modulated by the charge and/or photon flux through it and further stored in the device. The non-volatile photomemristor has a simple two-terminal architecture, in which Light, science & applicationsGraphene/MoS_2-xO_x/graphene photomemristor with tunable non-volatile responsivities for neuromorphic vision processing.PMC9905593075-15-2020-7916210405321JC140610021YF1454700Dong YLu WFu XSong BHu WMa XChen FLi QPanin GNXu HWang JMiao JCai BXia MLi TZhao QJiang XChen XHao CSun JfalseGraphene/MoS_2-xO_x/graphene photomemristor with tunable non-volatile responsivities for neuromorphic vision processing.Conventional artificial intelligence (AI) machine vision technology, based on the von Neumann architecture, uses separate sensing, computing, and storage units to process huge amounts of vision data generated in sensory terminals. The frequent movement of redundant data between sensors, processors and memory, however, results in high-power consumption and latency. A more efficient approach is to offload some of the memory and computational tasks to sensor elements that can perceive and process the optical signal simultaneously. Here, we proposed a non-volatile photomemristor, in which the reconfigurable responsivity can be modulated by the charge and/or photon flux through it and further stored in the device. The non-volatile photomemristor has a simple two-terminal architecture, in which 2023-01-01T00:00:00Z2023 Feb2025-04-04T23:51:58.196Z2025-04-04T23:51:58.196ZS-EPMC99055933675054810.1038/s41377-023-01079-5