Composite Nanomaterials for Implementation of Promising Memristive Structures

Abstract:

The paper considers principles of creating promising memristive structures based on composite oxides with agglomerates of nanoparticles. The proposed functional nanomaterial is promising for the formation of a composite structure of a memristor, consisting of two electrodes based on one or more nanoscale layers of metal oxides, which are separated by an active medium so that an insulating layer is applied between the electrodes at the periphery of the active medium region. A conductive layer is formed on top of the insulating layer, which is connected to the negative rail, which prevents leakage of negative oxygen ions through the insulating layer. The authors considered in detail technological process of integral production, which forms the necessary vertical profile of the memristive structure ensuring its greatest stability and repeatability of parameters. The implementation of a hardware-software complex for monitoring and diagnosing a memristive structure is proposed. As a result of the research, an original technical solution was created, which ensures formation of memristive structures with a high efficiency of impact on negative oxygen ions, which are charge carriers in this structure, which ensures their high productivity and stability of parameters.

• Periodical: Key Engineering Materials (Volume 910)
• Pages: 703-712
• DOI: https://doi.org/10.4028/p-72a77f
• Online since: February 2022
• Authors: Andrey I. Vlasov*, Vladimir P. Zhalnin, Alexander A. Rasuk, Oleg V. Kosyanov
• Keywords: Diagnostics of Memristive Structures, Electronic Engineering, Functional Nanomaterials, Integrated Production, Memristive Structures, Monitoring, Nanocomposites, Stability

References

[1] D.B. Strukov et al., The missing memristor found, Nature, 2008, Vol. 453, N. 179. pp.80-83.

[2] L.O. Chua, Memristor – the missing circuit element, IEEE Trans. Circuit Theory, 1971б vol. CT-18, N. 5, p.507 – 519.

DOI: 10.1109/tct.1971.1083337

[3] M. Di. Ventra, Y. V. Pershin, Nature Physics, 2013, 9, N. 4.

[4] A.N. Belov, A.A. Perevalov, V.I. Shevyakov. Memristor structures for micro- and nanoelectronics. Physics and technology. Review, Bulletin of universities. Electronics, 2017, V. 22, No. 4. pp.305-321. DOI: 10.214151 / 1561-5405-2017-22-4-305-321. [RUS].

DOI: 10.24151/1561-5405-2017-22-4-305-321

[5] N. Eliseev. Memristors and crossbars: nanotechnology for processors, Electronics: Science, Technology, Business, 2010, No. 8, p.84–89. [RUS].

[6] J.Yang, D.B. Strukov, D.R. Stewart Memristive devices for computing, Nature Nanotechnology, 2013, V.8, pp.13-24.

[7] S.V. Ryabtsev, A.E. Popov, F.M. Chernyshov, N.S. Ryabtseva, E.P. Domashevskaya. Memristor effect in a sandwich structure based on tin oxide. Condensed media and interphase boundaries, 2012, V. 14, No. 4, pp.456-459. [RUS].

[8] V.A. Shakhnov, A.I. Vlasov, S.V. Tokarev Electrochromic thin-film components for information representation systems, IOP Conference Series: Materials Science and Engineering. 2016, V. 151, N. 012005.

DOI: 10.1088/1757-899x/151/1/012005

[9] V.A. Shakhnov, A.I. Vlasov, V.P. Zhalnin, Methods for improvement of the consistency and durability of the inorganic memristor structures, International Journal of Nanotechnology, 2019, V.16, V.1-3, pp.187-195.

DOI: 10.1504/ijnt.2019.102405

[10] V.A. Shakhnov, I.V. Gudoshnikov, V.P. Zhalnin , A.T. Kadyr, A.I. Vlasov, Market for memristors and data mining memory structures for promising smart systems, Entrepreneurship and Sustainability Issues, 2020, 8(2), p.98–115.

DOI: 10.9770/jesi.2020.8.2(6)

[11] A.I. Vlasov, V.P. Zhalnin, S.P. Prisyazhnuk, Analysis of memristor modules as an element base of microprocessor control systems: Contradictions and prospects, Proceedings - 2020 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2020, 2020, N. 9111917.

DOI: 10.1109/icieam48468.2020.9111917

[12] V.A. Levanov, A.V. Emel'yanov, V.A. Demin, K.E. Nikirui, S.N. Nikolaev, V.V. Ryl'kov, A.V. Sitnikov, Y.E. Kalinin, A.S. Vedeneev, Memristive properties of structures based on (CO41FE39B20)X(LINBO3)100–X nanocomposites, Journal of Communications Technology and Electronics, 2018, V. 63, N.5, pp.491-496.

DOI: 10.1134/s1064226918050078

[13] Rylkov V., Taldenkov A., Demin V., Vedeneev A., Bugaev A., Granovsky A., Chernohlazov K., Nikiruy K., Blinov M., Sitnikov A., Nikolaev S., Fadeev E., Emelyanov A., Drovosekov A., Properties of nanocomposites with different concentrations of magnetic ions in an insulating matrix, IEEE Magnetics Letters. 2019. V. 10. p.8910433.

DOI: 10.1109/lmag.2019.2955060

[14] B.S. Shvetsov, M.N. Martyshov, A.V. Emelyanov, A.A. Minnekhanov, K.E. Nikiruy, A.A. Nesmelov, V.V. Rylkov, V.A. Demin, Synaptic plasticity of memristive structures based on poly-p-xylylene, Nanotechnologies in Russia, 2019, V. 14. N. 1-2.

DOI: 10.1134/s1995078019010105

[15] A.G. Abubakarov, J.A. Reyzenkind, L.A. Reznichenko, M.B. Manuilov, Y.M. Noykin Methods for comprehensive characterization of radar absorbing materials, Physics and Mechanics of New Materials and their Applications (PHENMA 2016), Abstracts & Schedule, 2016, pp.24-25.

[16] A.A. Alekseenko, V.E. Guterman, S.V. Belenov, V.A. Volochaev, Obtaining and study of ptcu/c electrocatalyst, Physics and Mechanics of New Materials and their Applications (PHENMA 2016), Abstracts & Schedule, 2016, pp.42-43.

[17] I.N. Andryushina, K.P. Andryushin, L.A. Reznichenko, L.A. Shilkina, A.G. Abubakarov, O.N. Razumovskaya Real diagram of states and macroresponse in soft-ferroelectric, multicomponent system (PB, SR, BA) (TI, ZR, NB, ZN, MG)O3, Physics and Mechanics of New Materials and their Applications (PHENMA 2016), Abstracts & Schedule, 2016. N. 46.

DOI: 10.1088/1742-6596/2057/1/012060

[18] Nesterov Yu.I., Vlasov A.I., Pershin B.N. Virtual measuring complex. Sensors and systems, 2000, No. 4. pp.12-22. [RUS].