INVESTIGATION OF SYNAPTIC PLASTICITY IN MEMRISTIVE CROSS-POINT STRUCTURES FOR NEUROMORPHIC ROBOTIC SYSTEMS
Abstract
The results show multilevel resistive switching and synaptic plasticity of a memristive cross-point based on a nanocrystalline zinc oxide film. It is shown that with a decrease in the amplitude and duration of input pulses, the memristive cross-point demonstrates resistive states from 4.27 × 105 Ohm to 8.34 × 107 Ohm. It is shown that the switching energy of some synaptic levels is picojoules, which is promising for creating compact low-power neuromorphic systems. Thus, it is shown that nanocrystalline ZnO films have synaptic plasticity, i.e. When applying voltage pulses, large limits and duration can vary depending on the synaptic levels. The fabricated memristive cross-point demonstrates paired-pulse facilitation PPF at tp from 1 ms to 10 ms and pair-pulse depression PPD at tp from 50 ms to 100 ms. The analysis of the experimental results of the PPF and PPD study showed that an increase in the number of pulses from 10 to 90 leads to an increase in postsynaptic current EPSC from 32 μA to 73 μA for tp = 1 ms, from 31 μA to 59 μA for tp = 5 ms, from 31 μA to 48 μA for tp = 10 ms, and a decrease in EPSC from 30 μA to 25 μA for tp = 50 ms, from 30 μA to 17 μA for tp = 70 ms, from 30 μA to 5 μA for tp = 100 ms. From the obtained results it follows that the interval between pulses, the higher the PPF index, thus it can be concluded that the manufactured memristive cross-point based on ZnO nanocrystalline films imitates the crucial plasticity of the biological synapse, in which the plasticity of PPF and PPD is determined by the concentration of Ca+ ions and which plays a role in many biological functions of the brain, such as determining the key source of sound, pattern recognition, associative learning, filtering unnecessary. information. The obtained results can be used for hardware implementation of neural networks, neuromorphic structures of robotic complexes, prostheses and artificial intelligence systems
References
1. Das S., Dey A., Pal A., & Roy N. Role of artificial intelligence and machine learning in nanosafety, Small, 2020, Vol. 16, No. 36, pp. 2001883.
2. Guo K., Yang Z., Yu C.H., Buehler M.J. Artificial intelligence and machine learning in design of mechan-ical materials, Materials Horizons, 2021, Vol. 8, No. 4, pp. 1153-1172.
3. Demin V.A., Emelyanov A.V., Lapkin D.A., Erokhin V.V., Kashkarov P.K., Kovalchuk M.V. Neuromor-phic elements and systems as the basis for the physical implementation of artificial intelligence technolo-gies, Crystallography Reports, 2016, No. 1 (61), pp. 992-1001.
4. Tominov R.V., Vakulov Z.E., Avilov V.I., Shikhovtsov I.A., Smirnov V.A. Issledovanie vliyaniya materiala kontaktov i tolshchiny plenok na rezistivnoe pereklyuchenie v ne trebuyushchikh formovki nanokristalli-cheskikh plenkakh ZnO dlya neyromorfnykh ustroystv na osnove memristornykh struktur [Study of the influence of contact material and film thickness on resistive switching in mold-free nanocrystalline ZnO films for neuromorphic devices based on memristor structures], Nanoindustriya [Nanoindustry], 2022, Vol. 15, No. S8-2, pp. 509-515.
5. Shchanikov S.A., Bordanov I.A., Zuev A.D., Danilin S.N., Korolev D.S., Belov A.I., Mikhaylov A.N. Primenenie sistemnogo podkhoda pri sozdanii iskusstvennykh neyronnykh setey na baze memristorov [Application of a systems approach to creating artificial neural networks based on memristors], Ney-rokomp'yutery i ikh primenenie [Neurocomputers and Their Application], 2020, pp. 18-23.
6. Rozhnova M.A., Pankratova E.V., Stasenko S.V., Kazantsev V.B. Bifurcation analysis of multistability and oscillation emergence in a model of brain extracellular matrix, Chaos, Solitons & Fractals, 2021, No. 1 (151), pp. 111253.
7. Tominov R., Avilov V., Vakulov Z., Khakhulin D., Ageev O., Valov I., Smirnov V. Forming‐Free Resis-tive Switching of Electrochemical Titanium Oxide Localized Nanostructures: Anodization, Chemical Composition, Nanoscale Size Effects, and Memristive Storage, Advanced Electronic Materials, 2022, No. 8 (8), pp. 2200215.
8. Tikhov S.V., Gorshkov O.N., Antonov I.N., Tetel'baum D.I., Mikhaylov A.N., Belov A.I., Morozov A.I. Osobennosti povedeniya MDP memristorov s nanosloem Si _3 N _4, izgotovlennykh na osnove provodyashchey podlozhki Si [Features of the behavior of MIS memristors with a Si_3N_4 nanolayer, manufactured on the basis of a conductive Si substrate], Fizika i tekhnika poluprovodnikov [Physics and Technology of Semiconductors], 2018, Vol. 52, No. 12, pp. 1436-1442.
9. Tominov R.V., Vakulov Z.E., Avilov V.I., Smirnov V.A., Ageev O.A. Issledovanie rezistivnogo pereklyucheniya ne trebuyushchikh formovki nanokristallicheskikh plenok oksida tsinka dlya ney-romorfnykh sistem iskusstvennogo intellekta [Study of resistive switching of mold-free nanocrystalline zinc oxide films for neuromorphic artificial intelligence systems], Nanoindustriya [Nanoindustry], 2020, Vol. 13, No. S5-3, pp. 733-739.
