IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v153y2021ip1s0960077921008870.html
   My bibliography  Save this article

Multi-level resistance switching and random telegraph noise analysis of nitride based memristors

Author

Listed:
  • Vasileiadis, Nikolaos
  • Loukas, Panagiotis
  • Karakolis, Panagiotis
  • Ioannou-Sougleridis, Vassilios
  • Normand, Pascal
  • Ntinas, Vasileios
  • Fyrigos, Iosif-Angelos
  • Karafyllidis, Ioannis
  • Sirakoulis, Georgios Ch.
  • Dimitrakis, Panagiotis

Abstract

Resistance switching devices are of special importance because of their application in resistive memories (RRAM) which are promising candidates for replacing current nonvolatile memories and realize storage class memories. These devices exhibit usually memristive properties with many discrete resistance levels and implement artificial synapses. The last years, researchers have demonstrated memristive chips as accelerators in computing, following new in-memory and neuromorphic computational approaches. Many different metal oxides have been used as resistance switching materials in MIM or MIS structures. Understanding of the mechanism and the dynamics of resistance switching is very critical for the modeling and use of memristors in different applications. Here, we demonstrate the bipolar resistance switching of silicon nitride thin films using heavily doped Si and Cu as bottom and top-electrodes, respectively. Analysis of the current-voltage characteristics reveal that under space-charge limited conditions and appropriate current compliance setting, multi-level resistance operation can be achieved. Furthermore, a flexible tuning protocol for multi-level resistance switching was developed applying appropriate SET/RESET pulse sequences. Retention and random telegraph noise measurements performed at different resistance levels. The present results reveal the attractive properties of the examined devices.

