SpringerLink
Log in

Emerging of two-dimensional materials in novel memristor

  • Topical Review
  • Published:
Frontiers of Physics Aims and scope Submit manuscript

Abstract

The rapid development of big-data analytics (BDA), internet of things (IoT) and artificial intelligent Technology (AI) demand outstanding electronic devices and systems with faster processing speed, lower power consumption, and smarter computer architecture. Memristor, as a promising Non-Volatile Memory (NVM) device, can effectively mimic biological synapse, and has been widely studied in recent years. The appearance and development of two-dimensional materials (2D material) accelerate and boost the progress of memristor systems owing to a bunch of the particularity of 2D material compared to conventional transition metal oxides (TMOs), therefore, 2D material-based memristors are called as new-generation intelligent memristors. In this review, the memristive (resistive switching) phenomena and the development of new-generation memristors are demonstrated involving graphene (GR), transition-metal dichalcogenides (TMDs) and hexagonal boron nitride (h-BN) based memristors. Moreover, the related progress of memristive mechanisms is remarked.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. D. B. Strukov, G. S. Snider, D. R. Stewart, and R. S. Williams, The missing memristor found, Nature 453 (7191), 80 (2008)

    ADS  Google Scholar 

  2. J. J. Yang, M. D. Pickett, X. Li, D. A. Ohlberg, D. R. Stewart, and R. S. Williams, Memristive switching mechanism for metal/oxide/metal nanodevices, Nat. Nanotechnol. 3(7), 429 (2008)

    Google Scholar 

  3. L. Chua, Memristor — The missing circuit element, IEEE Trans. Circuit Theory 18(5), 507 (1971)

    Google Scholar 

  4. Y. Yang and W. Lu, Nanoscale resistive switching devices: Mechanisms and modeling, Nanoscale 5(21), 10076 (2013)

    ADS  Google Scholar 

  5. D. Ielmini, Resistive switching memories based on metal oxides: Mechanisms, reliability and scaling, Semicond. Sci. Technol. 31(6), 063002 (2016)

    ADS  Google Scholar 

  6. F. Hui, E. Grustan-Gutierrez, S. Long, Q. Liu, A. K. Ott, A. C. Ferrari, and M. Lanza, Graphene and related materials for resistive random access memories, Adv. Electron. Mater. 3(8), 1600195 (2017)

    Google Scholar 

  7. J. Lee and W. D. Lu, On-demand reconfiguration of nanomaterials: When electronics meets ionics, Adv. Mater. 30(1), 1702770 (2018)

    Google Scholar 

  8. T. Zanotti, F. M. Puglisi, and P. Pavan, Smart logic-in-memory architecture for low-power non-Von Neumann computing, IEEE J. Electron. Dev. Soc. 8, 757 (2020)

    Google Scholar 

  9. P. M. Sheridan, F. Cai, C. Du, W. Ma, Z. Zhang, and W. D. Lu, Sparse coding with memristor networks, Nat. Nanotechnol. 12(8), 784 (2017)

    Google Scholar 

  10. D. H. Lim, S. Wu, R. Zhao, J. H. Lee, H. Jeong, and L. Shi, Sporntaneous sparse learning for PCM-based memristor neural networks, Nat. Commun. 12, 319 (2021)

    Google Scholar 

  11. C. Du, F. Cai, M. A. Zidan, W. Ma, S. H. Lee, and W. D. Lu, Reservoir computing using dynamic memristors for temporal information processing, Nat. Commun. 8, 2204 (2017)

    ADS  Google Scholar 

  12. J. H. Yoon, Z. Wang, K. M. Kim, H. Wu, V. Ravichandran, Q. **a, C. S. Hwang, and J. J. Yang, An artificial nociceptor based on a diffusive memristor, Nat. Commun. 9(1), 417 (2018)

    ADS  Google Scholar 

  13. J. Kim, Y. V. Pershin, M. Yin, T. Datta, and M. Di Ventra, An experimental proof that resistance-switching memory cells are not memristors, Adv. Electron. Mater. 6(7), 2000010 (2020)

    Google Scholar 

  14. Y. V. Pershin and M. Di Ventra, A simple test for ideal memristors, J. Phys. D Appl. Phys. 52(1), 01LT01 (2018)

    Google Scholar 

  15. J. J. Yang, D. B. Strukov, and D. R. Stewart, Memristive devices for computing, Nat. Nanotechnol. 8(1), 13 (2013)

    ADS  Google Scholar 

  16. Z. Wang, M. Rao, R. Midya, S. Joshi, H. Jiang, P. Lin, W. Song, S. Asapu, Y. Zhuo, C. Li, H. Wu, Q. **a, and J. J. Yang, Threshold switching of Ag or Cu in dielectrics: Materials, mechanism, and applications, Adv. Funct. Mater. 28(6), 1704862 (2018)