10. Kruglov A.V., Serov D.A., Belov A.I., Koryazhkina M.N., Antonov I.N., Zubkov S.Yu., Gorshkov O.N. Memristory dlya energonezavisimoy rezistivnoy pamyati na osnove dvukhsloynogo dielektrika Al _2 O _3/ZrO _2 (Y) [Memristors for non-volatile resistive memory based on a two-layer dielectric Al_2O_3/ZrO_2(Y)], Zhurnal tekhnicheskoy fiziki [Journal of Technical Physics], 2024, Vol. 94,
No. 11, pp. 1833-1842.
11. Tominov R.V., Vakulov Z.E., Avilov V.I., Khakhulin D.A., Fedotov A.A., Zamburg E.G., Ageev O.A. Synthesis and memristor effect of a forming-free ZnO nanocrystalline films, Nanomaterials, 2020,
No. 5 (10), pp. 1007.
12. Smirnov V.A., Tominov R.V., Avilov V.I., Alyab'eva N.I., Vakulov Z.E., Zamburg E.G., Ageev O.A. Issle-dovanie memristornogo effekta v nanokristallicheskikh plenkakh ZnO [Study of the memristor effect in nanocrystalline ZnO films], Fizika i tekhnika poluprovodnikov [Physics and Technology of Semiconduc-tors], 2019, No. 1 (53), pp. 77-82.
13. Tikhov S.V., Gorshkov O.N., Antonov I.N., Kasatkin A.P., Korolev D.S., Belov A.I., Tetel'baum D.I. Izmenenie immitansa pri elektroformovke i rezistivnom pereklyuchenii v memristivnykh strukturakh “metall–dielektrik–metall” na osnove SiO _x [Change in immittance during electroforming and resistive switching in memristive metal–insulator–metal structures based on SiO_x], Zhurnal tekhnicheskoy fiziki [Journal of Technical Physics], 2016, Vol. 86, No. 5, pp. 107-111.
14. Prezioso M., Merrikh-Bayat F., Hoskins B.D., Adam G.C., Likharev K.K., Strukov, D.B. Training and operation of an integrated neuromorphic network based on metal-oxide memristors, Nature, 2015, Vol. 521, No. 7550, pp. 61-64.
15. Belov A.I., Mikhaylov A.N., Korolev D.S., Sergeev V.A., Antonov I.N., Gorshkov O.N., Tetel'baum D.I. Rezistivnoe pereklyuchenie v memristivnykh strukturakh Au/SiO _x/TiN/Ti s razlichnymi geometrich-eskimi parametrami i stekhiometriey dielektricheskoy plenki [Resistive switching in Au/SiO_x/TiN/Ti memristive structures with different geometric parameters and stoichiometry of the dielectric film], Pis'ma v Zhurnal tekhnicheskoy fiziki [Letters to the Journal of Technical Physics], 2016, Vol. 42, No. 10, pp. 17-24.
16. Smirnov V.A., Tominov R.V., Avilov V.I., Ageev O.A. Issledovanie forming-free rezistivnogo pereklyucheniya nanokristallicheskikh plenok oksida tsinka dlya sozdaniya neyromorfnykh sistem [Study of forming-free resistive switching of nanocrystalline zinc oxide films for creating neuromorphic systems], Nanoindustriya [Nanoindustry], 2020, Vol. 13, No. S4, pp. 581-582.
17. Tikhov S.V., SHengurov V.G., Denisov S.A., Antonov I.N., Kruglov A.V., Belov A.I., Mikhaylov A.N. Rezistivnoe pereklyuchenie v strukturakh metall–oksid–poluprovodnik s nanoostrovkami GeSi na pod-lozhke kremniya [Resistive switching in metal-oxide-semiconductor structures with GeSi nanoislands on a silicon substrate], Zhurnal tekhnicheskoy fiziki [Journal of Technical Physics], 2020, Vol. 90, No. 10, pp. 1741-1749.
18. Gale E. TiO2-based memristors and ReRAM: materials, mechanisms and models (a review), Semicon-ductor Science and Technology, 2014, No. 10 (29), pp. 104004.
19. Tikhov S.V., Gorshkov O.N., Belov A.I., Antonov I.N., Morozov A.I., Koryazhkina M.N., Mikhaylov A.N. Mekhanizmy tokoperenosa i rezistivnogo pereklyucheniya v kondensatorakh so sloyami stabilizirovan-nogo ittriem dioksida gafniya [Mechanisms of current transport and resistive switching in capacitors with yttrium-stabilized hafnium dioxide layers], Zhurnal tekhnicheskoy fiziki [Journal of Technical Phys-ics], 2019, Vol. 89, No. 6, pp. 927-934.
20. Yoon J.H., Wang Z., Kim K.M., Wu H., Ravichandran V., Xia Q., Yang J.J. An artificial nociceptor based on a diffusive memristor, Nature communications, 2018, Vol. 9, No. 1, pp. 417.
21. Filatov D.O., Antonov D.A., Antonov I.N., Belov A.I., Baranova V.N., Shenina M.E., Gorshkov O.N. Rezistivnoe pereklyuchenie memristorov na osnove stabilizirovannogo dioksida tsirkoniya slozhnymi signalami [Resistive switching of memristors based on stabilized zirconium dioxide by complex signals], Fizika tverdogo tela [Solid State Physics], 2020, Vol. 62, No. 4, pp. 556-561.
22. Tominov R.V., Vakulov Z.E., Polupanov N.V., Saenko A.V., Avilov V.I., Ageev O.A., Smirnov V.A. Na-noscale-Resistive Switching in Forming-Free Zinc Oxide Memristive Structures, Nanomaterials, 2022, No. 3 (12), pp. 455.
