Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Imperfection-enabled memristive switching in van der Waals materials

Nature Electronics volume 6, pages 491–505 (2023)Cite this article

Subjects

Abstract

Memristive devices can offer dynamic behaviour, analogue programmability, and scaling and integration capabilities. As a result, they are of potential use in the development of information processing and storage devices for both conventional and unconventional computing paradigms. Their memristive switching processes originate mainly from the modulation of the number and position of structural defects or compositional impurities—what are commonly referred to as imperfections. While the underlying mechanisms and potential applications of memristors based on traditional bulk materials have been extensively studied, memristors based on van der Waals materials have only been considered more recently. Here we examine imperfection-enabled memristive switching in van der Waals materials. We explore how imperfections—together with the inherent physicochemical properties of the van der Waals materials—create different switching mechanisms, and thus provide a range of opportunities to engineer switching behaviour in memristive devices. We also discuss the challenges involved in terms of material selection, mechanism investigation and switching uniformity control, and consider the potential of van der Waals memristors in system-level implementations of efficient computing technologies.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Various imperfections in vdW materials.
Fig. 2: Imperfection-enabled switching mechanisms in vdW memristors.
Fig. 3: Imperfection-related kinetics of the resistive switching processes.
Fig. 4: The development and benchmarks of vdW memristors for various applications.
Fig. 5: Selected special characteristics of vdW memristors.
Fig. 6: Imperfection engineering to improve the performance of vdW memristors.

Similar content being viewed by others

References

  1. Lanza, M. et al. Memristive technologies for data storage, computation, encryption, and radio-frequency communication. Science 376, 1066 (2022).

    Google Scholar 

  2. Zhou, F. et al. Optoelectronic resistive random access memory for neuromorphic vision sensors. Nat. Nanotechnol. 14, 776–782 (2019).

    Google Scholar 

  3. Rao, M. et al. Thousands of conductance levels in memristors integrated on CMOS. Nature 615, 823–829 (2023).

    Google Scholar 

  4. Yang, J. J. et al. Memristive switching mechanism for metal/oxide/metal nanodevices. Nat. Nanotechnol. 3, 429–433 (2008).

    Google Scholar 

  5. Li, C. et al. Direct observations of nanofilament evolution in switching processes in HfO2-based resistive random access memory by in situ TEM studies. Adv. Mater. 29, 1602976 (2017).

    Google Scholar 

  6. Yuan, F. et al. Real-time observation of the electrode-size-dependent evolution dynamics of the conducting filaments in a SiO2 layer. ACS Nano 11, 4097–4104 (2017).

    Google Scholar 

  7. Yang, J. J., Strukov, D. B. & Stewart, D. R. Memristive devices for computing. Nat. Nanotechnol. 8, 13–24 (2013).

    Google Scholar 

  8. Chen, Y.-S. et al. An ultrathin forming-free HfOx resistance memory with excellent electrical performance. IEEE Electron Device Lett. 31, 1473–1475 (2010).

    Google Scholar 

  9. Panja, R., Roy, S., Jana, D. & Maikap, S. Impact of device size and thickness of Al2O3 film on the Cu pillar and resistive switching characteristics for 3D cross-point memory application. Nanoscale Res. Lett. 9, 692 (2014).

    Google Scholar 

  10. Chen, A. Area and thickness scaling of forming voltage of resistive switching memories. IEEE Electron Device Lett. 35, 57–59 (2014).

    Google Scholar 

  11. Liu, S. et al. Eliminating negative-SET behavior by suppressing nanofilament overgrowth in cation-based memory. Adv. Mater. 28, 10623–10629 (2016).

    Google Scholar 

  12. Zhao, H. et al. Atomically thin femtojoule memristive device. Adv. Mater. 29, 1703232 (2017). This paper exploited the atomic level uniformity of vdW materials and demonstrated a memristive device with sub-nanometre medium thickness and low power consumption.

    Google Scholar 

  13. Shi, Y. et al. Electronic synapses made of layered two-dimensional materials. Nat. Electron. 1, 458–465 (2018).

    Google Scholar 

  14. Chen, S. et al. Wafer-scale integration of two-dimensional materials in high-density memristive crossbar arrays for artificial neural networks. Nat. Electron. 3, 638–645 (2020).

