Quantum dot-based memristors for information processing and artificial intelligence applications
Source abstract
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.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Neuroscience and Neural Engineering · Quantum-Dot Cellular Automata
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Key Laboratory of Advanced Technologies of Materials, (Ministry of Education), Southwest Jiaotong University, Chengdu, Sichuan 610031, China
Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle (Ministry of Education), Southwest Jiaotong University, Chengdu, Sichuan 610031, China
Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shanxi 710049, China
School of Physical Science and Technology, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
Southwestern Institute of Physics, Chengdu, Sichuan 610225, China
Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 350117, China
Funding
National Natural Science Foundation of China · Xi’an Jiaotong University
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