An Overview of Fourth Fundamental Circuit Element- 'The Memristor'

By Tukaram Dattatray Dongale

Shivaji university kolhapur

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Abstract

The fourth fundamental circuit element- Memristor, was mathematically predicted by Prof. Leon Chua in his seminal research paper in IEEE Transaction on Circuit Theory on the symmetric background. After four decade in 2008, researchers at the Hewlett–Packard (HP) laboratories reported the development of a new basic circuit element that completes the missing link between charge and flux linkage, which was postulated by Chua. The new roadmap in the field of circuit designing, soft computing, memory technology and neuromorphic applications are emerged out very quickly in scientific community due to memristor. However the commercial device level memristor is not realized and reported in the literature until now. This paper overviews the some of the pioneer and state of art development in the view of memristor. The criticism constrains about memristor in scientific fraternity are also discussed.

Bio

T. D. Dongale School of Nanoscience and Technology, Shivaji University, Kolhapur, M.S-India

this paper present the an overview of memristor, simulation, criticism and application in general.

References

[1] Chua, L. O. Memristor - the missing circuit element, IEEE Trans. Circuit Theory, 18, 1971, 507–519. [2] Ketaki Kerur, A Study of The Memristor- The Fourth Circuit Element, M.Sc, project report for Visvesvaraya Technological University, 2010 [3] Strukov, D. B., Snider, G. S., Stewart, D. R. & Williams, R. S. Nature, 453, 2008, pp.80–83 [4] O. Kavehei, A. Iqbal, Y.S.Kim, K.Eshraghian, S. F. Al-Sarawi, Andd. Abbott, The fourth element: characteristics, modeling and electromagnetic theory of the memristor, Proc. R. Soc. A, 2010. [5] L. Chua and S.M. Kang, "Memristive Device and Systems," Proceedings of IEEE, Vol. 64, no. 2, 1976, pp. 209-223. [6] Z. Biolek, D. Biolek, V. Biolková, "Spice Model of Memristor with Nonlinear Dopant Drift", Radio engineering, vol. 18, no. 2, 2009, pp. 210-214. [7] Yogesh N Joglekar and Stephen J Wolf, "The elusive memristor: properties of basic electrical circuits", European Journal of Physics, vol. 30, 2009, pp. 661–675. [8] Robinson E. Pino, Kristy A. Campbell, Compact Method for Modeling and Simulation of Memristor Devices, Proceeding of international Symposium on Nanoscale Architecture, 2010, pp.1-4. [9] Rak and G. Cserey, "Macromodelling of the memristor in SPICE," IEEE Trans. Computer.-Aided Design Integr. Circuits Syst., vol. 29, no.4, Apr. 2010, pp. 632–636. [10] Z. Biolek, D. Biolek and V. Biolková, "SPICE model of memristor with nonlinear dopant drift", Radio Eng., vol. 18, no. 2, Jun. 2009, pp. 210–214. [11] D. Batas and H. Fiedler, "A memristor SPICE implementation and a new approach for magneticflux-controlled memristor modeling", IEEE Trans. Nanotech., vol. 10, no. 2, Mar. 2011, pp. 250–255. [12] S. Benderli and T. A. Wey, "On SPICE macromodelling of TiO2 memristor", Electron. Lett., vol. 45, no. 7, Mar. 2009, pp. 377–379. [13] Merrikh-Bayat, Farnood, and Saeed Bagheri Shouraki. "Memristor crossbar-based hardware implementation of fuzzy membership functions." Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on. Vol. 1. IEEE, 2011. [14] Karel Zaplatilek, Memristor modeling in MATLAB and Simulink, Proceedings of the European Computing Conference, 2010, pp. 62-67 [15] Yogesh N Joglekar and Stephen J Wolf, The elusive memristor: properties of basic electrical circuits, Eur. J. Phys.30(2009) 661–675 [16] S.W.Keemink, Mimicking synaptic plasticity in memristive neuromorphic systems, Life Sciences Graduate School, University of Utrecht, Utrecht, Netherlands, 2012 [17] Tiny organisms remember the way to food, Available at: http://www.newscientist.com/article/dn11394-tiny-organisms-remember-the-way-to-food.html , Retrieved: 28 December, 2012. [18] Gorm K. Johnsen, An introduction to the memristor – a valuable circuit element in bioelectricity and bioimpedance, J Electr Bioimp, vol. 3, 2012, pp. 20 –28. [19] Johnsen GK, Lütken CA, Martinsen ØG, Grimnes S. Memristive model of electro-osmosis in skin. Phys Rev E, 83, 031916 (2011). [20] Grimnes S. Skin impedance and electro-osmosis in the human epidermis. Med Biol Eng Comp. 1983;21;739-49 [21] S.P. Kosta, Y.P. Kosta, Mukta Bhatele, Y.M. Dubey, Avinash Gaur, Shakti Kosta, Jyoti Gupta, Amit Patel and Bhavin Patel, Human blood liquid memristor, Int. J. Medical Engineering and Informatics, Vol. 3, No. 1, 2011 [22] H. M. Upadhyaya, Suresh Chandra: "Polarity dependent memory switching behaviorin Ti/Cd Pb S/Ag system." Semiconductor Science and Technology 10, 332-338(1995) [23] 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, Atomicstructure of conducting nanofilaments in TiO2resistive switching memory. Nat. Nanotechnol.5(2), 148–153 (2010) [24] C. Nauenheim, C. Kuegeler, A. Ruediger, R. Waser, Investiga-tion of the electroforming process in resistively switching TiO2 nanocrosspoint junctions. Appl. Phys. Lett.96(12) (2010) [25] S.J. Song, K.M. Kim, G.H. Kim, M.H. Lee, J.Y. Seok, R. Jung, C.S. Hwang, Identification of the controlling parameter for the set-state resistance of a TiO2resistive switching cell. Appl. Phys. Lett. 96(11) (2010) [26] T.A. Wey, S. Benderli, Amplitude modulator circuit featuring TiO2 memristor with linear dopant drift. Electron. Lett.45(22), 1103-U8 (2009) [27] X. Cao, X.M. Li, X.D. Gao, W.D. Yu, X.J. Liu, Y.W. Zhang, L.D. Chen, X.H. Cheng, Forming-free colossal resistive switching effect in rare-earth-oxide Gd2O3films for memristor applications. J. Appl. Phys.106(7) (2009) [28] T. Driscoll, H.T. Kim, B.G. Chae, M. Di Ventra, D.N. Basov, Phase-transition driven memristive system. Appl. Phys. Lett.95(4) (2009) [29] 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(4), 1297–1301 (2010) [30] Francesca Pincella, Paolo Camorani, Victor Erokhin, Electrical properties of an organic memristive system, Appl Phys A (2011) 104:1039–1046 [31] Kyung Hyun Choi, Maria Mustafa, Khalid Rahman, Bum Ko Jeong, Yang Hui Doh, Cost-effective fabrication of memristive devices with ZnO thin film using printed electronics technologies, Appl Phys A (2012) 106:165–170 [32] Murali S et al. Resistive switching in zinc–tin-oxide. Solid State Electron (2012), http://dx.doi.org/10.1016/j.sse.2012.06.016 [33] Byung Joon Choi et al, Nitride memristor, Appl Phys A (2012) 109:1–4 [34] E. Gale, D. Pearson, S. Kitson, A. Adamatzky, B. de Lacy Costello, "Aluminium Electrodes Effect the Operation of Titanium Oxide Sol-gel Memristors," arXiv:1106.6293v1 [35] T. Berzina, A. Smerieri, M. Bernabo, A. Pucci, G. Ruggeri, V. Erokhin, M.P. Fontana, Optimization of an organic memristor as