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 photoexcited carriers and oxygen-related ions are coupled, leading to a displaced and pinched hysteresis in the current-voltage characteristics. For the first time, non-volatile photomemristors implement computationally complete logic with photoresponse-stateful operations, for which the same photomemristor serves as both a logic gate and memory, using photoresponse as a physical state variable instead of light, voltage and memresistance. The polarity reversal of photomemristors shows great potential for in-memory sensing and computing with feature extraction and image recognition for neuromorphic vision.
Conventional artificial-intelligence (AI) machine vision technology, based on the von Neumann architecture, uses separate computing and storage units to process the 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 shift some tasks of the memory and computational to sensory elements which can perceive and process optical signal simultaneously. Here, we proposed a non-volatile photo-memristor, in which reconfigurable responsivity can be modulated by charge and/or photon flux through it and further stored in the device. The non-volatile photo-memristors consist of simple two-terminal architecture, in which photoexcited carriers and oxygen-related ions are coupled, leading to a displaced and pinched hysteresis of current-voltage characteristics. The non-volatile photo-memristors sets first implemented computationally complete logic for the photoresponse-stateful logic operations, for which the same photo-memristor serves simultaneously as logic gates and memory unit that uses photoresponse instead of light, voltage and memresistance as the physical state variable. Further changing the polarity of photo-memristors demonstrate great potential for in-memory sensing and computing with feature extraction and image recognition for neuromorphic vision processing.
Most greenhouse gases come from biological activities and industry which will lead to global warming and show an impact on human life. With the need of green transformation of the global economic structure and seeking for higher quality of human life, the detection and management of greenhouse gases, as well as most hazardous gases in the environment, are increasingly demanding. Applications in different fields require sensors that can detect gas volume fractions with magnitudes from 10-9 to 10-4. Greenhouse gas detection plays an important role both in the agriculture and industry field. In this review, we first summarize the mechanism of several common gas detectors used currently. Then, the advantages of nanostructured gas sensors are discussed. Finally, the applications of infrared gas sensors based on nanophotonic devices are described in detail. This review has been an outlook on the future development of infrared gas sensors based on nanophotonic devices.INDEX TERMS Environment and climate, greenhouse gas, nanostructures, photonic device.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.