IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v148y2021ics0960077921003787.html
   My bibliography  Save this article

First principles investigation of oxygen vacancies filaments in polymorphic Titania and their role in memristor's applications

Author

Listed:
  • Kousar, Farhana
  • Rasheed, Umbreen
  • Khalil, R. M. Arif
  • Niaz, Niaz Ahmad
  • Hussain, Fayyaz
  • Imran, Muhammad
  • Shakoor, Umema
  • Algadi, Hassan
  • Ashiq, Naeem

Abstract

Inconsistency of resistive switching parameters in memristors is a major challenge in the development of memory devices. These variability issues can be resolved by using materials having capability of easily growing conducting filaments and less value of oxygen vacancy formation energy (OVFE). In this first principle study, device to device variability by the electronic modification subsequently with the creation of the oxygen vacancies in TiO2 phases have been investigated using density functional theory. The lattice constants, OVFE, density of states (DOS), partial density of states (PDOS), iso-surface charge density and integrated charge density are calculated to understand the structural and electronic properties of polytype TiO2 with single-, di- and tri-oxygen vacancy (Vo) at atomistic level. It is found that by introducing the Vos, defect states are formed within the band gap, which caused to increase the conductivity of crystalline phases of TiO2. The conductivity of the phases increased with increasing number of Vos resulting in low resistance state of the opted phase. Existence of various stages of CFs and formation energy at various concentration of Vos predicts the implementation of constructive role of noise to enhance the efficiency and stability of the Titania based memristors. On the basis of easily growing conducing filaments having higher concentration of Vos with lesser OVFE, it is predicted that brookite phase of TiO2 having 3Vos is more suitable in overcoming inconsistency issues related to resistive switching in low power consuming memristors devices.

Suggested Citation

  • Kousar, Farhana & Rasheed, Umbreen & Khalil, R. M. Arif & Niaz, Niaz Ahmad & Hussain, Fayyaz & Imran, Muhammad & Shakoor, Umema & Algadi, Hassan & Ashiq, Naeem, 2021. "First principles investigation of oxygen vacancies filaments in polymorphic Titania and their role in memristor's applications," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
  • Handle: RePEc:eee:chsofr:v:148:y:2021:i:c:s0960077921003787
    DOI: 10.1016/j.chaos.2021.111024
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077921003787
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2021.111024?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. Bernardo Spagnolo & Davide Valenti, 2008. "Volatility Effects on the Escape Time in Financial Market Models," Papers 0810.1625, arXiv.org.
    2. 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).
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jeong, Dong Geun & Park, Eunpyo & Jo, Yooyeon & Yang, Eunyeong & Noh, Gichang & Lee, Dae Kyu & Kim, Min Jee & Jeong, YeonJoo & Jang, Hyun Jae & Joe, Daniel J. & Chang, Jiwon & Kwak, Joon Young, 2024. "Grain boundary control for high-reliability HfO2-based RRAM," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
    2. Koryazhkina, M.N. & Filatov, D.O. & Shishmakova, V.A. & Shenina, M.E. & Belov, A.I. & Antonov, I.N. & Kotomina, V.E. & Mikhaylov, A.N. & Gorshkov, O.N. & Agudov, N.V. & Guarcello, C. & Carollo, A. & S, 2022. "Resistive state relaxation time in ZrO2(Y)-based memristive devices under the influence of external noise," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).