an adaptive memory element, Journal of Applied Physics 105 (12) (2009) 124515. [36] T.W.K. Dong Ick Son, J.H. Shim, J.H. Jung, D.U. Lee, J.M. Lee, W.I. Park, W.K. Choi, Flexible organic bistable devices based on graphene embedded in an insu-lating poly(methyl methacrylate) polymer layer, Nano Letters 10 (7) (2010)2441 [37] Julien Borghetti, Gregory S. Snider, Philip J. Kuekes, J. Joshua Yang, Duncan R. Stewart and R. Stanley Williams, 'Memristive' switches enable 'stateful' logic operations via material implication, Nature, Vol 464|8 April 2010, http:// doi:10.1038/nature08940 [38] S.H. Jo, T. Chang, I. Ebong, B.B. Bhadviya, P. Mazumder and W. Lu, Nanoscale Memristor Device as Synapse in Neuromorphic Systems, Nano letters, Am. Chem. Soc., vol. 10, no. 4 pp. 1297 -1301, 2010. [39] G. S. Snider, "Self-organized computation with unreliable, memristive nanodevices, Nanotechnology, vol. 18, p. 365202, 2007. [40] A. Afifi, A. Ayatollahi, and F. Raissi, "STDP implementation using memristive nanodevice in CMSO-nano neuromorphic networks," IEICE Electron. Expr., vol. 6, no. 3, pp. 148–153, Feb. 2009. [41] Y. V. Pershin, S. L. Fontaine, and M. D. Ventra, "Memristive model of amoeba learning, Phys. Rev. E, vol. 80, p. 021926, 2009. [42] B. Linares-Barranco and T. Serrano-Gotarredona, Memristance can explain Spike-Time-Dependent-Plasticity in Neural Synapses, Nature Precedings: hdl:10101/npre.2009.3010.1, Mar 2009 [43] T. Prodromakis and C. Toumazou, A Review on Memristive Devices and Applications, ICECS- 2010, pp-936-939 [44] B. Muthuswamy and P. P. Kokate, "Memristor-based chaotic circuits," IETE Tech. Rev., vol. 26, no. 6, pp. 417–429, Dec. 2009. [45] M. Itoh and L. O. Chua, "Memristor oscillators," Int. J. Bifurcation Chaos, vol. 18, no. 11, pp. 3183–3206, Nov. 2008. [46] P. Vontobel, W. Robinett, P. Kuekes, D. Stewart, J. Straznicky, and R. Williams, "Writing to and reading from a nano-scale crossbar memory based on memristors, Nanotechnology, vol. 20, p. 425204, 2009. [47] M. B. Laurent, "Pattern recognition using memristor crossbar array," U.S. Patent 7 459 933, Dec. 2, 2008. [48] A. Afifi and A. Ayatollahi, "Implementation of biologically plausible spiking neural network models on the memristor crossbar based CMOS/Nano circuits," in Proc. Eur. Conf. Circuit Theory Des., 2009, pp. 563–566. [49] J. Borghetti, Z. Y. Li, J. Straznicky, X. M. Li, D. A. A. Ohlberg, W. Wu, D. R. Stewart, and R. S. Williams, "A hybrid nanomemristor/transistor logic circuit capable of self-programming," in Proc. Nat. Acad. Sci., 2009, pp. 1699–1703. [50] M. B. Laurent, "Programmable Crossbar Signal Processor," U.S. Patent 7 302 513, Nov. 27, 2007. [51] Neil D. Mathur, The fourth circuit element, Nature, Vol 455, 30, 2008, doi:10.1038/nature07437 [52] Vongehr, S. (2012). The Missing Memristor: Novel Nanotechnology or rather new Case Study for the Philosophy and Sociology of Science?. arXiv preprint arXiv:1205.6129. p.10 [53] Chun Ning Lau, Duncan R. Stewart, R. Stanley Williams, Marc Bockrath: "Direct Observation of Nanoscale Switching Centers in Metal/Molecule/Metal Structures." Nano Letters 4(4), 569-572 (2004) [54] X. Wu, P. Zhou, J. Li, L. Y. Chen, H. B. Lu, Y. Y.Lin, T. A. Tang: "Reproducible unipolar resistance switching in stoichiometric ZrO2 films."Applied Physics Letters 90, 183507 (2007) [55] R. Waser, M. Aono: "Nanoionics-based resistive