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Memristive Devices: Switching Effects, Modeling, and Applications

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Memristors and Memristive Systems

Abstract

The rapid, exponential growth of modern electronics has brought about profound changes to our daily lives. However, maintaining the growth trend now faces significant challenges at both the fundamental and practical levels [1]. Possible solutions include More Moore—developing new, alternative device structures, and materials while maintaining the same basic computer architecture, and More Than Moore—enabling alternative computing architectures and hybrid integration to achieve increased system functionality without trying to push the devices beyond limits. In particular, an increasing number of computing tasks today are related to handling large amounts of data, e.g. image processing as an example. Conventional von Neumann digital computers, with separate memory and processer units, become less and less efficient when large amount of data have to be moved around and processed quickly. Alternative approaches such as bio-inspired neuromorphic circuits, with distributed computing and localized storage in networks, become attractive options [2–6].

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References

  1. International Technology Roadmap for Semiconductors (ITRS), 2011 Edition. http://www.itrs.net/Links/2011ITRS/Home2011.htm

  2. C. Mead, Neuromorphic electronic systems. Proc. IEEE 78, 1629–1636 (1990)

    Article  Google Scholar 

  3. C.-S. Poon, K. Zhou, Neuromorphic silicon neurons and large-scale neural networks: challenges and opportunities. Front. Neurosci. 5, 108–108 (2011)

    Google Scholar 

  4. D.S. Modha, R. Ananthanarayanan, S.K. Esser, A. Ndirango, A.J. Sherbondy, R. Singh, Cognitive computing. Commun. ACM 54, 62–71 (2011)

    Article  Google Scholar 

  5. G. Indiveri, B. Linares-Barranco, T.J. Hamilton, A. van Schaik, R. Etienne-Cummings, T. Delbruck, S.-C. Liu, P. Dudek, P. Hafliger, S. Renaud, J. Schemmel, G. Cauwenberghs, J. Arthur, K. Hynna, F. Folowosele, S. Saighi, T. Serrano-Gotarredona, J. Wijekoon, Y. Wang, K. Boahen, Neuromorphic silicon neuron circuits. Front. Neurosci. 5, 73–73 (2011)

    Google Scholar 

  6. Y.V. Pershin, M. Di Ventra, Neuromorphic, digital, and quantum computation with memory circuit elements. Proc. IEEE 100, 2071–2080 (2012)

    Article  Google Scholar 

  7. G. Rachmuth, H.Z. Shouval, M.F. Bear, C.-S. Poon, A biophysically-based neuromorphic model of spike rate- and timing-dependent plasticity. Proc. Natl. Acad. Sci. USA 108, E1266–E1274 (2011)

    Article  Google Scholar 

  8. X. Guardiola, A. Diaz-Guilera, M. Llas, C.J. Perez, Synchronization, diversity, and topology of networks of integrate and fire oscillators. Phys. Rev. E 62, 5565–5570 (2000)

    Article  Google Scholar 

  9. Y. Moreno, A.F. Pacheco, Synchronization of Kuramoto oscillators in scale-free networks. Europhys. Lett. 68, 603–609 (2004)

    Article  Google Scholar 

  10. H.Z. Shouval, M.F. Bear, L.N. Cooper, A unified model of NMDA receptor-dependent bidirectional synaptic plasticity. Proc. Natl. Acad. Sci. USA 99, 10831–10836 (2002)

    Article  Google Scholar 

  11. L.O. Chua, Memristor – the missing circuit element. IEEE Trans. Circuit Theory 18, 507–519 (1971)

    Article  Google Scholar 

  12. L.O. Chua, S.M. Kang, Memristive devices and systems. Proc. IEEE 64, 209–223 (1976)

    Article  MathSciNet  Google Scholar 

  13. D.B. Strukov, G.S. Snider, D.R. Stewart, R.S. Williams, The missing memristor found. Nature 453, 80–83 (2008)

    Article  Google Scholar 

  14. R. Waser, M. Aono, Nanoionics-based resistive switching memories. Nat. Mater. 6, 833–840 (2007)

    Article  Google Scholar 

  15. R. Waser, R. Dittmann, G. Staikov, K. Szot, Redox-based resistive switching memories - nanoionic mechanisms, prospects, and challenges. Adv. Mater. 21, 2632–2663 (2009)

