Investigation of Inherent Capacitive Effects in Linear Memristor Model
Source abstract
Abstract
Memristor plays a vital role in the advancement of recent semiconductor technology and has become a promising candidate in stepping up its progress towards Moore’s law. It attracts the attention of researchers with its small dimension, non-volatility comparable to flash memory, low cost, and its exploitation in the building of highly dense integrated circuits. In this manuscript, a novel memristor model is developed by adding a parallel variable capacitor in the linear model of memristor of the HP’s lab. The modified model of the memristor is simulated in the Matlab and variation of the capacitance and reactive capacitance is observed with the input signal, conductive width, thickness of the device, and with the input signal frequency variations. Apart from this, C-V characteristics and charge-voltage pinched hysteresis loop is also plotted and analyzed. It is seen that the capacitance of the parallel capacitor varies with the variation of the conductive width and thus insulating thickness of memristor, similar to RON and ROFF in the linear memristor model. In the saturation condition, a capacitance of 2.4 × 10−11 F is attained while a capacitance of 7 × 10−13 F is attained in the depletion state of the memristor.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Neuroscience and Neural Engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (27)
Show source-provided references
1. Chua LO (1971) "Memristor-the missing circuit element," Circuit Theory. IEEE Trans 18(5):507–519
2. Chua LO, Mo S (1976) Kang, Memristive devices and systems. Proc IEEE 64(2):209–22310.1109/PROC.1976.10092 ↗
3. Strukov DB, Snider GS, Stewart DR, Williams RS (2008) The missing memristor found. Nature 453(7191):80–8310.1038/nature06932 ↗
4. Strukov DB, Williams RS (2009) Exponential ionic drift: fast switching and low volatility ofáthin-film memristors. Appl Phys A 94(3):515–51910.1007/s00339-008-4975-3 ↗
5. Joglekar YN, Wolf SJ (2009) The elusive memristor: properties of basic electrical circuits. Eur J Phys 30(4):66110.1088/0143-0807/30/4/001 ↗
6. Biolek, Biolek D, Biolkova V (2009) Spice model of Memristor with nonlinear dopant drift. Radioengineering 18(2):210–214
7. Prodromakis T, Pin B, Peh CP, Toumazou C (2011) A versatile memristor model with nonlinear dopant kinetics. Electron Devices IEEE Trans 58(9):3099–310510.1109/TED.2011.2158004 ↗
8. Singh J, Raj B (2019) An accurate and generic window function for nonlinear memristor models. J Comput Electron 18(2):640–64710.1007/s10825-019-01306-6 ↗
9. Yang JJ, Pickett MD, Li X, Ohlberg DA, Stewart DR, Williams RS (2008) Memristive switching mechanism for metal/oxide/metal nanodevices. Nat Nanotechnol 3(7):429–43310.1038/nnano.2008.160 ↗
10. Singh J, Raj B (2018) Modeling of mean barrier height levying various image forces of metal–insulator–metal structure to enhance the performance of conductive filament based memristor model. IEEE Trans Nanotechnol 17(2):268–27510.1109/TNANO.2018.2793953 ↗
11. Simmons JG (1963) Generalized formula for the electric tunnel effect between similar electrodes separated by a thin insulating film. J Appl Phys 34(6):1793–180310.1063/1.1702682 ↗
12. Singh J, Raj B (2019) Tunnel current model of asymmetric MIM structure levying various image forces to analyze the characteristics of filamentary memristor. Appl Phys A 125(3):20310.1007/s00339-019-2482-3 ↗
13. Kvatinsky S, Friedman EG, Kolodny A, Weiser UC (2013) TEAM: ThrEshold adaptive memristor model, Circuits and Systems I: Regular Papers. IEEE Trans 60(1):211–221
14. Yakopcic C, Taha TM, Subramanyam G, Pino RE, Rogers S (2011) A memristor device model. IEEE Electron Device Lett 32(10):1436–143810.1109/LED.2011.2163292 ↗
15. Biolek D, Di Ventra M, Pershin YV 2013. Reliable SPICE simulations of memristors, memcapacitors and meminductors. arXiv preprint arXiv:1307.2717
16. Pershin YV, Di Ventra M 2012 SPICE model of memristive devices with threshold, arXiv preprint arXiv, pp 1204.2600
17. Singh J, Raj B (2019) Design and investigation of 7T2M-NVSRAM with enhanced stability and temperature impact on store/restore energy. IEEE Trans Very Large Scale Integration (VLSI) Syst 27(6):1322–132810.1109/TVLSI.2019.2901032 ↗
18. Hassan AM, Fahmy HA, Rafat NH (2016) Enhanced model of conductive filament-based memristor via including trapezoidal electron tunneling barrier effect. IEEE Trans Nanotechnol 15(3):484–49110.1109/TNANO.2016.2546686 ↗
19. Simmons JG (1963) Electric tunnel effect between dissimilar electrodes separated by a thin insulating film. J Appl Phys 34(9):2581–259010.1063/1.1729774 ↗
20. Wang R, Yang JQ, Mao JY, Wang ZP, Wu S, Zhou M, Chen T, Zhou Y, Han ST Recent Advances of Volatile Memristors: Devices, Mechanisms, and Applications. Adv Intell Syst: 200005510.1002/aisy.202000055 ↗
21. Cao G, Cheng C, Zhang H, Zhang H, Chen R, Huang B, Yan X, Pei W, Chen H (2020) The application of halide perovskites in memristors. J Semiconduct 41(5):05120510.1088/1674-4926/41/5/051205 ↗
22. Eason BN, Sneddon IN On certain integrals of Lipschitz-Hankel type involving products of Bessel functions. Phil Trans Roy Soc London A247:529–551 April 1955. (references)10.1098/rsta.1955.0005 ↗
23. Clerk Maxwell J (1892) A treatise on electricity and magnetism, vol 2. 3rd edn. Clarendon, Oxford, pp 68–73
24. Jacobs IS, Bean CP (1963) In: Rado GT, Suhl H (eds) Fine particles, thin films and exchange anisotropy in Magnetism, vol III. Academic, New York, pp 271–350
25. Singh J, Raj B (2018) Comparative analysis of memristor models and memories design. J Semiconduct 39(7):07400610.1088/1674-4926/39/7/074006 ↗
26. Singh J, Raj B (2018) Temperature dependent analytical modeling and simulations of nanoscale memristor. Eng Sci Technol In J 21(5):862–868
27. Singh J, Raj B (2019) Enhanced nonlinear Memristor model encapsulating stochastic dopant drift. J Nanoelectron Optoelectron 14(7):958–96310.1166/jno.2019.2570 ↗