switching memories." Nature Materials 6, 833-840 (2007) [56] Y. V. Pershin, M. Di Ventra: "Spin memristive systems: Spin memory effects in semiconductor spintronics." Phys. Rev. B 78, 113309 (2008) [57] Meuffels, P., & Soni, R. (2012). Fundamental Issues and Problems in the Realization of Memristors. arXiv preprint arXiv:1207.7319 [58] Jagdish Kumar, Memristor- why do we have to know about it?, IETE technical review, vol-26, issue -1, 2009, pp.3-6 [59] Prodromakis, T., and C. Toumazou. "A review on memristive devices and applications." Electronics, Circuits, and Systems (ICECS), 2010 17th IEEE International Conference on. IEEE, 2010, pp. 936-939. [60] Eshraghian, K.; Kyoung-Rok Cho; Kavehei, O.; Soon-Ku Kang; Abbott, D.; Sung-Mo Steve Kang; "Memristor MOS Content Addressable Memory (MCAM): Hybrid Architecture for Future High Performance Search Engines," IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol.19, no.8, Aug. 2011, pp.1407-1417. [61] Erokhin, T. Berzina, A. Smerieri, P. Camorani, S. Erokhina, and M. Fontana, "Bio-inspired adaptive networks based on organic memristors," Nano Communication Networks, vol. 1, no. 2, 2010, pp. 108 – 117. [62] S. H. Jo, T. Chang, I. Ebong, B. B. Bhadviya, P. Mazumder, and W. Lu, "Nanoscale memristor device as synapse in neuromorphic systems", Nano Lett., vol. 10, pp. 1297–1301, 2010 [63] Hu, J., & Wang, J. Global uniform asymptotic stabil-ity of memristor-based recurrent neural networks with time delays. In: 2010 International Joint Conference on Neural Networks, IJCNN 2010, Barcelona, Spain, pp. 1-8, (2010). [64] Pershin, Y. V., & Di Ventra, M. Experimental demon-stration of associative memory with memristive neural net-works. Neural Networks, 23(7), 881-886, (2010a). [65] Wu, A. L., Wen, S. P., & Zeng, Z. G. Synchroniza-tion control of a class of memristor-based recurrent neural networks. Information Sciences, 183(1), 106-116, (2012). [66] Wu, A. L., Zeng, Z. G., Zhu, X. S., & Zhang, J. E. Exponential synchronization of memristor-based recur-rent neural networks with time delays. Neurocomputing, 74(17), 3043-3050, (2011). [67] Wu, A., & Zeng, Z. Dynamic behaviors of memristor-based recurrent neural networks with time-varying delays. Neural Networks (2012). doi:10.1016/j.neunet.2012.08.009 [68] Klimo, Martin, and Ondrej Such. "Memristors can implement fuzzy logic." arXiv preprint arXiv:1110.2074 (2011). [69] Merrikh-Bayat, Farnood, Saeed Bagheri Shouraki, and Farshad Merrikh-Bayat. "Memristive fuzzy edge detector." Journal of Real-Time Image Processing (2011): 1-11. [70] Merrikh-Bayat, Farnood, and Saeed Bagheri Shouraki. "Programming of memristor crossbars by using genetic algorithm." Procedia Computer Science 3 (2011): 232-237. [71] Merrikh-Bayat, F., and Shouraki S. Bagheri. "Memristive Neuro-Fuzzy System." IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics: a publication of the IEEE Systems, Man, and Cybernetics Society (2012). [72] Keemink, S. W. "Mimicking synaptic plasticity in memristive neuromorphic systems." (2012). Available at: http://igitur-archive.library.uu.nl/student-theses/2012-0831-200644/UUindex.html

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  • Tukaram Dattatray Dongale (2013), "An Overview of Fourth Fundamental Circuit Element- 'The Memristor'," https://nanohub.org/resources/16590.

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