    Article  Google Scholar 

  16. J.J. Yang, D.B. Strukov, D.R. Stewart, Memristive devices for computing. Nat. Nanotechnol. 8, 13–24 (2013)

    Article  Google Scholar 

  17. T. Chang, Y. Yang, W. Lu, Building neuromorphic circuits with memristive devices. IEEE Circuits Syst. Mag. 13, 56–73 (2013)

    Article  Google Scholar 

  18. J.G. Simmons, R.R. Verderbe, New conduction and reversible memory phenomena in thin insulating films. Proc. R. Soc. Lond. A Mater. 301, 77–102 (1967)

    Article  Google Scholar 

  19. S.H. Jo, K.H. Kim, W. Lu, High-density crossbar arrays based on a Si memristive system. Nano Lett. 9, 870–874 (2009)

    Article  Google Scholar 

  20. S.H. Jo, K.H. Kim, W. Lu, Programmable resistance switching in nanoscale two-terminal devices. Nano Lett. 9, 496–500 (2009)

    Article  Google Scholar 

  21. J.J. Yang, M.D. Pickett, X.M. Li, D.A.A. Ohlberg, D.R. Stewart, R.S. Williams, Memristive switching mechanism for metal/oxide/metal nanodevices. Nat. Nanotechnol. 3, 429–433 (2008)

    Article  Google Scholar 

  22. L. Chua, Resistance switching memories are memristors. Appl. Phys. A Mater. Sci. Process. 102, 765–783 (2011)

    Article  Google Scholar 

  23. B. Govoreanu, G.S. Kar, Y.Y. Chen, V. Paraschiv, S. Kubicek, A. Fantini, I.P. Radu, L. Goux, S. Clima, R. Degraeve, N. Jossart, O. Richard, T. Vandeweyer, K. Seo, P. Hendrickx, G. Pourtois, H. Bender, L. Altimime, D.J. Wouters, J.A. Kittl, M. Jurczak, 10 × 10 nm2 Hf/HfOx crossbar resistive RAM with excellent performance, reliability and low-energy operation. IEDM 729–732 (2011)

    Google Scholar 

  24. A.C. Torrezan, J.P. Strachan, G. Medeiros-Ribeiro, R.S. Williams, Sub-nanosecond switching of a tantalum oxide memristor. Nanotechnology 22, 485203 (2011)

    Article  Google Scholar 

  25. M.-J. Lee, C.B. Lee, D. Lee, S.R. Lee, M. Chang, J.H. Hur, Y.-B. Kim, C.-J. Kim, D.H. Seo, S. Seo, U.I. Chung, I.-K. Yoo, K. Kim, A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O5-x/TaO2-x bilayer structures. Nat. Mater. 10, 625–630 (2011)

    Article  Google Scholar 

  26. D.H. Kwon, K.M. Kim, J.H. Jang, J.M. Jeon, M.H. Lee, G.H. Kim, X.S. Li, G.S. Park, B. Lee, S. Han, M. Kim, C.S. Hwang, Atomic structure of conducting nanofilaments in TiO2 resistive switching memory. Nat. Nanotechnol. 5, 148–153 (2010)

    Article  Google Scholar 

  27. D.B. Strukov, J.L. Borghetti, R.S. Williams, Coupled ionic and electronic transport model of thin-film semiconductor memristive behavior. Small 5, 1058–1063 (2009)

    Article  Google Scholar 

  28. Y. Yang, P. Gao, S. Gaba, T. Chang, X. Pan, W. Lu, Observation of conducting filament growth in nanoscale resistive memories. Nat. Commun. 3, 732 (2012)

    Article  Google Scholar 

  29. F. Miao, J.P. Strachan, J.J. Yang, M.-X. Zhang, I. Goldfarb, A.C. Torrezan, P. Eschbach, R.D. Kelley, G. Medeiros-Ribeiro, R.S. Williams, Anatomy of a nanoscale conduction channel reveals the mechanism of a high-performance memristor. Adv. Mater. 23, 5633–5640 (2011)