    Google Scholar 

  15. Wang, X. et al. Grain-boundary engineering of monolayer MoS2 for energy-efficient lateral synaptic devices. Adv. Mater. 33, 2102435 (2021).

    Google Scholar 

  16. Sangwan, V. K. et al. Gate-tunable memristive phenomena mediated by grain boundaries in single-layer MoS2. Nat. Nanotechnol. 10, 403–406 (2015).

    Google Scholar 

  17. Liu, X. W. et al. Temperature-sensitive spatial distribution of defects in PdSe2 flakes. Phys. Rev. Mater. 5, L041001 (2021).

    Google Scholar 

  18. Lin, Y. C., Dumcenco, D. O., Huang, Y. S. & Suenaga, K. Atomic mechanism of the semiconducting-to-metallic phase transition in single-layered MoS2. Nat. Nanotechnol. 9, 391–396 (2014).

    Google Scholar 

  19. Hus, S. M. et al. Observation of single-defect memristor in an MoS2 atomic sheet. Nat. Nanotechnol. 16, 58–62 (2021). This work revealed the switching process in a single-vacancy monolayer MoS2 memristor and its potential in realizing the smallest-footprint devices.

    Google Scholar 

  20. Sangwan, V. K. et al. Multi-terminal memtransistors from polycrystalline monolayer molybdenum disulfide. Nature 554, 500–504 (2018). This study demonstrated the gate-tunable heterosynaptic functionality in lateral MoS2 memristors.

    Google Scholar 

  21. Azizi, A. et al. Dislocation motion and grain boundary migration in two-dimensional tungsten disulphide. Nat. Commun. 5, 4867 (2014).

    Google Scholar 

  22. Zhu, X., Li, D., Liang, X. & Lu, W. D. Ionic modulation and ionic coupling effects in MoS2 devices for neuromorphic computing. Nat. Mater. 18, 141–148 (2019). This paper reported a phase-transition-enabled memristor based on field-driven ionic modulation.

    Google Scholar 

  23. Fang, Z. et al. Temperature instability of resistive switching on HfOx-based RRAM devices. IEEE Electron Device Lett. 31, 476–478 (2010).

    Google Scholar 

  24. Wang, M. et al. Robust memristors based on layered two-dimensional materials. Nat. Electron. 1, 130–136 (2018). This study reported a robust vdW memristive device with a high operating temperature enabled by the oxidisation of MoS2 flakes.

    Google Scholar 

  25. He, Y. et al. Engineering grain boundaries at the 2D limit for the hydrogen evolution reaction. Nat. Commun. 11, 57 (2020).

    Google Scholar 

  26. Zhou, W. et al. Intrinsic structural defects in monolayer molybdenum disulfide. Nano Lett. 13, 2615–2622 (2013).

    Google Scholar 

  27. Zou, X. & Yakobson, B. Defects in Two-Dimensional Materials. In Avouris, P., Heinz, T. & Low, T. (Eds.), 2D Materials: Properties and Devices (pp. 359-378) (2017) Cambridge: Cambridge University Press

  28. Ma, J., Alfè, D., Michaelides, A. & Wang, E. Stone–Wales defects in graphene and other planar sp2-bonded materials. Phys. Rev. B 80, 033407 (2009).

    Google Scholar 

  29. van der Zande, A. M. et al. Grains and grain boundaries in highly crystalline monolayer molybdenum disulphide. Nat. Mater. 12, 554–561 (2013).

    Google Scholar 

  30. Lahiri, J., Lin, Y., Bozkurt, P., Oleynik, I. I. & Batzill, M. An extended defect in graphene as a metallic wire. Nat. Nanotechnol. 5, 326–329 (2010).

    Google Scholar 

  31. Li, Y., Yan, H., Xu, B., Zhen, L. & Xu, C. Y. Electrochemical intercalation in atomically thin van der Waals materials for structural phase transition and device applications. Adv. Mater. 33, 2000581 (2021).

    Google Scholar 

  32. Su, C. et al. Engineering single-atom dynamics with electron irradiation. Sci. Adv. 5, eaav2252 (2019).

    Google Scholar 

  33. Tosun, M. et al. Air-stable n-doping of WSe2 by anion vacancy formation with mild plasma treatment. ACS Nano 10, 6853–6860 (2016).