    Google Scholar 

  17. M. A. Zidan, J. P. Strachan, and W. D. Lu, The future of electronics based on memristive systems, Nat. Electron. 1(1), 22 (2018)

    Google Scholar 

  18. B. Govoreanu, G. Kar, Y. Chen, V. Paraschiv, et al., 10 nm×10 nm Hf/HfOx crossbar resistive RAM with excellent performance, reliability and low-energy operation, 2011 International Electron Devices Meeting, IEEE, p. 31.6.1 (2011)

  19. A. C. Torrezan, J. P. Strachan, G. Medeiros-Ribeiro, and R. S. Williams, Sub-nanosecond switching of a tantalum oxide memristor, Nanotechnology 22(48), 485203 (2011)

    Google Scholar 

  20. S. Goswami, A. J. Matula, S. P. Rath, S. Hedström, S. Saha, M. Annamalai, D. Sengupta, A. Patra, S. Ghosh, H. Jani, S. Sarkar, M. R. Motapothula, C. A. Nijhuis, J. Martin, S. Goswami, V. S. Batista, and T. Venkatesan, Robust resistive memory devices using solution-processable metal-coordinated azo aromatics, Nat. Mater. 16(12), 1216 (2017)

    ADS  Google Scholar 

  21. A. M. Mostafa and A. A. Menazea, Laser-assisted for preparation ZnO/CdO thin film prepared by pulsed laser deposition for catalytic degradation, Radiat. Phys. Chem. 176, 109020 (2020)

    Google Scholar 

  22. K. H. Kim, S. Hyun Jo, S. Gaba, and W. Lu, Nanoscale resistive memory with intrinsic diode characteristics and long endurance, Appl. Phys. Lett. 96(5), 053106 (2010)

    ADS  Google Scholar 

  23. X. Feng, Y. Li, L. Wang, S. Chen, Z. G. Yu, W. C. Tan, N. Macadam, G. Hu, L. Huang, L. Chen, X. Gong, D. Chi, T. Hasan, A. V. Y. Thean, Y. W. Zhang, and K. W. Ang, A fully printed flexible MoS2 memristive artificial synapse with femtojoule switching energy, Adv. Electron. Mater. 5(12), 1900740 (2019)

    Google Scholar 

  24. X. Yan, Q. Zhao, A. P. Chen, J. Zhao, Z. Zhou, J. Wang, H. Wang, L. Zhang, X. Li, Z. **ao, K. Wang, C. Qin, G. Wang, Y. Pei, H. Li, D. Ren, J. Chen, and Q. Liu, Vacancy-induced synaptic behavior in 2D WS2 nanosheet-based memristor for low-power neuromorphic computing, Small 15(24), 1901423 (2019)

    Google Scholar 

  25. B. Radisavljevic, A. Radenovic, J. Brivio, V. Giacometti, and A. Kis, Single-layer MoS2 transistors, Nat. Nanotechnol. 6(3), 147 (2011)

    ADS  Google Scholar 

  26. J. Jiang and Z. Ni, Defect engineering in two-dimensional materials, J. Semicond. 40(7), 070403 (2019)

    ADS  Google Scholar 

  27. A. Sawa, Resistive switching in transition metal oxides, Mater. Today 11(6), 28 (2008)

    Google Scholar 

  28. A. Wedig, M. Luebben, D. Y. Cho, M. Moors, K. Skaja, V. Rana, T. Hasegawa, K. K. Adepalli, B. Yildiz, R. Waser, and I. Valov, Nanoscale cation motion in TaOx, HfOx and TiOx memristive systems, Nat. Nanotechnol. 11(1), 67 (2016)

    ADS  Google Scholar 

  29. S. Choi, S. H. Tan, Z. Li, Y. Kim, C. Choi, P. Y. Chen, H. Yeon, S. Yu, and J. Kim, SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations, Nat. Mater. 17(4), 335 (2018)

    ADS  Google Scholar 

  30. D. B. Strukov, Tightening grip, Nat. Mater. 17(4), 293 (2018)

    ADS  Google Scholar 

  31. D. Ielmini, R. Bruchhaus, and R. Waser, Thermochemical resistive switching: Materials, mechanisms, and scaling projections, Phase Transit. 84(7), 570 (2011)

