Abstract
The aim of this book chapter is to provide a comprehensive review report on the Memristor device. Development of linear model for memristor and analysis of memristor are the prime focus as its current requirement for high speed and low power circuits design. Detailed discussion about memristor device physics, structure, operation, mathematical modeling and TCAD simulations have been carried out for better understand of memristor. Moore’s law, the semiconductor industry’s obsession with the shrinking of transistors with the commensurate steady doubling on chip about every two years, has been a source of about 50 year technical and economic revolution. Numerous innovations by a large number of scientists and engineers have helped significantly to sustain Moore’s law since the beginning of the Integrated Circuit (IC) era. As the cost of computer power to the consumer reduces, the cost of production for producers to sustain Moore’s law follows an opposite trend, i.e. Research, Development, Manufacturing, and Test costs are increasing continuously with each new generation of chips. This had led to the reason for existence of Moore’s second law, also called Rock’s law, which is that the capital cost of a semiconductor fabrication also increases exponentially over time. The formation of memristor is a great achievement in semiconductor industry considering Moore’s second law because of its very easy and less steps of fabrication which is the reason for memristor being so cheap, while its nano scale size is new direction to attain Moore’s first law. Therefore, the modelling and simulation of memristor is essential to analyze more advanced features of memristor without spending a lot of money on fabrication and testing.
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Bhushan, S., Khandelwal, S., & Raj, B. (2013). Analyzing different mode FinFET based memory cell at different power supply for leakage reduction, Proceedings of Seventh International Conference on Bio-Inspired Computing.
Biolek, Z., Biolek, D., & Biolkova, V. (2009). SPICE model of memristor with non-linear dopant drift. Radioengineering, 18(2), 210–214.
Chua, L. O. (1971). Memristor-the missing circuit element. IEEE Transactions on Circuit Theory, 18(5).
Chua, L. O., & Kang, S. (1976). Memristive devices and systems. Proceedings of the IEEE, 64(2), 209–223.
da Costa, H. J. B., de Assis Brito Filho, F., & de Araujo do Nascimento, P. I. (2012). Memristor behavioural modeling and simulations using verilog-AMS, Third Latin American Symposium on Circuits and Systems IEEE, (pp. 1–4).
Dennard, R. (1968). Field-effect transistor memory, US 3387286, issued 4 June 1968 (filed 14 July 1967).
Fuechsle, M., Miwa, J. A., Mahapatra, S., Ryu, H., Lee, S., Warschkow, O., Hollenberg, L. C. L., Klimeck, G., & Simmons, M. Y. (2012). A single-atom transistor, Nature Nanotechnology, 7, 242–246.
Gergel-Hackett, N., Hamadani, B., Dunlap, B., Suehle, J., Richter, C., Hacker, C., et al. (2009). A flexible solution-processed memristor. IEEE Electron Device Letters, 30(7), 706–708.
Jain et al. K. (1982). Ultrafast deep-UV lithography with excimer lasers, IEEE Electron Device Letter, EDL-3(53).
Joglekar, Y. N., & Wolf, S. J. (2009). The elusive memristor: Properties of basic electrical circuits. European Journal of Physics, 30(4), 661–675.
Johnson, D. (2010). Junctionless transistor fabricated from nanowires. IEEE Spectrum. Retrieved 04-20-2010.
La Fontaine, B. (2010). Lasers and Moore’s Law, SPIE Professional, p. 20, Oct. 2010.
Liu, G., Fang, L., Li, N., Sui, B., & Duan, Z. (2010). New behavioral modeling method for crossbar-based memristor, Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics, (pp. 356–359).
Larrieu, G., & Han, X. L. (2013). Vertical nanowire array-based field effect transistors for ultimate scaling. Nanoscale, 5(6), 2437–2441.
Mohanty, S. P. (2013). Memristor: from basics to deployment. IEEE Potentials, 32(3), 34–39.
Mohsin, F. (2010). A Multivalued Storage System Using Memristor, Proceedings of 13th International Conference on Computer and Information Technology, (pp. 343–346).
Noyce, R. (1961). Semiconductor device-and-lead structure, US 2981877, issued 25 April 1961 (filed 30 July 1959).
Pattanaik, M., Raj, B., Sharma, S., & Kumar, A. (2012). Diode based trimode multi-threshold CMOS technique for ground bounce noise reduction in static CMOS adders. Advanced Materials Research, 548, 885–889.