    Google Scholar 

  34. Li, J. The mechanics and physics of defect nucleation. MRS Bull. 32, 151–159 (2011).

    Google Scholar 

  35. Li, W., Qian, X. & Li, J. Phase transitions in 2D materials. Nat. Rev. Mater. 6, 829–846 (2021).

    Google Scholar 

  36. Duerloo, K.-A. & Reed, E. J. Structural phase transitions by design in monolayer alloys. ACS Nano 10, 289–297 (2016).

    Google Scholar 

  37. Bessonov, A. A. et al. Layered memristive and memcapacitive switches for printable electronics. Nat. Mater. 14, 199–204 (2015).

    Google Scholar 

  38. Pam, M. E. et al. Interface-modulated resistive switching in Mo-irradiated ReS2 for neuromorphic computing. Adv. Mater. 34, 2202722 (2022).

    Google Scholar 

  39. Gong, Y. et al. Spatially controlled doping of two-dimensional SnS2 through intercalation for electronics. Nat. Nanotechnol. 13, 294–299 (2018).

    Google Scholar 

  40. Li, M. et al. High mobilities in layered InSe transistors with indium-encapsulation-induced surface charge doping. Adv. Mater. 30, 1803690 (2018).

    Google Scholar 

  41. Shen, Y. et al. Variability and yield in h-BN-based memristive circuits: the role of each type of defect. Adv. Mater. 33, 2103656 (2021).

    Google Scholar 

  42. Garaj, S. et al. Graphene as a subnanometre trans-electrode membrane. Nature 467, 190–193 (2010).

    Google Scholar 

  43. Lee, J., Du, C., Sun, K., Kioupakis, E. & Lu, W. D. Tuning ionic transport in memristive devices by graphene with engineered nanopores. ACS Nano 10, 3571–3579 (2016).

    Google Scholar 

  44. Ge, R. et al. Atomristor: nonvolatile resistance switching in atomic sheets of transition metal dichalcogenides. Nano Lett. 18, 434–441 (2018).

    Google Scholar 

  45. Sun, L. et al. Self-selective van der Waals heterostructures for large scale memory array. Nat. Commun. 10, 3161 (2019).

    Google Scholar 

  46. Wu, X. et al. Thinnest nonvolatile memory based on monolayer h-BN. Adv. Mater. 31, 1806790 (2019).

    Google Scholar 

  47. Ge, R. et al. A library of atomically thin 2D materials featuring the conductive-point resistive switching phenomenon. Adv. Mater. 33, 2007792 (2020).

    Google Scholar 

  48. Li, Y. S. et al. Anomalous resistive switching in memristors based on two-dimensional palladium diselenide using heterophase grain boundaries. Nat. Electron. 4, 348–356 (2021).

    Google Scholar 

  49. Zhang, D., Yeh, C.-H., Cao, W. & Banerjee, K. 0.5T0.5R—an ultracompact RRAM cell uniquely enabled by van der Waals heterostructures. IEEE Trans. Electron Devices 68, 2033–2040 (2021).

    Google Scholar 

  50. Zhao, X. et al. Confining cation injection to enhance CBRAM performance by nanopore graphene layer. Small 13, 1603948 (2017). This work employed nanoporous graphene to regulate the morphology and spatial distribution of conductive channels in metal-oxide memristors.

    Google Scholar 

  51. Yan, Y., Sun, B. & Ma, D. Resistive switching memory characteristics of single MoSe2 nanorods. Chem. Phys. Lett. 638, 103–107 (2015).

    Google Scholar 

  52. Pan, C. et al. Coexistence of grain-boundaries-assisted bipolar and threshold resistive switching in multilayer hexagonal boron nitride. Adv. Funct. Mater. 27, 1604811 (2017).

    Google Scholar 

  53. Xu, R. et al. Vertical MoS2 double-layer memristor with electrochemical metallization as an atomic-scale synapse with switching thresholds approaching 100 mV. Nano Lett. 19, 2411–2417 (2019).