    Google Scholar 

  32. Y. Zhang, X. Wang, and E. G. Friedman, Memristor-based circuit design for multilayer neural networks, IEEE Trans. Circuits Syst. I Regul. Pap. 65(2), 677 (2017)

    Google Scholar 

  33. P. Wijesinghe, A. Ankit, A. Sengupta, and K. Roy, An all-memristor deep spiking neural computing system: A step toward realizing the low-power stochastic brain, IEEE Transactions on Emerging Topics in Computational Intelligence 2(5), 345 (2018)

    Google Scholar 

  34. T. Kim, S. Hu, J. Kim, J. Y. Kwak, J. Park, S. Lee, I. Kim, J. K. Park, and Y. J. Jeong, Spiking neural network (SNN) with memristor synapses having non-linear weight update, Front. Comput. Neurosci. 15, 22 (2021)

    Google Scholar 

  35. A. S. Sokolov, H. Abbas, Y. Abbas, and C. Choi, Towards engineering in memristors for emerging memory and neuromorphic computing: A review, J. Semicond. 42(1), 013101 (2021)

    Google Scholar 

  36. L. **e, H. A. Du Nguyen, M. Taouil, S. Hamdioui, et al., Fast boolean logic mapped on memristor crossbar, 2015 33rd IEEE International Conference on Computer Design (ICCD), IEEE, p. 335 (2015)

  37. H. Tan, G. Liu, H. Yang, X. Yi, L. Pan, J. Shang, S. Long, M. Liu, Y. Wu, and R. W. Li, Light-gated memristor with integrated logic and memory functions, ACS Nano 11(11), 11298 (2017)

    Google Scholar 

  38. L. Xu, R. Yuan, Z. Zhu, K. Liu, Z. **g, Y. Cai, Y. Wang, Y. Yang, and R. Huang, Memristor-based efficient in-memory logic for cryptologic and arithmetic applications, Adv. Mater. Technol. 4(7), 1900212 (2019)

    Google Scholar 

  39. S. Hussain, K. Xu, S. Ye, L. Lei, X. Liu, R. Xu, L. **e, and Z. Cheng, Local electrical characterization of two-dimensional materials with functional atomic force microscopy, Front. Phys. 14(3), 33401 (2019)

    ADS  Google Scholar 

  40. L. Meng, Y. Ma, K. Si, S. Xu, J. Wang, and Y. Gong, Recent advances of phase engineering in group VI transition metal dichalcogenides, Tungsten 1(1), 46 (2019)

    Google Scholar 

  41. J. Lee, C. Du, K. Sun, E. Kioupakis, and W. D. Lu, Tuning ionic transport in memristive devices by graphene with engineered nanopores, ACS Nano 10(3), 3571 (2016)

    Google Scholar 

  42. X. Zhao, J. Ma, X. **ao, Q. Liu, L. Shao, D. Chen, S. Liu, J. Niu, X. Zhang, Y. Wang, R. Cao, W. Wang, Z. Di, H. Lv, S. Long, and M. Liu, Breaking the current-retention dilemma in cation-based resistive switching devices utilizing graphene with controlled defects, Adv. Mater. 30(14), 1705193 (2018)

    Google Scholar 

  43. V. K. Sangwan, D. Jariwala, I. S. Kim, K. S. Chen, T. J. Marks, L. J. Lauhon, and M. C. Hersam, Gate-tunable memristive phenomena mediated by grain boundaries in single-layer MoS2, Nat. Nanotechnol. 10(5), 403 (2015)

    ADS  Google Scholar 

  44. R. Ge, X. Wu, M. Kim, J. Shi, S. Sonde, L. Tao, Y. Zhang, J. C. Lee, and D. Akinwande, Atomristor: Nonvolatile resistance switching in atomic sheets of transition metal dichalcogenides, Nano Lett. 18(1), 434 (2018)

    ADS  Google Scholar 

  45. R. Ge, X. Wu, L. Liang, S. M. Hus, Y. Gu, E. Okogbue, H. Chou, J. Shi, Y. Zhang, S. K. Banerjee, Y. Jung, J. C. Lee, and D. Akinwande, A library of atomically thin 2D materials featuring the conductive-point resistive switching phenomenon, Adv. Mater. 33(7), e2007792 (2021)

