The Impact of the Different Voltages and Frequencies on Resistivity of the TiO2-based Memristors with 3D Observation in MATLAB

Yıl 2020, Sayı: 20, 260 - 264, 31.12.2020

Niloufar Rajabiyoun

https://doi.org/10.31590/ejosat.769921

Cited By: 1

Öz

Memristor is the fourth fundamental element that was theoretically discovered about 40 years ago by Professor Leon Chua and was introduced alongside three other existing elements (resistor, capacitor and inductor) in the electronic world. Until recently, however, the construction of a physical example of this had not yet taken place. Finally, in 2008, HP introduced a nanometer-sized TiO2 structure with predictable memory behavior and hysteresis. In this paper, after introducing the general characteristics and structure of the memristor, a 3D MATLAB model with nonlinear ion deflection for the titanium dioxide memristor made by HP with current or voltage control capability is presented. By setting the model parameters for the specifications of this memory, some simulations are performed and the results are displayed.

Anahtar Kelimeler

Memristor, TiO2, 3D Matlab simulations

The Impact of the Different Voltages and Frequencies on Resistivity of the TiO2-based Memristors with 3D Observation in MATLAB

Öz

Memristör, yaklaşık 40 yıl önce Profesör Leon Chua tarafından teorik olarak Elektronikte keşfedilen dördüncü temel unsurdur ve elektronik dünyasında mevcut diğer üç unsurun yanısıra (direnç, kapasitör ve indüktör) tanıtıldı. Ancak yakın zamana kadar, bu unsurun fiziksel bir örneğinin yapılması ve geliştirmesi henüz gerçekleşmemişti. Son olarak, 2008'de HP, öngörülebilir bellek davranışı ve histerezisi olan nanometre boyutlu bir TiO2 yapısı ortaya koymuştur. Bu makalede, memrisörün genel özellikleri ve yapısı tanıtıldıktan sonra, HP tarafından akım veya gerilim kontrol kapasitesine sahip titanyum dioksit memristörü için doğrusal olmayan iyon sapmasına sahip bir 3D MATLAB modeli sunulmaktadır. Bu belleğin özellikleri için model parametreleri ayarlanarak, bazı simülasyonlar gerçekleştirilmiştir ve sonuçlar görüntülenmiştir.

Anahtar Kelimeler

Memristör, TiO2, 3 Boyutlu Matlab simulatörü

Kaynakça

• Rajabiyoun, N. Karacalı, T. A new approach to modeling TiO2−x-based memristors using molecular dynamics simulation. Appl. Phys. A 125, 296 (2019). https://doi.org/10.1007/s00339-019-2602-0
• Rajabi̇youn, N. (2020). Investigation of the Current and Voltage Waveforms for a TiO2-based Memristor with MATLAB. Avrupa Bilim ve Teknoloji Dergisi , (19) , 303-311. DOI: 10.31590/ejosat.723069.
• L. Chua, "Memristor-The missing circuit element," in IEEE Transactions on Circuit Theory, vol. 18, no. 5, pp. 507-519, September 1971, doi: 10.1109/TCT.1971.1083337.
• Tuszynski, J.A., Friesen, D., Freedman, H. et al. Microtubules as Sub-Cellular Memristors. Sci Rep 10, 2108 (2020). https://doi.org/10.1038/s41598-020-58820-y.
• A. Ascoli, I. Messaris, R. Tetzlaff and L. O. Chua, "Theoretical Foundations of Memristor Cellular Nonlinear Networks: Stability Analysis With Dynamic Memristors," in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 67, no. 4, pp. 1389-1401, April 2020, doi: 10.1109/TCSI.2019.2957813.
• F. Corinto, M. Di Marco, M. Forti and L. Chua, "Nonlinear Networks With Mem-Elements: Complex Dynamics via Flux-Charge Analysis Method," in IEEE Transactions on Cybernetics, doi: 10.1109/TCYB.2019.2904903.
• O. Krestinskaya, A. P. James and L. O. Chua, "Neuromemristive Circuits for Edge Computing: A Review," in IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 1, pp. 4-23, Jan. 2020, doi: 10.1109/TNNLS.2019.2899262.
• Itoh M. Chua L. (2019) Memristor Cellular Automata and Memristor Discrete-Time Cellular Neural Networks. In: Chua L. Sirakoulis G., Adamatzky A. (eds) Handbook of Memristor Networks. Springer, Cham.
• Chua, L. Five non-volatile memristor enigmas solved. Appl. Phys. A 124, 563 (2018). https://doi.org/10.1007/s00339-018-1971-0.
• Shyam Prasad Adhikari, Hyongsuk Kim, Changju Yang, Leon O. Chua, Building cellular neural network templates with a hardware friendly learning algorithm, Neurocomputing, Volume 312, 2018, Pages 276-284, https://doi.org/10.1016/j.neucom.2018.05.113.
• A. G. Radwan, M. A. Zidan and K. N. Salama, "HP Memristor mathematical model for periodic signals and DC," 2010 53rd IEEE International Midwest Symposium on Circuits and Systems, Seattle, WA, 2010, pp. 861-864, doi: 10.1109/MWSCAS.2010.5548670.
• A. G. Radwan, M. A. Zidan and K. N. Salama, "On the mathematical modeling of memristors," 2010 International Conference on Microelectronics, Cairo, 2010, pp. 284-287, doi: 10.1109/ICM.2010.5696139.