    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. Alsuwian, Turki & Kousar, Farhana & Rasheed, Umbreen & Imran, Muhammad & Hussain, Fayyaz & Arif Khalil, R.M. & Algadi, Hassan & Batool, Najaf & Khera, Ejaz Ahmad & Kiran, Saira & Ashiq, Muhammad Naeem, 2021. "First principles investigation of physically conductive bridge filament formation of aluminum doped perovskite materials for neuromorphic memristive applications," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    2. 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).
    3. 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).
    4. Djohan Bonnet & Tifenn Hirtzlin & Atreya Majumdar & Thomas Dalgaty & Eduardo Esmanhotto & Valentina Meli & Niccolo Castellani & Simon Martin & Jean-François Nodin & Guillaume Bourgeois & Jean-Michel P, 2023. "Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    5. Xiangpeng Liang & Yanan Zhong & Jianshi Tang & Zhengwu Liu & Peng Yao & Keyang Sun & Qingtian Zhang & Bin Gao & Hadi Heidari & He Qian & Huaqiang Wu, 2022. "Rotating neurons for all-analog implementation of cyclic reservoir computing," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    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. Koo, Eunho & Kim, Geonwoo, 2017. "Explicit formula for the valuation of catastrophe put option with exponential jump and default risk," Chaos, Solitons & Fractals, Elsevier, vol. 101(C), pages 1-7.
    8. Yu, Fei & Kong, Xinxin & Yao, Wei & Zhang, Jin & Cai, Shuo & Lin, Hairong & Jin, Jie, 2024. "Dynamics analysis, synchronization and FPGA implementation of multiscroll Hopfield neural networks with non-polynomial memristor," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    9. Zhang, Wenyue & Shi, Peiming & Li, Mengdi & Han, Dongying, 2021. "A novel stochastic resonance model based on bistable stochastic pooling network and its application," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    10. Ruibin Mao & Bo Wen & Arman Kazemi & Yahui Zhao & Ann Franchesca Laguna & Rui Lin & Ngai Wong & Michael Niemier & X. Sharon Hu & Xia Sheng & Catherine E. Graves & John Paul Strachan & Can Li, 2022. "Experimentally validated memristive memory augmented neural network with efficient hashing and similarity search," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    11. Zhang, Xiaofeng & Yuan, Rong, 2021. "Forward attractor for stochastic chemostat model with multiplicative noise," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    12. Bin Gao & Ying Zhou & Qingtian Zhang & Shuanglin Zhang & Peng Yao & Yue Xi & Qi Liu & Meiran Zhao & Wenqiang Zhang & Zhengwu Liu & Xinyi Li & Jianshi Tang & He Qian & Huaqiang Wu, 2022. "Memristor-based analogue computing for brain-inspired sound localization with in situ training," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    13. Li, Jiang-Cheng & Tao, Chen & Li, Hai-Feng, 2022. "Dynamic forecasting performance and liquidity evaluation of financial market by Econophysics and Bayesian methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    14. Zhongfang Zhang & Xiaolong Zhao & Xumeng Zhang & Xiaohu Hou & Xiaolan Ma & Shuangzhu Tang & Ying Zhang & Guangwei Xu & Qi Liu & Shibing Long, 2022. "In-sensor reservoir computing system for latent fingerprint recognition with deep ultraviolet photo-synapses and memristor array," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    15. Dong, Yang & Wen, Shu-hui & Hu, Xiao-bing & Li, Jiang-Cheng, 2020. "Stochastic resonance of drawdown risk in energy market prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    16. Gong, Xiao-li & Zhuang, Xin-tian, 2016. "Option pricing and hedging for optimized Lévy driven stochastic volatility models," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 118-127.
    17. Ren, Lujie & Mou, Jun & Banerjee, Santo & Zhang, Yushu, 2023. "A hyperchaotic map with a new discrete memristor model: Design, dynamical analysis, implementation and application," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    18. Wang, Weiwei & Ralescu, Dan A., 2021. "Valuation of lookback option under uncertain volatility model," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    19. Syed Ghazi Sarwat & Timoleon Moraitis & C. David Wright & Harish Bhaskaran, 2022. "Chalcogenide optomemristors for multi-factor neuromorphic computation," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    20. Duan, Wei-Long & Lin, Ling, 2021. "Noise and delay enhanced stability in tumor-immune responses to chemotherapy system," Chaos, Solitons & Fractals, Elsevier, vol. 148(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:148:y:2021:i:c:s0960077921003787. 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.