Graphene-Based Memristive and Photomemristive Nanosensors for Energy-Efficient Information Processing

The emergence of advanced low-dimensional materials of the graphene family opens up unique opportunities for energy-efficient and fast processing of electrical and optical signals in a wide spectral range from ultraviolet to infrared. Non-volatile resistive states in memristors based on two-dimensional (2D) crystals, 1D nanoribbons, and 0D quantum dots are accessible for control by light and an electric field due to polarization and rearrangement of sp2-sp3 hybridization of carbon atoms, as well as due to photoinduced phase transitions. Two-dimensional materials possess unique structural and electronic properties required for the development of highly efficient nanoenergy memristor devices for low-energy information technology. This article discusses memristors and photomemristors based on graphene, graphene oxide, diamane, and chalcogenide semiconductors such as MoS2, WSe2, MoS2−xOx, which are structurally similar to graphene and have a 2D layered structure. Memristors based on graphene and graphene oxide, bigraphene, and diamane, fabricated using localized electron irradiation, exhibit nonlinear behavior and well-controlled memristive states associated with sp2-sp3 transitions of carbon atoms under low-power conditions. The review highlights the dual role of graphene as an active material and electrode, as well as the redox control mechanism. Due to a well-controlled redox process, graphene-based devices exhibit the dynamic behavior required for neuromorphic computing directly in the sensor, reducing the energy and time costs associated with data processing. Neuromorphic computing in a photomemristor-based sensor enables the creation of a compact nano-energy system for real-time information recognition in a wide spectral range, similar to biological vision, for use in self-driving cars, personalized medicine, and other applications.