Improvement of power consumption and linearity of integrate/fire characteristics using diffusive memristors with defective graphene for artificial neuron application
{"title":"Improvement of power consumption and linearity of integrate/fire characteristics using diffusive memristors with defective graphene for artificial neuron application","authors":"Moonkyu Song, Sangheon Lee, S.S. Teja Nibhanupudi, Siyu Wu, Sanjay K. Banerjee","doi":"10.1016/j.sse.2024.108892","DOIUrl":null,"url":null,"abstract":"<div><p>Diffusive memristors made with conductive metal bridge random access memories (RAMs) have been studied for low power consumption and linearity of integrate/fire characteristics of artificial neurons by using a defective graphene interlayer. Utilizing this approach, a volatile artificial neuron incorporating Ag demonstrates sustained low-power characteristics inherent to Ag-based devices, accompanied by linearity in spike occurrence through precise control of on/off-current ratio and conductive filament dissolution time. This approach enables the precise tuning of the neuron's behavior and offers potential applications in neuromorphic computing and artificial intelligence.</p></div>","PeriodicalId":21909,"journal":{"name":"Solid-state Electronics","volume":"215 ","pages":"Article 108892"},"PeriodicalIF":1.4000,"publicationDate":"2024-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Solid-state Electronics","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0038110124000418","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
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Abstract
Diffusive memristors made with conductive metal bridge random access memories (RAMs) have been studied for low power consumption and linearity of integrate/fire characteristics of artificial neurons by using a defective graphene interlayer. Utilizing this approach, a volatile artificial neuron incorporating Ag demonstrates sustained low-power characteristics inherent to Ag-based devices, accompanied by linearity in spike occurrence through precise control of on/off-current ratio and conductive filament dissolution time. This approach enables the precise tuning of the neuron's behavior and offers potential applications in neuromorphic computing and artificial intelligence.
期刊介绍：
It is the aim of this journal to bring together in one publication outstanding papers reporting new and original work in the following areas: (1) applications of solid-state physics and technology to electronics and optoelectronics, including theory and device design; (2) optical, electrical, morphological characterization techniques and parameter extraction of devices; (3) fabrication of semiconductor devices, and also device-related materials growth, measurement and evaluation; (4) the physics and modeling of submicron and nanoscale microelectronic and optoelectronic devices, including processing, measurement, and performance evaluation; (5) applications of numerical methods to the modeling and simulation of solid-state devices and processes; and (6) nanoscale electronic and optoelectronic devices, photovoltaics, sensors, and MEMS based on semiconductor and alternative electronic materials; (7) synthesis and electrooptical properties of materials for novel devices.
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