    ADS  Google Scholar 

  46. H. Zhao, Z. Dong, H. Tian, D. DiMarzi, M. G. Han, L. Zhang, X. Yan, F. Liu, L. Shen, S. J. Han, S. Cronin, W. Wu, J. Tice, J. Guo, and H. Wang, Atomically thin femtojoule memristive device, Adv. Mater. 29(47), 1703232 (2017)

    Google Scholar 

  47. Q. Zhao, Z. **e, Y. P. Peng, K. Wang, H. Wang, X. Li, H. Wang, J. Chen, H. Zhang, and X. Yan, Current status and prospects of memristors based on novel 2D materials, Mater. Horiz. 7(6), 1495 (2020)

    Google Scholar 

  48. Y. Cao, V. Fatemi, A. Demir, S. Fang, S. L. Tomarken, J. Y. Luo, J. D. Sanchez-Yamagishi, K. Watanabe, T. Taniguchi, E. Kaxiras, R. C. Ashoori, and P. Jarillo-Herrero, Correlated insulator behaviour at half-filling in magic-angle graphene superlattices, Nature 556(7699), 80 (2018)

    ADS  Google Scholar 

  49. J. M. Park, Y. Cao, K. Watanabe, T. Taniguchi, and P. Jarillo-Herrero, Tunable phase boundaries and ultra-strong coupling superconductivity in mirror symmetric magic-angle trilayer graphene, ar**v: 2012.01434 (2020)

  50. J. W. Jiang, Graphene versus MoS2: A short review, Front. Phys. 10(3), 287 (2015)

    ADS  Google Scholar 

  51. R. Wang, X. G. Ren, Z. Yan, L. J. Jiang, W. E. I. Sha, and G. C. Shan, Graphene based functional devices: A short review, Front. Phys. 14(1), 13603 (2019)

    ADS  Google Scholar 

  52. X. M. Huang, L. Z. Liu, S. Zhou, and J. J. Zhao, Physical properties and device applications of graphene oxide, Front. Phys. 15(3), 33301 (2020)

    ADS  Google Scholar 

  53. Q. A. Vu, H. Kim, V. L. Nguyen, U. Y. Won, S. Adhikari, K. Kim, Y. H. Lee, and W. J. Yu, A high-on/off-ratio floating-gate memristor array on a flexible substrate via CVD-grown large-area 2D layer stacking, Adv. Mater. 29(44), 1703363 (2017)

    Google Scholar 

  54. L. Pósa, M. El Abbassi, P. Makk, B. Sánta, C. Nef, M. Csontos, M. Calame, and A. Halbritter, Multiple physical time scales and dead time rule in few-nanometers sized graphene-SiOx-graphene memristors, Nano Lett. 17(11), 6783 (2017)

    ADS  Google Scholar 

  55. Y. Ji, S. A. Lee, A. N. Cha, M. Goh, S. Bae, S. Lee, D. I. Son, and T. W. Kim, Resistive switching characteristics of ZnO-graphene quantum dots and their use as an active component of an organic memory cell with one diode-one resistor architecture, Org. Electron. 18, 77 (2015)

    Google Scholar 

  56. D. I. Son, T. W. Kim, J. H. Shim, J. H. Jung, D. U. Lee, J. M. Lee, W. I. Park, and W. K. Choi, Flexible organic bistable devices based on graphene embedded in an insulating poly(methyl methacrylate) polymer layer, Nano Lett. 10(7), 2441 (2010)

    ADS  Google Scholar 

  57. Y. T. Chan, Y. Fu, L. Yu, F. Y. Wu, H. W. Wang, T. H. Lin, S. H. Chan, M. C. Wu, and J. C. Wang, Compacted self-assembly graphene with hydrogen plasma surface modification for robust artificial electronic synapses of gadolinium oxide memristors, Adv. Mater. Inter-faces 7(20), 2000860 (2020)

    Google Scholar 

  58. T. Berzina, K. Gorshkov, V. Erokhin, V. Nevolin, and Y. A. Chaplygin, Investigation of electrical properties of organic memristors based on thin polyaniline-graphene films, Russ. Microelectron. 42(1), 27 (2013)

    Google Scholar 

  59. H. He, J. Klinowski, M. Forster, and A. Lerf, A new structural model for graphite oxide, Chem. Phys. Lett. 287(1–2), 53 (1998)

    ADS  Google Scholar 

  60. S. Qin, J. Zhang, D. Fu, D. **e, Y. Wang, H. Qian, L. Liu, and Z. Yu, A physics/circuit-based switching model for carbon-based resistive memory with sp2/sp3 cluster conversion, Nanoscale 4(20), 6658 (2012)