Prodromakis, T., & Papavassiliou, C. (2011). A Versatile Memristor Model With nonlinear Dopant Kinetics. IEEE Transactions on Electron Devices, 58(9), 3099–3105.
Raj, B. (2014). Quantum mechanical potential modeling of FinFET. Towards Quantum FinFET, (Vol. 17, pp 81–97). Springer. (ISBN 978-3-319-02021-1).
Raj, B., Saxena, A. K., & Dasgupta, S. (2008). A compact drain current and threshold voltage quantum mechanical analytical modeling for FinFETs. Journal of Nanoelectronics and Optoelectronics (JNO) USA, 3(2), 163–170.
Raj, B., Saxena, A. K., & Dasgupta, S. (2009). Analytical modeling for the estimation of leakage current and subthreshold swing factor of nanoscale double gate finfet device. Microelectronics International, UK, 26, 53–63.
Raj, B., Saxena, A. K., & Dasgupta, S. (2011a). Nanoscale FinFET Based SRAM Cell Design: Analysis of Performance metric, Process variation, Underlapped FinFET and Temperature effect. IEEE Circuits and System Magazine, 11(2), 38–50.
Raj, B., Mitra, J., Bihani, D. K., Rangharajan, V, Saxena, A. K., & Dasgupta, S. (2011). Process variation tolerant FinFET based robust low power sram cell design at 32 nm technology. Journal of Low Power Electronics (JOLPE), Academy Publisher, FINLAND, 7(2), 163–171.
Raj, B., Saxena, A. K., & Dasgupta, S. (2011c). High performance double gate FinFET SRAM cell design for low power application. International Journal of VLSI and Signal Processing Applications., 1(1), 12–20.
Raj, B., Saxena, A. K., & Dasgupta, S. (2013). Quantum mechanical analytical modeling of nanoscale DG FinFET: evaluation of potential, threshold voltage and source/drain resistance. Elsevier’s Journal of Material Science in Semiconductor Processing, Elsevier, 16(4), 1131–1137.
Raja, T., & Mourad, S. (2010). Digital logic implementation in memristor-based crossbars—a tutorial, Proceedings. Fifth IEEE International Symposium on Electronic Design, Test & Applications, (pp. 303–309).
Sharma, V. K., Pattanaik, M., & Raj, B. (2014). PVT variations aware low leakage INDEP approach for nanoscale CMOS circuits. Microelectronics Reliability, 54(1), 90–99.
Sharma, V. K., Pattanaik, M., & Raj, B. (2015). INDEP approach for leakage reduction in nanoscale CMOS circuits. International Journal of Electronics, 102(2), 200–215.
Shin, S., Kim, K., & Kang, S. M. (2010). Compact models for memristors based on charge–flux constitutive relationships. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 29(4).
Strukov, D. B., Snider, G. S., Stewart, D. R., & Williams, R. S. (2008). The missing memristor found. Nature, 453, 80–83.
Varghese, D., & Gandhi, G. (2009). Memristor based high linear range differential pair, International Conference on Communications, Circuits and Systems, (pp. 935–938).
Vishvakarma, S. K., Agrawal, V., Raj, B., Dasgupta, S., & Saxena, A. K. (2007). Two dimensional analytical potential modeling of Nanoscale Symmetric Double Gate (SDG) MOSFET with Ultra Thin Body (UTB). Journal of Computational and Theoretical Nanoscience, 4(6), 1144–1148.
Volos, Ch. K., & Kyprianidis, I. M., Stouboulos1, I. N., Tlelo-Cuautle2, E., Vaidyanathan, S. (2015). Memristor: a new concept in synchronization of coupled neuromorphic circuits, Journal of Engineering Science and Technology Review, 8(2), 157–173.
Wanlass, F. (1967). Low stand-by power complementary field effect circuitry”, US 3356858, issued 5 December 1967 (filed 18 June 1963).
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Raj, B., Vaidyanathan, S. (2017). Analysis of Dynamic Linear Memristor Device Models. In: Vaidyanathan, S., Volos, C. (eds) Advances in Memristors, Memristive Devices and Systems. Studies in Computational Intelligence, vol 701. Springer, Cham. https://doi.org/10.1007/978-3-319-51724-7_18
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DOI: https://doi.org/10.1007/978-3-319-51724-7_18
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