    Article  MATH  Google Scholar 

  30. J.P. Strachan, M.D. Pickett, J.J. Yang, S. Aloni, A.L.D. Kilcoyne, G. Medeiros-Ribeiro, R.S. Williams, Direct identification of the conducting channels in a functioning memristive device. Adv. Mater. 22, 3573–3577 (2010)

    Article  Google Scholar 

  31. J.J. Yang, F. Miao, M.D. Pickett, D.A.A. Ohlberg, D.R. Stewart, C.N. Lau, R.S. Williams, The mechanism of electroforming of metal oxide memristive switches. Nanotechnology 21, 215201 (2010)

    Article  Google Scholar 

  32. D.B. Strukov, R.S. Williams, Exponential ionic drift: fast switching and low volatility of thin-film memristors. Appl. Phys. A Mater. Sci. Process. 94, 515–519 (2009)

    Article  Google Scholar 

  33. J.J. Yang, J.P. Strachan, F. Miao, M.-X. Zhang, M.D. Pickett, W. Yi, D.A.A. Ohlberg, G. Medeiros-Ribeiro, R.S. Williams, Metal/TiO2 interfaces for memristive switches. Appl. Phys. A Mater. Sci. Process. 102, 785–789 (2011)

    Article  Google Scholar 

  34. J.J. Yang, J.P. Strachan, Q.F. Xia, D.A.A. Ohlberg, P.J. Kuekes, R.D. Kelley, W.F. Stickle, D.R. Stewart, G. Medeiros-Ribeiro, R.S. Williams, Diffusion of adhesion layer metals controls nanoscale memristive switching. Adv. Mater. 22, 4034–4038 (2010)

    Article  Google Scholar 

  35. W.C. Chien, Y.C. Chen, E.K. Lai, F.M. Lee, Y.Y. Lin, A.T.H. Chuang, K.P. Chang, Y.D. Yao, T.H. Chou, H.M. Lin, M.H. Lee, Y.H. Shih, K.Y. Hsieh, C.-Y. Lu, A study of the switching mechanism and electrode material of fully CMOS compatible tungsten oxide ReRAM. Appl. Phys. A Mater. Sci. Process. 102, 901–907 (2011)

    Article  Google Scholar 

  36. T. Chang, S.-H. Jo, K.-H. Kim, P. Sheridan, S. Gaba, W. Lu, Synaptic behaviors and modeling of a metal oxide memristive device. Appl. Phys. A Mater. Sci. Process. 102, 857–863 (2011)

    Article  Google Scholar 

  37. C. Ho, C.-L. Hsu, C.-C. Chen, J.-T. Liu, C.-S. Wu, C.-C. Huang, C. Hu, F.-L. Yang, 9 nm half-pitch functional resistive memory cell with <1 μA programming current using thermally oxidized sub-stoichiometric WOx film. IEDM 436–439 (2010)

    Google Scholar 

  38. T. Chang, S.-H. Jo, W. Lu, Short-term memory to long-term memory transition in a nanoscale memristor. ACS Nano 5, 7669–7676 (2011)

    Article  Google Scholar 

  39. Y. Yang, P. Sheridan, W. Lu, Complementary resistive switching in tantalum oxide-based resistive memory devices. Appl. Phys. Lett. 100, 203112 (2012)

    Article  Google Scholar 

  40. K. Terabe, T. Hasegawa, T. Nakayama, M. Aono, Quantized conductance atomic switch. Nature 433, 47–50 (2005)

    Article  Google Scholar 

  41. T. Hasegawa, T. Ohno, K. Terabe, T. Tsuruoka, T. Nakayama, J.K. Gimzewski, M. Aono, Learning abilities achieved by a single solid-state atomic switch. Adv. Mater. 22, 1831–1834 (2010)

    Article  Google Scholar 

  42. T. Ohno, T. Hasegawa, T. Tsuruoka, K. Terabe, J.K. Gimzewski, M. Aono, Short-term plasticity and long-term potentiation mimicked in single inorganic synapses. Nat. Mater. 10, 591–595 (2011)