    ADS  Google Scholar 

  61. H. Y. Jeong, J. Y. Kim, J. W. Kim, J. O. Hwang, J. E. Kim, J. Y. Lee, T. H. Yoon, B. J. Cho, S. O. Kim, R. S. Ruoff, and S. Y. Choi, Graphene oxide thin films for flexible nonvolatile memory applications, Nano Lett. 10(11), 4381 (2010)

    ADS  Google Scholar 

  62. F. Zhao, L. Wang, Y. Zhao, L. Qu, and L. Dai, Graphene oxide nanoribbon assembly toward moisture-powered information storage, Adv. Mater. 29(3), 1604972 (2017)

    Google Scholar 

  63. M. Lübben, S. Wiefels, R. Waser, and I. Valov, Processes and effects of oxygen and moisture in resistively switching TaOx and HfOx, Adv. Electron. Mater. 4(1), 1700458 (2018)

    Google Scholar 

  64. F. Zhuge, B. Hu, C. He, X. Zhou, Z. Liu, and R. W. Li, Mechanism of nonvolatile resistive switching in graphene oxide thin films, Carbon 49(12), 3796 (2011)

    Google Scholar 

  65. D. P. Sahu, P. Jetty, and S. N. Jammalamadaka, Graphene oxide based synaptic memristor device for neuromorphic computing, Nanotechnology 32(15), 155701 (2021)

    ADS  Google Scholar 

  66. J. Liu, Z. Zeng, X. Cao, G. Lu, L. H. Wang, Q. L. Fan, W. Huang, and H. Zhang, Preparation of MoS2-polyvinylpyrrolidone nanocomposites for flexible nonvolatile rewritable memory devices with reduced graphene oxide electrodes, Small 8(22), 3517 (2012)

    Google Scholar 

  67. C. Tan, X. Qi, Z. Liu, F. Zhao, H. Li, X. Huang, L. Shi, B. Zheng, X. Zhang, L. **e, Z. Tang, W. Huang, and H. Zhang, Self-assembled chiral nanofibers from ultra-thin low-dimensional nanomaterials, J. Am. Chem. Soc. 137(4), 1565 (2015)

    Google Scholar 

  68. J. Yuan and J. Lou, Memristor goes two-dimensional, Nat. Nanotechnol. 10(5), 389 (2015)

    ADS  Google Scholar 

  69. P. Cheng, K. Sun, and Y. H. Hu, Memristive behavior and ideal memristor of 1T phase MoS2 nanosheets, Nano Lett. 16(1), 572 (2016)

    ADS  Google Scholar 

  70. M. Yoshida, R. Suzuki, Y. Zhang, M. Nakano, and Y. Iwasa, Memristive phase switching in two-dimensional 1T-TaS2 crystals, Sci. Adv. 1(9), e1500606 (2015)

    ADS  Google Scholar 

  71. S. M. Hus, R. Ge, P. A. Chen, L. Liang, G. E. Donnelly, W. Ko, F. Huang, M. H. Chiang, A. P. Li, and D. Akinwande, Observation of single-defect memristor in an MoS2 atomic sheet, Nat. Nanotechnol. 16, 58 (2020)

    ADS  Google Scholar 

  72. M. Wang, S. Cai, C. Pan, C. Wang, X. Lian, Y. Zhuo, K. Xu, T. Cao, X. Pan, B. Wang, S. J. Liang, J. J. Yang, P. Wang, and F. Miao, Robust memristors based on layered two-dimensional materials, Nat. Electron. 1(2), 130 (2018)

    Google Scholar 

  73. H. K. He, R. Yang, W. Zhou, H. M. Huang, J. **ong, L. Gan, T. Y. Zhai, and X. Guo, Photonic potentiation and electric habituation in ultrathin memristive synapses based on monolayer MoS2, Small 14(15), 1800079 (2018)

    Google Scholar 

  74. S. Chen, Z. Lou, D. Chen, and G. Shen, An artificial flexible visual memory system based on an UV-motivated memristor, Adv. Mater. 30(7), 1705400 (2018)

    Google Scholar 

  75. G. U. Siddiqui, M. M. Rehman, Y. J. Yang, and K. H. Choi, A two-dimensional hexagonal boron nitride/polymer nanocomposite for flexible resistive switching devices, J. Mater. Chem. C 5(4), 862 (2017)

