Compact multifilament model of resistive switching metal-oxide memristor

Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy


Release:

2023. Vol. 9. № 2 (34)

Title: 
Compact multifilament model of resistive switching metal-oxide memristor


For citation: Ebrahim, A. H. A., Gubin, A. A., Busygin, A. N., & Udovichenko, S. Yu. (2023). Compact multifilament model of resistive switching metal-oxide memristor. Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy, 9(2), 128–138. https://doi.org/10.21684/2411-7978-2023-9-2-128-138

About the authors:

Abdulla H. Ebrahim, Cand. Sci. (Phys.-Math.), Junior Researcher, Memristive Materials Laboratory, Center for Nature-Inspired Engineering, University of Tyumen, Tyumen, Russia; abdulla.ybragim@mail.ru, https://orcid.org/0000-0002-1709-9882

Alexey A. Gubin, Postgraduate Student, Department of Applied and Technical Physics, Engineer, REC “Nanotechnology”, University of Tyumen; a.a.gubin@utmn.ru

Alexander N. Busygin, Cand. Sci. (Phys.-Math.), Associate Professor, Department of Applied and Technical Physics, School of Natural Sciences, University of Tyumen, Tyumen, Russia; Senior Researcher, Memristive Materials Laboratory, Center for Nature-Inspired Engineering, University of Tyumen, Tyumen, Russia; a.n.busygin@utmn.ru, https://orcid.org/0000-0002-3439-8067

Sergey Yu. Udovichenko, Dr. Sci. (Phys.-Math.), Professor, Department of Applied and Tech­nical Physics, School of Natural Sciences, University of Tyumen, Tyumen, Russia; Scientific Director of the Memristive Materials Laboratory, Center for Nature-Inspired Engineering, University of Tyumen, Tyumen, Russia; udotgu@mail.ru, https://orcid.org/0000-0003-3583-7081

Abstract:

A fairly simple compact circuit multifilament resistive switching model of a metal-oxide memristor with controlled multilevel conductance tuning is presented, which is in demand for self-training of large arrays of memristor synapses and information processing using them. A good agreement between the calculated and measured volt-ampere characteristics and the pulse-time dependent plasticity curve is shown.

References:

Asapu, S., & Maiti, T. (2017). Multifilamentary conduction modeling in transition metal oxide-based RRAM. IEEE Transactions on Electron Devices, 64(8), 3145–3150. https://doi.org/10.1109/TED.2017.2709249

Busygin, A., Udovichenko, S., Ebrahim, A., Bobylev, A., & Gubin, A. (2023). Mathematical model of metal-oxide memristor resistive switching based on full physical model of heat and mass transfer of oxygen vacancies and ions. physica status solidi (a), 220(11), Article 2200478. https://doi.org/10.1002/pssa.202200478

Chee, H. L., Nandha, K. T., & Almurib, H. A. (2018). Multifilamentary conduction modelling of bipolar Ta2O5/TaOx bi-layered RRAM. In IEEE 7th Non-Volatile Memory Systems and Applications Symposium (NVMSA) (pp. 113–114). https://doi.org/10.1109/NVMSA.2018.00029

González-Cordero, A., Roldan, J. B., Jiménez-Molinos, F., Suñé, J., Long, S., & Liu, M. (2016). A new compact model for bipolar RRAMs based on truncated-cone conductive filaments — A Verilog-A approach. Semiconductor Science and Technology, 31(11), Article 115013. https://doi.org/10.1088/0268-1242/31/11/115013

Martyshov, M. N., Emelyanov, A. V., Demin, V. A., Nikiruy, K. E., Minnekhanov, A. A., Nikolaev, S. N., Taldenkov, A. N., Ovcharov, A. V., Presnyakov, M. Yu., Sitnikov, A. V., Vasiliev, A. L., Forsh, P. A., Granovsky, A. B., Kashkarov, P. K., Kovalchuk, M. V., & Ryl­kov, V. V. (2020). Multifilamentary character of anticorrelated capacitive and resistive switching in memristive structures based on (CoFeB)x(LiNbO3)100−x nanocomposite. Physical Review Applied, 14(3), Article 034016. https://doi.org/10.1103/PhysRevApplied.14.034016

Matsukatova, A. N., Iliasov, A. I., Nikiruy, K. E., Kukueva, E. V., Vasiliev, A. L., Goncharov, B. V., Sitnikov, A. V., Zanaveskin, M. L., Bugaev, A. S., Demin, V. A., Ryl­kov, V. V., & Emelya­nov, A. V.
(2022). Convolutional neural network based on crossbar arrays of (CoFeB)x(LiNbO3)100−x nanocomposite memristors. Nanomaterials, 12(19), Article 3455. https://doi.org/10.3390/nano12193455

Miranda, E., Mehonic, A., Suñé, J., & Kenyon, A. J. (2013). Multi-channel conduction in redox-based resistive switch modelled using quantum point contact theory. Applied Physics Letters, 103(22), Article 222904. https://doi.org/10.1063/1.4836935

Nikiruy, K. E., Emelyanov, A. V., Demin, V. A., Sitnikov, A. V., & Kashkarov, P. K. (2018). A precise algorithm of memristor switching to a state with preset resistance. Technical Physics Letters, 44(5), 416–419. https://doi.org/10.1134/S106378501805022X

Nikiruy, K. E., Emelyanov, A. V., Demin, V. A., Sitnikov, A. V., Minnekhanov, A. A., Rylkov, V. V., Kashkarov, P. K., & Kovalchuk, M. V. (2019). Dopamine-like STDP modulation in nanocomposite memristors. AIP Advances, 9(6), Article 065116. https://doi.org/10.1063/1.5111083

Zhuo, Y., Midya, R., Song, W., Wang, Z., Asapu, S., Rao, M., Lin, P., Jiang, H., Xia, Q. & Williams, S. R. (2022). A dynamical compact model of diffusive and drift memristors for neuromorphic computing. Advanced Electronic Materials, 8(8), Article 2100696. https://doi.org/10.1002/aelm.202100696