    Google Scholar 

  54. Frey, N. C., Akinwande, D., Jariwala, D. & Shenoy, V. B. Machine learning-enabled design of point defects in 2D materials for quantum and neuromorphic information processing. ACS Nano 14, 13406–13417 (2020).

    Google Scholar 

  55. Son, D. et al. Colloidal synthesis of uniform-sized molybdenum disulfide nanosheets for wafer-scale flexible nonvolatile memory. Adv. Mater. 28, 9326–9332 (2016).

    Google Scholar 

  56. Yan, X. et al. Vacancy-induced synaptic behavior in 2D WS2 nanosheet-based memristor for low-power neuromorphic computing. Small 15, 1901423 (2019).

    Google Scholar 

  57. Feng, X. et al. Self-selective multi-terminal memtransistor crossbar array for in-memory computing. ACS Nano 15, 1764–1774 (2021).

    Google Scholar 

  58. Song, D.-X., Ma, W.-G. & Zhang, X. Correlated migration of ions in a 2D heterostructure anode: guaranteeing a low barrier for a high site occupancy. J. Mater. Chem. A 8, 17463–17470 (2020).

    Google Scholar 

  59. Wang, L. et al. Artificial synapses based on multiterminal memtransistors for neuromorphic application. Adv. Funct. Mater. 29, 1901106 (2019).

    Google Scholar 

  60. Wang, Y. et al. High on/off ratio black phosphorus based memristor with ultra-thin phosphorus oxide layer. Appl. Phys. Lett. 115, 193503 (2019).

    Google Scholar 

  61. Liu, L. et al. Low-power memristive logic device enabled by controllable oxidation of 2D HfSe2 for in-memory computing. Adv. Sci. 8, 2005038 (2021).

    Google Scholar 

  62. Huh, W. et al. Synaptic barristor based on phase-engineered 2D heterostructures. Adv. Mater. 30, 1801447 (2018).

    Google Scholar 

  63. Yamamoto, M. et al. Self-limiting layer-by-layer oxidation of atomically thin WSe2. Nano Lett. 15, 2067–2073 (2015).

    Google Scholar 

  64. Liu, Y. et al. Thermal oxidation of WSe2 nanosheets adhered on SiO2/Si substrates. Nano Lett. 15, 4979–4984 (2015).

    Google Scholar 

  65. Yang, F. S. et al. Oxidation-boosted charge trapping in ultra-sensitive van der Waals materials for artificial synaptic features. Nat. Commun. 11, 2972 (2020).

    Google Scholar 

  66. Mleczko, M. J. et al. HfSe2 and ZrSe2: two-dimensional semiconductors with native high-kappa oxides. Sci. Adv. 3, 1700481 (2017).

    Google Scholar 

  67. Duerloo, K. A., Li, Y. & Reed, E. J. Structural phase transitions in two-dimensional Mo- and W-dichalcogenide monolayers. Nat. Commun. 5, 4214 (2014).

    Google Scholar 

  68. Yang, H., Kim, S. W., Chhowalla, M. & Lee, Y. H. Structural and quantum-state phase transitions in van der Waals layered materials. Nat. Phys. 13, 931–937 (2017). This paper critically examined the phase transition physics in vdW materials and highlighted the perspective applications of vdW electronics.

    Google Scholar 

  69. Wang, Y. et al. Structural phase transition in monolayer MoTe2 driven by electrostatic doping. Nature 550, 487–491 (2017).

    Google Scholar 

  70. Rao, F. et al. Reducing the stochasticity of crystal nucleation to enable subnanosecond memory writing. Science 358, 1423–1427 (2017).

    Google Scholar 

  71. Zhang, F. et al. An ultra-fast multi-level MoTe2-based RRAM. In 2018 IEEE International Electron Devices Meeting (IEDM) 22.7.1–22.7.4 (IEEE, 2019).

  72. Zhang, F. et al. Electric-field induced structural transition in vertical MoTe2- and Mo1−xWTe2-based resistive memories. Nat. Mater. 18, 55–61 (2019).

    Google Scholar 

  73. Cheng, P., Sun, K. & Hu, Y. H. Memristive behavior and ideal memristor of 1T phase MoS2 nanosheets. Nano Lett. 16, 572–576 (2016).