    Google Scholar 

  76. C. Pan, Y. Ji, N. **ao, F. Hui, K. Tang, Y. Guo, X. **e, F. M. Puglisi, L. Larcher, E. Miranda, L. Jiang, Y. Shi, I. Valov, P. C. McIntyre, R. Waser, and M. Lanza, Coexistence of grain-boundaries-assisted bipolar and threshold resistive switching in multilayer hexagonal boron nitride, Adv. Funct. Mater. 27(10), 1604811 (2017)

    Google Scholar 

  77. X. Wu, R. Ge, P. A. Chen, H. Chou, Z. Zhang, Y. Zhang, S. Banerjee, M. H. Chiang, J. C. Lee, and D. Akinwande, Thinnest nonvolatile memory based on monolayer h-BN, Adv. Mater. 31(15), 1806790 (2019)

    Google Scholar 

  78. S. Chen, M. R. Mahmoodi, Y. Shi, C. Mahata, B. Yuan, X. Liang, C. Wen, F. Hui, D. Akinwande, D. B. Strukov, and M. Lanza, Wafer-scale integration of two-dimensional materials in high-density memristive crossbar arrays for artificial neural networks, Nat. Electron. 3(10), 638 (2020)

    Google Scholar 

  79. W. Lv, H. Wang, L. Jia, X. Tang, C. Lin, L. Yuwen, L. Wang, W. Huang, and R. Chen, Tunable nonvolatile memory behaviors of PCBM-MoS2 2D nanocomposites through surface deposition ratio control, ACS Appl. Mater. Interfaces 10(7), 6552 (2018)

    Google Scholar 

  80. J. C. Wang, Y. T. Chan, W. F. Chen, M. C. Wu, and C. S. Lai, Interface modification of bernal- and rhombohedral-stacked trilayer-graphene/metal electrode on resistive switching of silver electrochemical metallization cells, ACS Appl. Mater. Interfaces 9(42), 37031 (2017)

    Google Scholar 

  81. X. Zhao, Z. Wang, Y. **e, H. Xu, J. Zhu, X. Zhang, W. Liu, G. Yang, J. Ma, and Y. Liu, Photocatalytic reduction of graphene oxide-TiO2 nanocomposites for improving resistive-switching memory behaviors, Small 14(29), 1801325 (2018)

    Google Scholar 

  82. R. B. Jacobs-Gedrim, M. T. Murphy, F. Yang, N. Jain, M. Shanmugam, E. S. Song, Y. Kandel, P. Hesamaddin, H. Y. Yu, M. P. Anantram, D. B. Janes, and B. Yu, Reversible phase-change behavior in two-dimensional antimony telluride (Sb2Te3) nanosheets, Appl. Phys. Lett. 112(13), 133101 (2018)

    ADS  Google Scholar 

  83. P. Saini, M. Singh, J. Thakur, R. Patil, Y. R. Ma, R. P. Tandon, S. P. Singh, and A. K. Mahapatro, Probing the mechanism for bipolar resistive switching in annealed graphene oxide thin films, ACS Appl. Mater. Interfaces 10(7), 6521 (2018)

    Google Scholar 

  84. X. Sun, Z. Lu, Z. Chen, Y. Wang, J. Shi, M. Washington, and T. M. Lu, Single-crystal graphene-directed van der waals epitaxial resistive switching, ACS Appl. Mater. Interfaces 10(7), 6730 (2018)

    Google Scholar 

  85. S. I. Oh, J. R. Rani, S. M. Hong, and J. H. Jang, Self-rectifying bipolar resistive switching memory based on an iron oxide and graphene oxide hybrid, Nanoscale 9(40), 15314 (2017)

    Google Scholar 

  86. Y. Li, S. Long, Q. Liu, H. Lv, and M. Liu, Resistive switching performance improvement via modulating nanoscale conductive filament, involving the application of two-dimensional layered materials, Small 13(35), 1604306 (2017)

    Google Scholar 

  87. X. Zhao, S. Liu, J. Niu, L. Liao, Q. Liu, X. **ao, H. Lv, S. Long, W. Banerjee, W. Li, S. Si, and M. Liu, Confining cation injection to enhance CBRAM performance by nanopore graphene layer, Small 13(35), 1603948 (2017)

    Google Scholar 

  88. R. Shi, X. Wang, Z. Wang, L. Cao, M. Song, X. Huang, J. Liu, and W. Huang, Fully solution-processed transparent nonvolatile and volatile multifunctional memory devices from conductive polymer and graphene oxide, Adv. Electron. Mater. 3(8), 1700135 (2017)

