Skip to main content
Log in

Voltage-controlled reverse filament growth boosts resistive switching memory

  • Research Article
  • Published:
Nano Research Aims and scope Submit manuscript

Abstract

Nonvolatile memory devices based on filamentary resistance switching (RS) areamong the frontrunners to fuel future devices and sensors of the internet of things (IoT) era. The capability of many metal-insulator-metal cells to switch between two distinctive resistive states in response to an external electrical stimulus has been demonstrated. Through years of selection, cells based on the drift of metal ions, namely conductive-bridge memory devices, have shown a wide range of applications with nanosecond switching speeds, nanometer scalability, high-density, and low power-consumption. However, for low (sub-10-μA) current operation, a critical challenge is still represented by programming variability and by the stability of the conductive filament over time. Here, by introducing the concept of reverse filament growth (RFG), we managed to control the structural reconfiguration of the conductive filament inside a memory cell with significant enhancements of each of the aforementioned properties. A first-in-class Cu-based switching device is demonstrated, with a dedicated stack that enabled us to systematically trigger RFG, thus tuning the device’s properties. Along with nanosecond switching speeds, we achieved an endurance of up to 106 cycles with a 102 read window, with outstanding disturb immunity and optimal stability of the filament over time. Furthermore, by tuning the filament’s shape, an excellent control of multi-level bit operations was achieved. Thus, this device offers high flexibility in memory applications.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Yang, J. J.; Strukov, D. B.; Stewart, D. R. Memristive devices for computing. Nat. Nanotechnol. 2013, 8, 13–24.

    Article  Google Scholar 

  2. Waser, R.; Aono, M. Nanoionics-based resistive switching memories. Nat. Mater. 2007, 6, 833–840.

    Article  Google Scholar 

  3. Lu, W. Memristors: Going active. Nat. Mater. 2013, 12, 93–94.

    Article  Google Scholar 

  4. Zahurak, J.; Miyata, K.; Fischer, M.; Balakrishnan, M.; Chhajed, S.; Wells, D.; Li, H.; Torsi, A.; Lim, J.; Korber, M. et al. Process integration of a 27 nm, 16Gb Cu ReRAM. In Proceedings of 2014 IEEE International Electron Devices Meeting, San Francisco, CA, USA, 2014, pp 6.2.1–6.2.4.

    Chapter  Google Scholar 

  5. Goux, L.; Sankaran, K.; Kar, G.; Jossart, N.; Opsomer, K.; Degraeve, R.; Rignanese, G. M.; Detavernier, C.; Clima, S.; Chen, Y. Y. et al. Field-driven ultrafast sub-ns programming in W/Al2O3/Ti/CuTe-based 1T1R CBRAM system. In Symposium on VLSI Technology (VLSIT), Honolulu, HI, USA, 2012, pp 69–70.

    Chapter  Google Scholar 

  6. Goux, L.; Valov, I. Electrochemical processes and device improvement in conductive bridge RAM cells. Phys. Status Solidi Appl. Mater. Sci. 2016, 213, 274–288.

    Article  Google Scholar 

  7. Celano, U.; Goux, L.; Belmonte, A.; Opsomer, K.; Franquet, A.; Schulze, A.; Detavernier, C.; Richard, O.; Bender, H.; Jurczak, M. et al. Three-dimensional observation of the conductive filament in nanoscaled resistive memory devices. Nano Lett. 2014, 14, 2401–2406.

    Article  Google Scholar 

  8. Wang, H.; Meng, F. B.; Cai, Y. R.; Zheng, L. Y.; Li, Y. G.; Liu, Y. J.; Jiang, Y. Y.; Wang, X. T.; Chen, X. D. Sericin for resistance switching device with multilevel nonvolatile memory. Adv. Mater. 2013, 25, 5498–5503.

    Article  Google Scholar 

  9. Yang, Y. C.; Gao, P.; Li, L. Z.; Pan, X. Q.; Tappertzhofen, S.; Choi, S.; Waser, R.; Valov, I.; Lu, W. D. Electrochemical dynamics of nanoscale metallic inclusions in dielectrics. Nat. Commun. 2014, 5, 4232.

    Article  Google Scholar 

  10. Valov, I.; Kozicki, M. N. Cation-based resistance change memory. J. Phys. D: Appl. Phys. 2013, 46, 074005.

    Article  Google Scholar 

  11. Onofrio, N.; Guzman, D.; Strachan, A. Atomic origin of ultrafast resistance switching in nanoscale electrometallization cells. Nat. Mater. 2015, 14, 440–446.

    Article  Google Scholar 

  12. Woo, J.; Hwang, H. Communication—Impact of filament instability in an Ag2S-based conductive-bridge RAM for cross-point selector applications. ECS J. Solid State Sci. Technol. 2016, 5, Q98–Q100.