    Article  Google Scholar 

  43. S.H. Jo, W. Lu, CMOS compatible nanoscale nonvolatile resistance switching memory. Nano Lett. 8, 392–397 (2008)

    Article  Google Scholar 

  44. K.H. Kim, S.H. Jo, S. Gaba, W. Lu, Nanoscale resistive memory with intrinsic diode characteristics and long endurance. Appl. Phys. Lett. 96, 053106 (2010)

    Article  Google Scholar 

  45. S.H. Jo, T. Chang, I. Ebong, B.B. Bhadviya, P. Mazumder, W. Lu, Nanoscale memristor device as synapse in neuromorphic systems. Nano Lett. 10, 1297–1301 (2010)

    Article  Google Scholar 

  46. M. Wuttig, N. Yamada, Phase-change materials for rewriteable data storage. Nat. Mater. 6, 824–832 (2007)

    Article  Google Scholar 

  47. D. Kuzum, R.G.D. Jeyasingh, B. Lee, H.S.P. Wong, Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing. Nano Lett. 12, 2179–2186 (2012)

    Article  Google Scholar 

  48. M.D. Pickett, R.S. Williams, Sub-100 fJ and sub-nanosecond thermally driven threshold switching in niobium oxide crosspoint nanodevices. Nanotechnology 23, 215202 (2012)

    Article  MATH  Google Scholar 

  49. M.D. Pickett, G. Medeiros-Ribeiro, R.S. Williams, A scalable neuristor built with Mott memristors. Nat. Mater. 12, 114–117 (2013)

    Article  Google Scholar 

  50. W. Lu, Memristors: going active. Nat. Mater. 12, 93–94 (2013)

    Article  Google Scholar 

  51. W.M. Cowan, T.C. Südhof, C.F. Stevens (eds.) Synapses (Johns Hopkins University Press, Baltimore, 2001)

    Google Scholar 

  52. P.J. Sjostrom, G.G. Turrigiano, S.B. Nelson, Rate, timing, and cooperativity jointly determine cortical synaptic plasticity. Neuron 32, 1149–1164 (2001)

    Article  Google Scholar 

  53. G.Q. Bi, M.M. Poo, Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J. Neurosci. 18, 10464–10472 (1998)

    Google Scholar 

  54. R.C. Froemke, Y. Dan, Spike-timing-dependent synaptic modification induced by natural spike trains. Nature 416, 433–438 (2002)

    Article  Google Scholar 

  55. D.O. Hebb, The Organization of Behavior: A Neuropsychological Theory (Wiley, New York, 1949)

    Google Scholar 

  56. K. Seo, I. Kim, S. Jung, M. Jo, S. Park, J. Park, J. Shin, K.P. Biju, J. Kong, K. Lee, B. Lee, H. Hwang, Analog memory and spike-timing-dependent plasticity characteristics of a nanoscale titanium oxide bilayer resistive switching device. Nanotechnology 22, 254023 (2011)

    Article  Google Scholar 

  57. P. Krzysteczko, J. Muenchenberger, M. Schaefers, G. Reiss, A. Thomas, The memristive magnetic tunnel junction as a nanoscopic synapse-neuron system. Adv. Mater. 24, 762–766 (2012)

    Article  Google Scholar 

  58. Z.Q. Wang, H.Y. Xu, X.H. Li, H. Yu, Y.C. Liu, X.J. Zhu, Synaptic learning and memory functions achieved using oxygen ion migration/diffusion in an amorphous InGaZnO memristor. Adv. Funct. Mater. 22, 2759–2765 (2012)

    Article  Google Scholar 

  59. S. Yu, Y. Wu, R. Jeyasingh, D. Kuzum, H.S.P. Wong, An electronic synapse device based on metal oxide resistive switching memory for neuromorphic computation. IEEE Trans. Electron Devices 58, 2729–2737 (2011)

    Article  Google Scholar 

  60. G.S. Snider, Spike-timing-dependent learning in memristive nanodevices, in 2008 IEEE/ACM International Symposium on Nanoscale Architectures, Anaheim (2008), pp. 85–92