    Google Scholar 

  89. C. Baeumer, R. Valenta, C. Schmitz, A. Locatelli, T. O. Menteş, S. P. Rogers, A. Sala, N. Raab, S. Nemsak, M. Shim, C. M. Schneider, S. Menzel, R. Waser, and R. Dittmann, Subfilamentary networks cause cycle-to-cycle variability in memristive devices, ACS Nano 11(7), 6921 (2017)

    Google Scholar 

  90. C. Pan, E. Miranda, M. A. Villena, N. **ao, X. **g, X. **e, T. Wu, F. Hui, Y. Shi’ and M. Lanza, Model for multi-filamentary conduction in graphene/hexagonal-boron-nitride/graphene based resistive switching devices, 2D Mater. 4 (2), 025099 (2017)

    Google Scholar 

  91. G. Anoop, V. Panwar, T. Y. Kim, and J. Y. Jo, Resistive switching in ZnO nanorods/graphene oxide hybrid multilayer structures, Adv. Electron. Mater. 3(5), 1600418 (2017)

    Google Scholar 

  92. P. Zhang, C. Gao, B. Xu, L. Qi, C. Jiang, M. Gao, and D. Xue, Structural phase transition effect on resistive switching behavior of MoS2-polyvinylpyrrolidone nanocomposites films for flexible memory devices, Small 12(15), 2077 (2016)

    ADS  Google Scholar 

  93. V. K. Nagareddy, M. D. Barnes, F. Zipoli, K. T. Lai, A. M. Alexeev, M. F. Craciun, and C. D. Wright, Multilevel ultrafast flexible nanoscale nonvolatile hybrid graphene oxide-titanium oxide memories, ACS Nano 11(3), 3010 (2017)

    Google Scholar 

  94. F. Fan, B. Zhang, Y. Cao, and Y. Chen, Solution-processable poly(N-vinylcarbazole)-covalently grafted MoS2 nanosheets for nonvolatile rewritable memory devices, Nanoscale 9(7), 2449 (2017)

    Google Scholar 

  95. T. Li, P. Sharma, A. Lipatov, H. Lee, J. W. Lee, M. Y. Zhuravlev, T. R. Paudel, Y. A. Genenko, C. B. Eom, E. Y. Tsymbal, A. Sinitskii, and A. Gruverman, Polarization-mediated modulation of electronic and transport properties of hybrid MoS2-BaTiO3-SrRuO3 tunnel junctions, Nano Lett. 17(2), 922 (2017)

    ADS  Google Scholar 

  96. C. H. Bok, C. Wu, and T. W. Kim, Operating mechanisms of highly-reproducible write-once-read-many-times memory devices based on graphene quantum dot: poly(methyl silsesquioxane) nanocomposites, Appl. Phys. Lett. 110(1), 013301 (2017)

    ADS  Google Scholar 

  97. A. Rani, D. B. Velusamy, R. H. Kim, K. Chung, F. M. Mota, C. Park, and D. H. Kim, Non-volatile ReRAM devices based on self-assembled multilayers of modified graphene oxide 2D nanosheets, Small 12(44), 6167 (2016)

    Google Scholar 

  98. G. H. Shin, C.-K. Kim, G. S. Bang, J. Y. Kim, B. C. Jang, B. J. Koo, M. H. Woo, Y. K. Choi, and S. Y. Choi, Multilevel resistive switching nonvolatile memory based on MoS2 nanosheet-embedded graphene oxide, 2D Mater. 3(3), 034002 (2016)

    Google Scholar 

  99. K. Qian, R. Y. Tay, V. C. Nguyen, J. Wang, G. Cai, T. Chen, E. H. T. Teo, and P. S. Lee, Hexagonal boron nitride thin film for flexible resistive memory applications, Adv. Funct. Mater. 26(13), 2176 (2016)

    Google Scholar 

  100. C. Hao, F. Wen, J. **ang, S. Yuan, B. Yang, L. Li, W. Wang, Z. Zeng, L. Wang, Z. Liu, and Y. Tian, Liquid-exfoliated black phosphorous nanosheet thin films for flexible resistive random access memory applications, Adv. Funct. Mater. 26(12), 2016 (2016)