    Article  Google Scholar 

  13. Chen, W.; Barnaby, H. J.; Kozicki, M. N. Volatile and non-volatile switching in Cu-SiO2 programmable metallization cells. IEEE Electron Device Lett. 2016, 37, 580–583.

    Article  Google Scholar 

  14. Yang, Y. C.; Lu, W. Nanoscale resistive switching devices: Mechanisms and modeling. Nanoscale 2013, 5, 10076–10092.

    Article  Google Scholar 

  15. van Wees, B. J.; van Houten, H.; Beenakker, C. W. J.; Williamson, J. G.; Kouwenhoven, L. P.; van der Marel, D.; Foxon, C. T. Quantized conductance of point contacts in a two-dimensional electron gas. Phys. Rev. Lett. 1988, 60, 848–850.

    Article  Google Scholar 

  16. Celano, U.; Goux, L.; Belmonte, A.; Opsomer, K.; Degraeve, R.; Detavernier, C.; Jurczak, M.; Vandervorst, W. Under-standing the dual nature of the filament dissolution in conductive bridging devices. J. Phys. Chem. Lett. 2015, 6, 1919–1924.

    Article  Google Scholar 

  17. Liu, S.; Lu, N. D.; Zhao, X. L.; Xu, H.; Banerjee, W.; Lv, H. B.; Long, S. B.; Li, Q. J.; Liu, Q, Liu, M. Memory devices: Eliminating negative-SET behavior by suppressing nanofilament overgrowth in cation-based memory (Adv. Mater. 48/2016). Adv. Mater. 2016, 28, 10809.

    Article  Google Scholar 

  18. Celano, U.; Goux, L.; Degraeve, R.; Fantini, A.; Richard, O.; Bender, H.; Jurczak, M.; Vandervorst, W. Imaging the three-dimensional conductive channel in filamentary-based oxide resistive switching memory. Nano Lett. 2015, 15, 7970–7975.

    Article  Google Scholar 

  19. Belmonte, A.; Degraeve, R.; Fantini, A.; Kim, W.; Houssa, M.; Jurczak, M.; Goux, L. Origin of the current discretization in deep reset states of an Al2O3/Cu-based conductive-bridging memory, and impact on state level and variability. Appl. Phys. Lett. 2014, 104, 233508.

    Article  Google Scholar 

  20. Woo, J.; Belmonte, A.; Redolfi, A.; Hwang, H.; Jurczak, M.; Goux, L. Introduction of WO3 layer in a Cu-based Al2O3 conductive bridge RAM system for robust cycling and large memory window. IEEE J. Electron Devices Soc. 2016, 4, 163–166.

    Article  Google Scholar 

  21. Kozicki, M. N.; Gopalan, C.; Balakrishnan, M.; Mitkova, M. A low-power nonvolatile switching element based on copper-tungsten oxide solid electrolyte. IEEE Trans. Nanotechnol. 2006, 5, 535–544.

    Article  Google Scholar 

  22. Gopalan, C.; Kozicki, M. N.; Bhagat, S.; Puthen Thermadam, S. C.; Alford, T. L.; Mitkova, M. Structure of copper-doped tungsten oxide films for solid-state memory. J. Non-Cryst. Solids 2007, 353, 1844–1848.

    Article  Google Scholar 

  23. Belmonte, A.; Celano, U.; Redolfi, A.; Fantini, A.; Muller, R.; Vandervorst, W.; Houssa, M.; Jurczak, M.; Goux, L. Analysis of the excellent memory disturb characteristics of a hourglass- shaped filament in Al2O3/Cu-based CDRAM devices. IEEE Trans. Electron Devices 2015, 62, 2007–2013.

    Article  Google Scholar 

  24. Menzel, S.; Böttger, U.; Wimmer, M.; Salinga, M. Physics of the switching kinetics in resistive memories. Adv. Funct. Mater. 2015, 25, 6306–6325.

    Article  Google Scholar 

  25. Wang, Z. R.; Joshi, S.; Savel’ev, S. E.; Jiang, H.; Midya, R.; Lin, P.; Hu, M.; Ge, N.; Strachan, J. P.; Li, Z. Y. et al. Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing. Nat. Mater. 2016, 16, 101–108.

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge the partial funding by IMEC’s Industrial Affiliation programs.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Attilio Belmonte or Umberto Celano.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Belmonte, A., Celano, U., Chen, Z. et al. Voltage-controlled reverse filament growth boosts resistive switching memory. Nano Res. 11, 4017–4025 (2018). https://doi.org/10.1007/s12274-018-1983-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12274-018-1983-2

Keywords

Navigation