Abstract
Resistive random-access memories made from memristor crossbar arrays could provide the next generation of non-volatile memories. However, integrating large memristor crossbar arrays is challenging due to the high power consumption that originates from leakage currents (known as the sneak-path problem) and the large device-to-device and cycle-to-cycle variations of memristors. Here we report a memory cell comprised of two serially connected memristors and a minimum-sized transistor. With this approach, we use the ratio of the resistances of the memristors to encode information, rather than the absolute resistance of a single memristor, as is traditionally used in resistive-based memories. The minimum-sized transistor, which is connected to the midpoint between the two series-connected memristors, is used to sense the voltage to read the state of the cell and to assist with write operations. Our memory cell design solves the sneak-path problem and, compared to the traditional resistance-based current sensing approach for memory reads, our ratio-based voltage sensing scheme is more robust and less prone to data errors caused by variations in memristors.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Waser, R. & Aono, M. Nanoionics-based resistive switching memories. Nat. Mater. 6, 833–840 (2007).
Chua, L. O. Memristor–the missing circuit element. IEEE Trans. Circuit Theory 18, 507–519 (1971).
Jeong, D. S., Choi, B. J. & Hwang, C. S. in Resistive Switching: From Fundamentals of Nanoionic Redox Processes to Memristive Device Applications (eds Ielmini, D. & Waser, R.) 289–316 (Wiley-VCH, Weinheim, 2016).
Burr, G. W., Shenoy, R. S. & Hwang, H. in Resistive Switching: From Fundamentals of Nanoionic Redox Processes to Memristive Device Applications (eds Ielmini, D. & Waser, R.) 623–660 (Wiley-VCH, Weinheim, 2016).
Zidan, M. A., Fahmy, H. A. H., Hussain, M. M. & Salama, K. N. Memristor-based memory: The sneak paths problem and solutions. Microelectron. J. 44, 176–183 (2013).
Lv, H. et al. Evolution of conductive filament and its impact on reliability issues in oxide-electrolyte based resistive random access memory. Sci. Rep. 5, 7764 (2015).
Li, C. et al. Analogue signal and image processing with large memristor crossbars. Nat. Electron. 1, 52–59 (2018).
Jo, S. H., Kumar, T., Narayanan, S., Lu, W. D. & Nazarian, H. 3D-stackable crossbar resistive memory based on field-assisted superlinear threshold (FAST) selector. 2014 IEEE Int. Electron Devices Meet. (IEDM) https://doi.org/10.1109/IEDM.2014.7046999 (2014).
Gopalakrishnan, K. et al. Highly-scalable novel access device based on mixed ionic electronic conduction (MIEC) materials for high density phase change memory (PCM) arrays. 2010 Symp. VLSI Tech. (VLSIT) https://doi.org/10.1109/VLSIT.2010.5556229 (2010).
Linn, E., Rosezin, R., Kügeler, C. & Waser, R. Complementary resistive switches for passive nanocrossbar memories. Nat. Mater. 9, 403–406 (2010).
Alibart, F., Gao, L., Hoskins, B. D. & Strukov, D. B. High precision tuning of state for memristive devices by adaptable variation-tolerant algorithm. Nanotechnology 23, 075201 (2012).
Choi, S., Sheridan, P. & Lu, W. D. Data clustering using memristor networks. Sci. Rep. 5, 10492 (2015).
Chen, B. et al. Physical mechanisms of endurance degradation in TMO-RRAM. 2011 IEEE Int. Electron Devices Meet. (IEDM) https://doi.org/10.1109/IEDM.2011.6131539 (2011).
Baeumer, C. et al. Subfilamentary networks cause cycle-to-cycle variability in memristive devices. ACS Nano 11, 6921–6929 (2017).
Chang, M.-F. et al. Low VDDmin swing-sample-and-couple sense amplifier and energy-efficient self-boost-write-termination scheme for embedded ReRAM macros against resistance and switch-time variations. IEEE J. Solid-State Circuits 50, 2786–2795 (2015).
Li, Y. et al. Improvement of resistive switching characteristics in ZrO2 film by embedding a thin TiOx layer. Nanotechnology 22, 254028 (2011).
Rana, A. M. et al. Endurance and cycle-to-cycle uniformity improvement in tri-layered CeO2/Ti/CeO2 resistive switching devices by changing top electrode material. Sci. Rep. 7, 39539 (2017).
Merced-Grafals, E. J., Dávila, N., Ge, N., Williams, R. S. & Strachan, J. P. Repeatable, accurate, and high speed multi-level programming of memristor 1T1R arrays for power efficient analog computing applications. Nanotechnology 27, 365202 (2016).
Kim, K. M. et al. Voltage divider effect for the improvement of variability and endurance of TaOx memristor. Sci. Rep. 6, 20085 (2016).
Wang, G. et al. Impact of program/erase operation on the performances of oxide-based resistive switching memory. Nanoscale Res. Lett. 10, 39 (2015).
Adam, G. C., Hoskins, B. D., Prezioso, M. & Strukov, D. B. Optimized stateful material implication logic for three-dimensional data manipulation. Nano Res. 9, 3914–3923 (2016).
Balatti, S. et al. Pulsed cycling operation and endurance failure of metal-oxide resistive (RRAM). 2014 IEEE Int. Electron Devices Meet. (IEDM) https://doi.org/10.1109/IEDM.2014.7047050 (2014).
Mielke, N. et al. Bit error rate in NAND flash memories. 2008 IEEE Int. Reliability Phys. Symp. (RELPHY) https://doi.org/10.1109/RELPHY.2008.4558857 (2008).
Lee, A. R. et al. Memory window engineering of Ta2O5-x oxide-based resistive switches via incorporation of various insulating frames. Sci. Rep. 6, 30333 (2016).
Schmelzer, S., Linn, E., Bottger, U. & Waser, R. Uniform complementary resistive switching in tantalum oxide using current sweeps. IEEE Electron Device Lett. 34, 114–116 (2013).
Acknowledgements
The authors would like to thank D. Strukov and his research group for providing the memristors used in this paper and the procedure to electroform and program them.
Author information
Authors and Affiliations
Contributions
M.A.L.-M. conceived the initial idea, conducted the measurements and analysed the results. K.-T.C. supervised the research, discussed the idea and results, and suggested actions throughout the research. M.A.L.-M. and K.-T.C. wrote the manuscript and discussed the results and implications at all stages.
Corresponding authors
Ethics declarations
Competing interests
A patent application has been submitted by HKUST and UCSB based on these results.
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 Notes 1–8 and Supplementary Figures 1–8
Rights and permissions
About this article
Cite this article
Lastras-Montaño, M.A., Cheng, KT. Resistive random-access memory based on ratioed memristors. Nat Electron 1, 466–472 (2018). https://doi.org/10.1038/s41928-018-0115-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41928-018-0115-z
This article is cited by
-
Recent Advances in In-Memory Computing: Exploring Memristor and Memtransistor Arrays with 2D Materials
Nano-Micro Letters (2024)
-
Recent progress of layered memristors based on two-dimensional MoS2
Science China Information Sciences (2023)
-
Ratio-based multi-level resistive memory cells
Scientific Reports (2021)
-
A bidirectional threshold switching selector with a symmetric multilayer structure
Science China Information Sciences (2021)
-
Two-dimensional materials for next-generation computing technologies
Nature Nanotechnology (2020)