A memristor SPICE model accounting for volatile characteristics of practical ReRAM

IEEE Electron Device Letters

Volumn 35, Issue 1, 2014, Pages 135-137

  Berdan, Radu ^a   Lim, Chuan ^a   Khiat, Ali ^b   Papavassiliou, Christos ^a   Prodromakis, Themis ^b  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

memristive devices; Memristor; model; non volatile; ReRAM; SPICE; TiO2; volatility

Indexed keywords

MEMRISTIVE DEVICES; MEMRISTOR; NON-VOLATILE; RERAM; TIO; VOLATILITY;

COMPUTER SIMULATION; MODELS; PASSIVE FILTERS; SPICE; TITANIUM DIOXIDE;

MEMRISTORS;

EID: 84891545410     PISSN: 07413106     EISSN: None     Source Type: Journal    
DOI: 10.1109/LED.2013.2291158     Document Type: Article

References (19)

1. S. R. Williams, "How we found the missing memristor," IEEE Spectrum, vol. 45, no. 12, pp. 28-35, Dec. 2008.
2. I. E. Ebong and P. Mazumder, "CMOS and memristor-based neural network design for position detection," Proc. IEEE, vol. 100, no. 6, pp. 2050-2060, Jun. 2012.
3. T. Driscoll, J. Quinn, S. Klein, et al., "Memristive adaptive filters," Appl. Phys. Lett., vol. 97, no. 9, pp. 093502-1-093502-3, 2010.
4. S. Shin, K. Kim, and S. Kang, "Memristor applications for programmable analog ICs," IEEE Trans. Nanotechnol., vol. 10, no. 2, pp. 266-274, Mar. 2011.
5. T. Serrano-Gotarredona, T. Masquelier, T. Prodromakis, et al., "STDP and STDP variations with memristors for spiking neuromorphic learning systems," Frontiers Neurosci., vol. 7, pp. 1-15, Feb. 2013.
6. A. Gelencser, T. Prodromakis, C. Toumazou, et al., "Biomimetic model of the outer plexiform layer by incorporating memristive devices," Phys. Rev. E, vol. 85, no. 4, pp. 041918-1-041918-10, 2012.
7. G. Indiveri, B. Linares-Barranco, R. Legenstein, et al., "Integration of nanoscale memristor synapses in neuromorphic computing architectures," Nanotechnology, vol. 24, no. 38, pp. 384010-1-384010-22, 2013.
8. A. Ascoli and F. Corinto, "Memristor diode bridge with LCR filter," Electron. Lett., vol. 48, no. 14, pp. 824-825, 2012.
9. A. Ascoli, F. Corinto, V. Senger, et al., "Memristor model comparison," IEEE Circuits Syst. Mag., vol. 13, no. 2, pp. 89-105, May 2013.
10. T. Chang, S. H. Jo, and W. Lu, "Short-term memory to long-term memory transition in a nanoscale memristor," ACS Nano, vol. 5, no. 9, pp. 7669-7676, 2011.
11. M. D. Pickett, G. Medeiros-Ribeiro, and R. S. Williams, "A scalable neuristor built with mott memristors," Nature Mater., vol. 12, no. 2, pp. 114-117, 2013.
12. S. Gaba, P. Sheridan, J. Zhou, et al., "Stochastic memristive devices for computing and neuromorphic applications," Nanoscale, vol. 5, no. 13, pp. 5872-5878, 2013.
13. F. Alibart, L. Gao, B. D. Hoskins, et al., "High-precision tuning of state for memristive devices by adaptable variation-tolerant algorithm," Nanotechnology, vol. 23, no. 7, pp. 75201-75207, 2012.
14. L. O. Chua, "Memristor - The missing circuit element," IEEE Trans. Circuit Theory, vol. 18, no. 5, pp. 507-519, Sep. 1971.
15. Z. Wei, T. Takagi, Y. Kanzawa, et al., "Demonstration of high-density ReRAM ensuring 10-year retention at 85 °C based on a newly developed reliability model," in Proc. IEEE IEDM, Dec. 2011, pp. 31.4.1-31.4.4.
16. D. B. Strukov and R. S. Williams, "Exponential ionic drift: Fast switching and low volatility of thin-film memristors," Appl. Phys. A, Mater. Sci. Process., vol. 94, no. 3, pp. 515-519, 2009.
17. I. Valov, I. Sapezanskaia, A. Nayak, et al., "Atomically controlled electrochemical nucleation at superionic solid electrolyte surfaces," Nature Mater., vol. 11, pp. 530-535, Apr. 2012.
18. Z. Biolek, D. Biolek, and V. Biolkova, "SPICE model of memristor with nonlinear dopant drift," Radioengineering, vol. 18, no. 2, pp. 210-214, 2009.
19. T. Prodromakis, B. P. Peh, C. Papavassiliou, et al., "A versatile memristor model with nonlinear dopant kinetics," IEEE Trans. Electron Devices, vol. 58, no. 9, pp. 3099-3105, Sep. 2011.