    Google Scholar 

  61. K.L. Magleby, Effect of repetitive stimulation on facilitation of transmitter release at frog neuromuscular junction. J. Physiol. Lond. 234, 327–352 (1973)

    Google Scholar 

  62. P.P. Atluri, W.G. Regehr, Determinants of the time course of facilitation at the granule cell to Purkinje cell synapse. J. Neurosci. 16, 5661–5671 (1996)

    Google Scholar 

  63. F. Alibart, S. Pleutin, D. Guerin, C. Novembre, S. Lenfant, K. Lmimouni, C. Gamrat, D. Vuillaume, An organic nanoparticle transistor behaving as a biological spiking synapse. Adv. Funct. Mater. 20, 330–337 (2010)

    Article  Google Scholar 

  64. M. Tsodyks, K. Pawelzik, H. Markram, Neural networks with dynamic synapses. Neural Comput. 10, 821–835 (1998)

    Article  Google Scholar 

  65. R.M. Shiffrin, R.C. Atkinson, Storage and retrieval processes in long-term memory. Psychol. Rev. 76, 179–193 (1969)

    Article  Google Scholar 

  66. I. Pavlov, Conditioned Reflexes: An Investigation of the Physiological Activity of the Cerebral Cortex (translated by G. V. Anrep) (Oxford University Press, London, 1927)

    Google Scholar 

  67. Y.V. Pershin, M. Di Ventra, Experimental demonstration of associative memory with memristive neural networks. Neural Netw. 23, 881–886 (2010)

    Article  Google Scholar 

  68. M. Ziegler, R. Soni, T. Patelczyk, M. Ignatov, T. Bartsch, P. Meuffels, H. Kohlstedt, An electronic version of Pavlov’s dog. Adv. Funct. Mater. 22, 2744–2749 (2012)

    Article  Google Scholar 

  69. A.Z. Stieg, A.V. Avizienis, H.O. Sillin, C. Martin-Olmos, M. Aono, J.K. Gimzewski, Emergent criticality in complex Turing B-type atomic switch networks. Adv. Mater. 24, 286–293 (2012)

    Article  Google Scholar 

  70. J. Hermiz, T. Chang, C. Du, W. Lu, Interference and memory capacity effects in memristive systems. Appl. Phys. Lett. 102, 083106 (2013)

    Article  Google Scholar 

  71. K.-H. Kim, S. Gaba, D. Wheeler, J.M. Cruz-Albrecht, T. Hussain, N. Srinivasa, W. Lu, A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications. Nano Lett. 12, 389–395 (2012)

    Article  MATH  Google Scholar 

  72. Q.F. Xia, W. Robinett, M.W. Cumbie, N. Banerjee, T.J. Cardinali, J.J. Yang, W. Wu, X.M. Li, W.M. Tong, D.B. Strukov, G.S. Snider, G. Medeiros-Ribeiro, R.S. Williams, Memristor-CMOS hybrid integrated circuits for reconfigurable logic. Nano Lett. 9, 3640–3645 (2009)

    Article  Google Scholar 

  73. D.B. Strukov, K.K. Likharev, CMOL FPGA: a reconfigurable architecture for hybrid digital circuits with two-terminal nanodevices. Nanotechnology 16, 888–900 (2005)

    Article  Google Scholar 

  74. G.S. Snider, R.S. Williams, Nano/CMOS architectures using a field-programmable nanowire interconnect. Nanotechnology 18, 035204 (2007)

    Article  Google Scholar 

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  1. Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109, USA

    Yuchao Yang, Ting Chang & Wei Lu

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  1. Yuchao Yang
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Correspondence to Wei Lu .

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  1. Faculty of Electrical and Computer Engineering, Institute of Circuits and Systems, Technische Universität Dresden, Dresden, Germany

    Ronald Tetzlaff

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Yang, Y., Chang, T., Lu, W. (2014). Memristive Devices: Switching Effects, Modeling, and Applications. In: Tetzlaff, R. (eds) Memristors and Memristive Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-9068-5_6

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