Low-Dimensional Layered Light-Sensitive Memristive Structures for Energy-Efficient Machine Vision

ELECTRONICS(2022)

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摘要
Layered two-dimensional (2D) and quasi-zero-dimensional (0D) materials effectively absorb radiation in the wide ultraviolet, visible, infrared, and terahertz ranges. Photomemristive structures made of such low-dimensional materials are of great interest for creating optoelectronic platforms for energy-efficient storage and processing of data and optical signals in real time. Here, photosensor and memristor structures based on graphene, graphene oxide, bismuth oxyselenide, and transition metal dichalcogenides are reviewed from the point of view of application in broadband image recognition in artificial intelligence systems for autonomous unmanned vehicles, as well as the compatibility of the formation of layered neuromorphic structures with CMOS technology.
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smart energy-efficient optoelectronics, neuromorphic photosensors, photomemristors, graphene, transition metal dichalcogenides, oxyselenides, photoinduced phase transitions, artificial intelligence systems, machine vision
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