电阻随机存取存储器
神经形态工程学
记忆电阻器
非易失性存储器
材料科学
重置(财务)
氮化硅
光电子学
氮化物
兴奋剂
电子工程
介电谱
计算机科学
电压
硅
纳米技术
电气工程
电极
工程类
化学
图层(电子)
人工智能
人工神经网络
电化学
物理化学
金融经济学
经济
作者
Nikolaos Vasileiadis,Panagiotis Karakolis,Panagiotis Mandylas,V. Ioannou-Sougleridis,P. Normand,Michele Perego,Ph. Komninou,Vasileios Ntinas,Iosif-Angelos Fyrigos,Ioannis G. Karafyllidis,Georgios Ch. Sirakoulis,Panagiotis Dimitrakis
标识
DOI:10.1109/tnano.2021.3072974
摘要
Resistive memories are promising candidates for replacing current nonvolatile memories and realize storage class memories. Moreover, they have memristive properties, with many discrete resistance levels and implement artificial synapses. The last years researchers have demonstrated RRAM chips used as accelerators in computing, following the new in-memory and neuromorphic computational approaches. Many different metal oxides have been used as resistance switching materials in MIM structures. Understanding of the switching mechanism is very critical for the modeling and the use of memristors in different applications. Here, we demonstrate the bipolar resistance switching of silicon nitride thin films using heavily doped Si and Cu as bottom and top-electrodes respectively. Next, we dope nitride with oxygen in order to introduce and modify the intrinsic nitride defects. Analysis of the current-voltage characteristics reveal that under space-charge limited conditions and by setting the appropriate current compliance, the operation condition of the RRAM cells can be tuned. Furthermore, resistance change can be obtained using appropriate SET/RESET pulsing sequences allowing the use of the devices in computing acceleration application. Impedance spectroscopy measurements clarify the presence of different mechanisms during SET and RESET. We prove through a customized measurement set-up and the appropriate control software that the initial charge-storage in the intrinsic nitride traps governs the resistance change.
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