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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Huang, P. Chen, B. Wang, Y.J. Zhang, F.F. Shen, L. Liu, R. Zeng, L. Du, G. Zhang, X. Gao, B. Kang, J.F. Liu, X.Y. Wang, X.P. Weng, B.B. Tang, Y.Z. Lo, G.-Q. Kwong, D.-L. |
| Copyright Year | 2013 |
| Description | Author affiliation: Inst. of Microelectron., A*STAR, Singapore, Singapore (Wang, X.P.; Weng, B.B.; Tang, Y.Z.; Lo, G.-Q.; Kwong, D.-L.) || Inst. of Microelectron., Peking Univ., Beijing, China (Huang, P.; Chen, B.; Wang, Y.J.; Zhang, F.F.; Shen, L.; Liu, R.; Zeng, L.; Du, G.; Zhang, X.; Gao, B.; Kang, J.F.; Liu, X.Y.) |
| Abstract | An analytic model for the endurance degradation of metal oxide based RRAM is presented for the first time. The endurance degradation behaviors under various operation modes can be predicted by the model, which were verified by the measured data in different devices. Furthermore, the $10^{6}$ endurance for all 4-level resistance states in $HfO_{X}-based$ RRAM is demonstrated by using the proposed optimization operation scheme for multi-level data storage based on the model prediction. Guided by the model, a dynamic self-recovery operation scheme is developed to achieve more than 2 orders endurance enhancement at a high switching speed (10 ns). |
| File Size | 1043415 |
| File Format | |
| ISBN | 9781479923069 |
| ISSN | 2156017X |
| DOI | 10.1109/IEDM.2013.6724685 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-12-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Degradation Resistance Switches Analytical models Tin Integrated circuit modeling Predictive models |
| Content Type | Text |
| Resource Type | Article |
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