Suggested Citation

  • Vasileiadis, Nikolaos & Loukas, Panagiotis & Karakolis, Panagiotis & Ioannou-Sougleridis, Vassilios & Normand, Pascal & Ntinas, Vasileios & Fyrigos, Iosif-Angelos & Karafyllidis, Ioannis & Sirakoulis,, 2021. "Multi-level resistance switching and random telegraph noise analysis of nitride based memristors," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
  • Handle: RePEc:eee:chsofr:v:153:y:2021:i:p1:s0960077921008870
    DOI: 10.1016/j.chaos.2021.111533
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077921008870
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2021.111533?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fiasconaro, A & Valenti, D & Spagnolo, B, 2003. "Role of the initial conditions on the enhancement of the escape time in static and fluctuating potentials," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 325(1), pages 136-143.
    2. Can Li & Daniel Belkin & Yunning Li & Peng Yan & Miao Hu & Ning Ge & Hao Jiang & Eric Montgomery & Peng Lin & Zhongrui Wang & Wenhao Song & John Paul Strachan & Mark Barnell & Qing Wu & R. Stanley Wil, 2018. "Efficient and self-adaptive in-situ learning in multilayer memristor neural networks," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    3. Shchanikov, Sergey & Zuev, Anton & Bordanov, Ilya & Danilin, Sergey & Lukoyanov, Vitaly & Korolev, Dmitry & Belov, Alexey & Pigareva, Yana & Gladkov, Arseny & Pimashkin, Alexey & Mikhaylov, Alexey & K, 2021. "Designing a bidirectional, adaptive neural interface incorporating machine learning capabilities and memristor-enhanced hardware," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    4. Peng Yao & Huaqiang Wu & Bin Gao & Jianshi Tang & Qingtian Zhang & Wenqiang Zhang & J. Joshua Yang & He Qian, 2020. "Fully hardware-implemented memristor convolutional neural network," Nature, Nature, vol. 577(7792), pages 641-646, January.
    5. Mikhaylov, A.N. & Guseinov, D.V. & Belov, A.I. & Korolev, D.S. & Shishmakova, V.A. & Koryazhkina, M.N. & Filatov, D.O. & Gorshkov, O.N. & Maldonado, D. & Alonso, F.J. & Roldán, J.B. & Krichigin, A.V. , 2021. "Stochastic resonance in a metal-oxide memristive device," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    6. Surazhevsky, I.A. & Demin, V.A. & Ilyasov, A.I. & Emelyanov, A.V. & Nikiruy, K.E. & Rylkov, V.V. & Shchanikov, S.A. & Bordanov, I.A. & Gerasimova, S.A. & Guseinov, D.V. & Malekhonova, N.V. & Pavlov, D, 2021. "Noise-assisted persistence and recovery of memory state in a memristive spiking neuromorphic network," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kim, Tae-Hyeon & Kim, Sungjoon & Hong, Kyungho & Park, Jinwoo & Hwang, Yeongjin & Park, Byung-Gook & Kim, Hyungjin, 2021. "Multilevel switching memristor by compliance current adjustment for off-chip training of neuromorphic system," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    2. Choi, Woo Sik & Kim, Donguk & Yang, Tae Jun & Chae, Inseok & Kim, Changwook & Kim, Hyungjin & Kim, Dae Hwan, 2022. "Electrode-dependent electrical switching characteristics of InGaZnO memristor," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    3. Agudov, N.V. & Dubkov, A.A. & Safonov, A.V. & Krichigin, A.V. & Kharcheva, A.A. & Guseinov, D.V. & Koryazhkina, M.N. & Novikov, A.S. & Shishmakova, V.A. & Antonov, I.N. & Carollo, A. & Spagnolo, B., 2021. "Stochastic model of memristor based on the length of conductive region," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    4. Lee, Geun Ho & Kim, Tae-Hyeon & Song, Min Suk & Park, Jinwoo & Kim, Sungjoon & Hong, Kyungho & Kim, Yoon & Park, Byung-Gook & Kim, Hyungjin, 2022. "Effect of weight overlap region on neuromorphic system with memristive synaptic devices," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    5. Ping, Zhu, 2023. "Analytical equivalent transformation method for nonlinear stochastic dynamics with multiple noises in high dimensions," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    6. Choi, Woo Sik & Jang, Jun Tae & Kim, Donguk & Yang, Tae Jun & Kim, Changwook & Kim, Hyungjin & Kim, Dae Hwan, 2022. "Influence of Al2O3 layer on InGaZnO memristor crossbar array for neuromorphic applications," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    7. Setoudeh, Farbod & Dezhdar, Mohammad Matin & Najafi, M., 2022. "Nonlinear analysis and chaos synchronization of a memristive-based chaotic system using adaptive control technique in noisy environments," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    8. Jin, Yanfei & Wang, Haotian & Xu, Pengfei, 2023. "Noise-induced enhancement of stability and resonance in a tri-stable system with time-delayed feedback," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    9. Filatov, D.O. & Koryazhkina, M.N. & Novikov, A.S. & Shishmakova, V.A. & Shenina, M.E. & Antonov, I.N. & Gorshkov, O.N. & Agudov, N.V. & Carollo, A. & Valenti, D. & Spagnolo, B., 2022. "Effect of internal noise on the relaxation time of an yttria stabilized zirconia-based memristor," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    10. Ai, Hao & Yang, GuiJiang & Liu, Wei & Wang, Qiubao, 2023. "A fast search method for optimal parameters of stochastic resonance based on stochastic bifurcation and its application in fault diagnosis of rolling bearings," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    11. Taheri, Alireza Ghomi & Setoudeh, Farbod & Tavakoli, Mohammad Bagher & Feizi, Esmaeil, 2022. "Nonlinear analysis of memcapacitor-based hyperchaotic oscillator by using adaptive multi-step differential transform method," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    12. Setoudeh, Farbod & Dousti, Massoud, 2022. "Analysis and implementation of a meminductor-based colpitts sinusoidal oscillator," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    13. Lin, Lifeng & Lin, Tianzhen & Zhang, Ruoqi & Wang, Huiqi, 2023. "Generalized stochastic resonance in a time-delay fractional oscillator with damping fluctuation and signal-modulated noise," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    14. Maldonado, D. & Aguilera-Pedregosa, C. & Vinuesa, G. & García, H. & Dueñas, S. & Castán, H. & Aldana, S. & González, M.B. & Moreno, E. & Jiménez-Molinos, F. & Campabadal, F. & Roldán, J.B., 2022. "An experimental and simulation study of the role of thermal effects on variability in TiN/Ti/HfO2/W resistive switching nonlinear devices," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    15. Tan, Yiping & Cai, Yongli & Sun, Xiaodan & Wang, Kai & Yao, Ruoxia & Wang, Weiming & Peng, Zhihang, 2022. "A stochastic SICA model for HIV/AIDS transmission," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    16. Mahata, Chandreswar & Kim, Sungjun, 2021. "Electrical and optical artificial synapses properties of TiN-nanoparticles incorporated HfAlO-alloy based memristor," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    17. Ryu, Hojeong & Kim, Sungjun, 2021. "Implementation of a reservoir computing system using the short-term effects of Pt/HfO2/TaOx/TiN memristors with self-rectification," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    18. Park, Jinwoo & Kim, Tae-Hyeon & Kim, Sungjoon & Lee, Geun Ho & Nili, Hussein & Kim, Hyungjin, 2021. "Conduction mechanism effect on physical unclonable function using Al2O3/TiOX memristors," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    19. Han, Cheng & Wang, Yan & Jiang, Daqing, 2023. "Dynamics analysis of a stochastic HIV model with non-cytolytic cure and Ornstein–Uhlenbeck process," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    20. Parshina, Liubov & Novodvorsky, Oleg & Khramova, Olga & Gusev, Dmitriy & Polyakov, Alexander & Cherebilo, Elena, 2022. "Tuning the resistive switching in tantalum oxide-based memristors by oxygen pressure during low temperature laser synthesis," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:153:y:2021:i:p1:s0960077921008870. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.