    Google Scholar 

  74. Jin, Q., Liu, N., Chen, B. & Mei, D. Mechanisms of semiconducting 2H to metallic 1T phase transition in two-dimensional MoS2 nanosheets. J. Phys. Chem. C 122, 28215–28224 (2018).

    Google Scholar 

  75. Han, S. T. et al. Black phosphorus quantum dots with tunable memory properties and multilevel resistive switching characteristics. Adv. Sci. 4, 1600435 (2017).

    Google Scholar 

  76. Yao, J. et al. Resistive switching in nanogap systems on SiO2 substrates. Small 5, 2910–2915 (2009).

    Google Scholar 

  77. Hong, S. K., Kim, J. E., Kim, S. O., Choi, S.-Y. & Cho, B. J. Flexible resistive switching memory device based on graphene oxide. IEEE Electron Device Lett. 31, 1005–1007 (2010).

    Google Scholar 

  78. Wang, Z. et al. Resistive switching materials for information processing. Nat. Rev. Mater. 5, 173–195 (2020).

    Google Scholar 

  79. Jo, S. H. et al. Nanoscale memristor device as synapse in neuromorphic systems. Nano Lett. 10, 1297–1301 (2010).

    Google Scholar 

  80. Ma, C. et al. Intelligent infrared sensing enabled by tunable moiré quantum geometry. Nature 604, 266–272 (2022).

    Google Scholar 

  81. Feng, X. et al. A fully printed flexible MoS2 memristive artificial synapse with femtojoule switching energy. Adv. Electron. Mater. 5, 1900740 (2019).

    Google Scholar 

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

    Google Scholar 

  83. Li, X. et al. Power-efficient neural network with artificial dendrites. Nat. Nanotechnol. 15, 776–782 (2020).

    Google Scholar 

  84. Kalita, H. et al. Artificial neuron using vertical MoS2/graphene threshold switching memristors. Sci. Rep. 9, 53 (2019).

    Google Scholar 

  85. Liu, H. et al. A tantalum disulfide charge-density-wave stochastic artificial neuron for emulating neural statistical properties. Nano Lett. 21, 3465–3472 (2021).

    Google Scholar 

  86. Pi, S., Ghadiri-Sadrabadi, M., Bardin, J. C. & Xia, Q. F. Nanoscale memristive radiofrequency switches. Nat. Commun. 6, 7519 (2015).

    Google Scholar 

  87. Kim, M. et al. Analogue switches made from boron nitride monolayers for application in 5G and terahertz communication systems. Nat. Electron. 3, 479–485 (2020). This study reported the monolayer h-BN memristor and its application in radiofrequency switches.

    Google Scholar 

  88. Kim, M. et al. Monolayer molybdenum disulfide switches for 6G communication systems. Nat. Electron. 5, 367–373 (2022).

    Google Scholar 

  89. Lanza, M., Smets, Q., Huyghebaert, C. & Li, L.-J. Yield, variability, reliability, and stability of two-dimensional materials based solid-state electronic devices. Nat. Commun. 11, 5689 (2020).

    Google Scholar 

  90. Choi, S. et al. SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations. Nat. Mater. 17, 335–340 (2018). This work demonstrated SiGe epitaxial memristors with engineered grain boundary distribution and provided inspiration for variation control of vdW memristors.

    Google Scholar 

  91. Chen, T. A. et al. Wafer-scale single-crystal hexagonal boron nitride monolayers on Cu(111). Nature 579, 219–223 (2020).

    Google Scholar 

  92. Wang, Z. R. et al. Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing. Nat. Mater. 16, 101–108 (2017).

    Google Scholar 

  93. Sun, L., Banhart, F. & Warner, J. Two-dimensional materials under electron irradiation. MRS Bull. 40, 29–37 (2015).

    Google Scholar 

  94. Rollings, R. C., Kuan, A. T. & Golovchenko, J. A. Ion selectivity of graphene nanopores. Nat. Commun. 7, 11408 (2016).

    Google Scholar 

  95. Zhao, X. et al. Breaking the current-retention dilemma in cation-based resistive switching devices utilizing graphene with controlled defects. Adv. Mater. 30, 1705193 (2018).