    Google Scholar 

  101. H. Tian, H. Zhao, X. F. Wang, Q. Y. **e, H. Y. Chen, M. A. Mohammad, C. Li, W. T. Mi, Z. Bie, C. H. Yeh, Y. Yang, H. S. P. Wong, P. W. Chiu, and T. L. Ren, In situ tuning of switching window in a gate-controlled bilayer graphene-electrode resistive memory device, Adv. Mater. 27(47), 7767 (2015)

    Google Scholar 

  102. G. Khurana, P. Misra, N. Kumar, and R. S. Katiyar, Tunable power switching in nonvolatile flexible memory devices based on graphene oxide embedded with ZnO nanorods, J. Phys. Chem. C 118(37), 21357 (2014)

    Google Scholar 

  103. Y. J. Huang and S. C. Lee, Graphene/h-BN heterostructures for vertical architecture of RRAM design, Sci. Rep. 7, 9679 (2017)

    ADS  Google Scholar 

  104. Y. T. Lee, J. Lee, H. Ju, J. A. Lim, Y. Yi, W. K. Choi, D. K. Hwang, and S. Im, Nonvolatile charge injection memory based on black phosphorous 2D nanosheets for charge trap** and active channel layers, Adv. Funct. Mater. 26(31), 5701 (2016)

    Google Scholar 

  105. C. Yeon, S. J. Yun, J. Yang, D. H. Youn, and J. W. Lim, Na-cation-assistedr exfoliation of MX2 (M = Mo, W; X = S, Se) nanosheets in an aqueous medium with the aid of a polymeric surfactant for flexible polymer-nanocomposite memory applications, Small 14(2), 1702747 (2018)

    Google Scholar 

  106. I. Valov and G. Staikov, Nucleation and growth phenomena in nanosized electrochemical systems for resistive switching memories, J. Solid State Electrochem. 17(2), 365 (2013)

    Google Scholar 

  107. A. Tsurumaki-Fukuchi, R. Nakagawa, M. Arita, and Y. Takahashi, Smooth interfacial scavenging for resistive switching oxide via the formation of highly uniform layers of amorphous TaOx, ACS Appl. Mater. Interfaces 10(6), 5609 (2018)

    Google Scholar 

  108. B. Li, Y. Liu, C. Wan, Z. Liu, M. Wang, D. Qi, J. Yu, P. Cai, M. **ao, Y. Zeng, and X. Chen, Mediating short-term plasticity in an artificial memristive synapse by the orientation of silica mesopores, Adv. Mater. 30(16), 1706395 (2018)

    Google Scholar 

  109. Q. Wu, H. Wang, Q. Luo, W. Banerjee, J. Cao, X. Zhang, F. Wu, Q. Liu, L. Li, and M. Liu, Full imitation of synaptic metaplasticity based on memristor devices, Nanoscale 10(13), 5875 (2018)

    Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (NSFC) (Nos. 51971070 and 10974037), National Key Research Program of China (No. 2016YFA0200403), Eu-FP7 Project (No. 247644), CAS Strategy Pilot Program (No. XDA 09020300). C. Wang acknowledges the support of the Fundamental Research Funds for the Central Universities (buctrc 202122). Y. **e acknowledges the support of Beihang Youth Talent Funding Plan (No. YWF-18-BJ-Y-196).

Author information

Author notes

  1. These authors contributed equally.

Authors and Affiliations

  1. MOE Key Laboratory of Weak-Light Nonlinear Photonics, Department of Physics, Nankai University, Tian**, 300071, China

    Zhican Zhou & Qian Liu

  2. CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, University of Chinese Academy of Sciences, Bei**g, 100190, China

    Zhican Zhou, Fengyou Yang, Shu Wang, Lei Wang, **aofeng Wang & Qian Liu

  3. College of Mathematics and Physics, Shandong Advanced Optoelectronic Materials and Technologies Engineering Laboratory, Qingdao University of Science and Technology, Qingdao, 266061, China

    Lei Wang

  4. College of Mathematics and Physics, Bei**g University of Chemical Technology, Bei**g, 100029, China

    Cong Wang

  5. School of Physics, Beihang University, Bei**g, 100191, China

    Yong **e

Authors
  1. Zhican Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fengyou Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. **aofeng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Cong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yong **e
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Qian Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Cong Wang, Yong **e or Qian Liu.

Additional information

This article can also be found at http://journal.hep.com.cn/fop/EN/10.1007/s11467-021-1114-5.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, Z., Yang, F., Wang, S. et al. Emerging of two-dimensional materials in novel memristor. Front. Phys. 17, 23204 (2022). https://doi.org/10.1007/s11467-021-1114-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11467-021-1114-5

Keywords

Search

Navigation