Boolean Logic Gates from a Single Memristor via Low-Level Sequential Logic

  • Ella Gale
  • Ben de Lacy Costello
  • Andrew Adamatzky
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7956)


By using the memristor’s memory to both store a bit and perform an operation with a second input bit, simple Boolean logic gates have been built with a single memristor. The operation makes use of the interaction of current spikes (occasionally called current transients) found in both memristors and other devices. The sequential time-based logic methodology allows two logical input bits to be used on a one-port by sending the bits separated in time. The resulting logic gate is faster than one relying on memristor’s state switching, low power and requires only one memristor. We experimentally demonstrate working OR and XOR gates made with a single flexible Titanium dioxide sol-gel memristor.


Memristor sequential logic ReRAM OR XOR Boolean logic Time-separated logic 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Strukov, D.B., Snider, G.S., Stewart, D.R., Williams, R.S.: The Missing Memristor Found. Nature 453, 80–83 (2008)CrossRefGoogle Scholar
  2. 2.
    Chua, L.O.: Memristor - The Missing Circuit Element. IEEE Trans. Circuit Theory 18, 507–519 (1971)CrossRefGoogle Scholar
  3. 3.
    Chua, L.O.: Resistance Switching Memories are Memristors. Applied Physics A: Materials Science & Processing, 765–782 (2011)Google Scholar
  4. 4.
    Waser, R.: Nanoelectronics and Information Technology. Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim (2003)Google Scholar
  5. 5.
    Cantley, K., Subramaniam, A., Stiegler, H., Chapman, R., Vogel, E.: Hebbian Learning in Spiking Neural Networks with Nano-Crystalline Silicon TFTs and Memristive Synapses. IEEE Tran. Nanotechnology 10, 1066–1073 (2011)CrossRefGoogle Scholar
  6. 6.
    Zamarreno-Ramos, C., Carmuñas, L.A., Pérez-Carrasco, J.A., Masquelier, T., Serrano-Gotarredona, T., Linares-Barranco, B.: On Spike-Timing Dependent Plasticity, Memristive Devices and Building a Self-Learning Visual Cortex. Frontiers in Neuromorphic Engineering 5, 26(1)–26(20) (2011)Google Scholar
  7. 7.
    Howard, G.D., Gale, E., Bull, L., de Lacy Costello, B., Adamatzky, A.: Evolution of Plastic Learning in Spiking Networks via Memristive Connection. IEEE Trans. Evolutionary Computation 26, 711–719 (2012)CrossRefGoogle Scholar
  8. 8.
    Chua, L., Sbitnev, V., Kim, H.: Hodgkin-Huxley Axon is made of Memristors. Int. J. Bifur. Chaos 22, 1230011(1)–1230011(48) (2012)Google Scholar
  9. 9.
    Chua, L., Sbitnev, V., Kim, H.: Neurons are Poised Near the Edge of Chaos. Int. J. Bifur. Chaos 22, 1250098(1)–1250098(49) (2012)Google Scholar
  10. 10.
    Gale, E.M., de Lacy Costello, B., Adamatzky, A.: Observation and Characterization of Memristor Current Spikes and their Application to Neuromorphic Computation. In: 2012 International Conference on Numerical Analysis and Applied Mathematics, ICNAAM 2012. AIP Conference Proceedings, vol. 1479, pp. 1898–1901. AIP Melvil, New York (2012)Google Scholar
  11. 11.
    Borghetti, J., Snider, G.D., Kuekes, P.J., Yang, J.J., Stewart, D.R., Williams, R.S.: ‘Memristive’ switches enable ‘stateful’ logic operations via material implication. Nature 464, 873–876 (2010)CrossRefGoogle Scholar
  12. 12.
    Pershin, Y.V., di Ventra, M.: Neuromorphic, Digital and Quantum Computation with Memory Circuit Elements. Proc. IEEE 100, 2071–2080 (2012)CrossRefGoogle Scholar
  13. 13.
    Pino, R.E., Bohl, J.W.: Self-Reconfigurable Memristor-Based Analog Resonant Computer, US Patent, US 8,274,312 B2Google Scholar
  14. 14.
    Gale, E., Pearson, D., Kitson, S., Adamatzky, A., de Lacy Costello, B.: Aluminium Electrodes Effect the Operation f Titanium Dioxide Sol-Gel Memristors, arXiv:1106:6293v1 (cond-mat.mtrl-ci),
  15. 15.
    Gale, E., Mayne, R., Adamatzky, A., de Lacy Costello, B.: Drop-coated Titanium Dioxide Memristors, arXiv:1205:2885v2 (cond-mat.mtrl-ci),
  16. 16.
    Gale, E.: The Missing Magnetic Flux in the HP Memristor Found, arXiv:1106:3170v1 (cond-mat.mtrl-ci),
  17. 17.
    Gale, E., Matthews, O., de Lacy Costello, B., Adamatzky, A.: Beyond Markov Chains, Towards Adaptive Memristor Network-based Music Generation. In: Proceedings of the Annual Convention of Society of the study of Artificial Intelligence and the Simulation of Behaviour, AISB 2013, vol. 8, pp. 28–49 (2013)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ella Gale
    • 1
  • Ben de Lacy Costello
    • 1
  • Andrew Adamatzky
    • 1
  1. 1.Unconventional Computing Group, Dept. of Applied Sciences & Dept. of Computer Science and Creative TechnologyUniversity of the West of EnglandBristolUK

Personalised recommendations