    Google Scholar 

  96. Ambrogio, S. et al. Equivalent-accuracy accelerated neural-network training using analogue memory. Nature 558, 60–67 (2018).

    Google Scholar 

  97. Hinton, H. et al. A 200 × 256 image sensor heterogeneously integrating a 2D nanomaterial-based photo-FET array and CMOS time-to-digital converters. In 2022 IEEE International Solid-State Circuits Conference (ISSCC) 12.2.1–12.2.3 (IEEE, 2022). This paper provided the fabrication contexts of vdW device and CMOS integrated circuits.

  98. Zhu, K. et al. Hybrid 2D/CMOS microchips for memristive applications. Nature 618, 57–62 (2023).

  99. Zhao, Y. et al. Large-area transfer of two-dimensional materials free of cracks, contamination and wrinkles via controllable conformal contact. Nat. Commun. 13, 4409 (2022).

    Google Scholar 

  100. Pi, S. et al. Memristor crossbar arrays with 6-nm half-pitch and 2-nm critical dimension. Nat. Nanotechnol. 14, 35–39 (2019).

    Google Scholar 

  101. Jiang, J., Parto, K., Cao, W. & Banerjee, K. Ultimate monolithic-3D integration with 2D materials: rationale, prospects, and challenges. IEEE J. Electron Devices Soc. 7, 878–887 (2019).

    Google Scholar 

  102. Luo, Q. et al. A highly CMOS compatible hafnia-based ferroelectric diode. Nat. Commun. 11, 1391 (2020).

    Google Scholar 

  103. IEEE International Roadmap for Devices and Systems (IRDS™) 2022 Edition https://irds.ieee.org/editions/2022 (2022).

Download references

Acknowledgements

We thank M.-Y. Tsai for constructive suggestions on the figure optimization. M.L. and Y.-F.L. acknowledge support from the Taiwan Ministry of Science and Technology (grants MOST 109-2112-M-005-013-MY3 and 110-2881-M-005-512-MY2). H.L. and H.W. acknowledge the support of the Army Research Office (grant W911NF1810268) and National Science Foundation (grants 2036359 and 1653870). This work was partially supported by the Air Force Office of Scientific Research (AFOSR) through the Multidisciplinary University Research Initiative (MURI) programme under contract FA9550-19-1-0213 and the United States Air Force Research Laboratory (AFRL) under grants FA8750-18-2-0122 and FA8650-21-C-5405. This work was also partially supported by the National Science Foundation under contract 2023752. The opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of AFRL.

Author information

Author notes

  1. These authors contributed equally: Mengjiao Li, Hefei Liu, Ruoyu Zhao.

Authors and Affiliations

  1. Electrical and Computer Engineering Department, University of Southern California, Los Angeles, CA, USA

    Mengjiao Li, Hefei Liu, Ruoyu Zhao, Mingrui Chen, Ye Zhuo, Chongwu Zhou, Han Wang & J. Joshua Yang

  2. Department of Physics, National Chung Hsing University, Taichung, Taiwan

    Mengjiao Li, Feng-Shou Yang & Yen-Fu Lin

  3. Department of Material Science and Engineering, Institutes of Nanoscience, i-Center for Advanced Science and Technology (i-CAST), National Chung Hsing University, Taichung, Taiwan

    Yen-Fu Lin

Authors
  1. Mengjiao Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hefei Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ruoyu Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Feng-Shou Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mingrui Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ye Zhuo
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Chongwu Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Han Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yen-Fu Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. J. Joshua Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.J.Y., Y.-F.L. and H.W. conceived the concepts and perspectives. M.L., H.L. and R.Z. worked on literature analysis and data collection. M.L., H.L. and J.J.Y. co-wrote the manuscript. All authors contributed to the discussion of content and reviewed and edited the manuscript. J.J.Y. supervised the project at all stages.

Corresponding authors

Correspondence to Chongwu Zhou, Han Wang, Yen-Fu Lin or J. Joshua Yang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Electronics thanks Jun Lou, Kah-Wee Ang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–3 and Tables 1–4.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, M., Liu, H., Zhao, R. et al. Imperfection-enabled memristive switching in van der Waals materials. Nat Electron 6, 491–505 (2023). https://doi.org/10.1038/s41928-023-00984-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41928-023-00984-2

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing