Journal Article10.1063/1.4868383
Random telegraph noise analysis in AlOx/WOy resistive switching memories
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TL;DR: In this paper, the origins of current fluctuations of Al/AlOx/WOy/W bilayer resistive random access memory (RRAM) devices are investigated through detailed noise analysis.
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Abstract: In this Letter, the origins of current fluctuations of Al/AlOx/WOy/W bilayer resistive random access memory (RRAM) devices are investigated through detailed noise analysis. Random telegraph noise (RTN) measurements were performed on RRAMs with three different resistance states. An obvious RTN signal with 40.7% amplitude difference was found at high resistance state, and the trapping/de-trapping process leading to the RTN signal was studied in detail by extracting the trap energy from energy diagram. For median and low resistance states, the resistance fluctuations were 34.0% and 0.3%, respectively. To further study the RTN characteristics, the normalized power spectral density (PSD) was analyzed. It is found that, for one dominant-trap caused RTN phenomena, the normalized noise PSD behaves as 1/f 2 on the high resistance state; while for median and low resistance states, the noise follows 1/f rule, suggesting that the current fluctuations are associated with the envelop of multiple RTNs caused by traps located near/in the conductive filament. Based on the noise analyses in time and frequency domains, a conduction mechanism is proposed to describe the trap effects on the current fluctuations of different resistance states.
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Citations
A Complete Statistical Investigation of RTN in HfO 2 -Based RRAM in High Resistive State
TL;DR: In this paper, the random telegraph noise (RTN) in hafnium-oxide resistive random access memories in high resistive state (HRS) is analyzed by decomposing the multilevel RTN signal into two-level RTN traces using a factorial hidden Markov model approach, which allows extracting the properties of the traps originating the RTN.
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Switched by input: power efficient structure for RRAM-based convolutional neural network
Lixue Xia,Tianqi Tang,Wenqin Huangfu,Ming Cheng,Xiling Yin,Boxun Li,Yu Wang,Huazhong Yang +7 more
- 05 Jun 2016
TL;DR: An energy efficient structure using input data as selection signals is proposed to reduce the ADC cost for merging results of multiple crossbars and save 80% area and more than 95% energy while maintaining the same or comparable classification accuracy of CNN on MNIST.
107
Investigation of Filamentary Current Fluctuations Features in the High-Resistance State of Ni/HfO 2 -Based RRAM
Mireia Bargallo Gonzalez,Javier Martin-Martinez,M. Maestro,M.C. Acero,Montserrat Nafria,Francesca Campabadal +5 more
TL;DR: In this article, the presence of filamentary current instabilities in the high resistance state of Ni/HfO2-based RRAM devices and their associated current fluctuations mechanisms are explored.
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Investigation of switching mechanism in HfO x -ReRAM under low power and conventional operation modes
TL;DR: This is the first study that reveals the different noise characteristics in the low power operation mode from that in the conventional operation mode, and the PSD value is proportional to 1/f.
Engineering interface-type resistance switching based on forming current compliance in ITO/Ga2O3:ITO/TiN resistance random access memory: Conduction mechanisms, temperature effects, and electrode influence
Chih-Hung Pan,Ting-Chang Chang,Ting-Chang Chang,Tsung-Ming Tsai,Kuan-Chang Chang,Po-Hsun Chen,Shi-Wang Chang-Chien,Min-Chen Chen,Hui-Chun Huang,Huaqiang Wu,Ning Deng,He Qian,Simon M. Sze +12 more
TL;DR: In this article, an ITO/Ga2O3:ITO/TiN structured resistance random access memory is introduced, where either interface or filament conduction mechanism can be induced depending on the forming compliance current, which has not been investigated before.
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Resistance-dependent amplitude of random telegraph-signal noise in resistive switching memories
TL;DR: In this article, the authors proposed a physical model describing the interaction of the localized current with a fluctuating defect, which quantitatively accounts for the observed RTN amplitude, thus allowing for an analytical prediction of state stability in RRAMs.
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