Dingshu Tian, Chuan Ke, Bai Sun, Haotian Liang, Ziran Qian, Qifan Wen, Xueqi Chen, Chuan Yang, Min Xu, Yong Zhao
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引用次数: 0
Abstract
Traditional computing systems struggle to keep pace with the development of artificial intelligence, as well as the development of the economy and continuous innovation in science and technology. Therefore, there is an urgent need for a new generation of powerful yet low-power computing technologies to replace them. Quantum dots have been incorporated into memristors due to their unique electrical properties, and the development of quantum dot memristors is expected to solve the problems faced by traditional memristors, including cycle stability, high energy consumption, and conductivity uniformity. This article reviews the research progress of quantum dot memristors and their simulation applications in artificial synapses. It summarizes some of the current challenges faced in the development of quantum dot memristors and discusses the potential future applications of these memristors in the field of artificial intelligence.
期刊介绍:
Nanoscale is a high-impact international journal, publishing high-quality research across nanoscience and nanotechnology. Nanoscale publishes a full mix of research articles on experimental and theoretical work, including reviews, communications, and full papers.Highly interdisciplinary, this journal appeals to scientists, researchers and professionals interested in nanoscience and nanotechnology, quantum materials and quantum technology, including the areas of physics, chemistry, biology, medicine, materials, energy/environment, information technology, detection science, healthcare and drug discovery, and electronics.