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Modeling of single-electron tunneling networks for supersensitive sensors at room temperature

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Abstract

Due to their unique properties of ultralow power dissipation and extremely high density, single-electron devices represent the best option for highly sensitive sensors. Despite their excellent performance in capturing subtle electrical signals at cryogenic temperatures, the signal detectability at room temperature or higher is substantially degraded by thermal noise. To reduce such interference from thermal noise at room temperature, the physical dimensions of single-electron devices are conventionally scaled down to below 10 nm, but this leads to great challenges in device fabrication processes. The challenge of retaining superior signal detectability of single-electron devices at room temperature without aggressive scaling is addressed herein. It is proposed that the effects of capacitive and resistive signal coupling between adjacent single-electron devices can be exploited to enhance the signal-to-noise ratio of sensor outputs. A series of efficient coupled networks that shift the peak signal detectability from cryogenic to room temperature are studied. The impacts of the network topology, coupling strength, and bias voltage are investigated. The simulation results reveal that, for given device dimensions, the proposed coupled device network improves the room-temperature signal detectability by 13.2 dB (i.e., an enhancement of 200%) over the uncoupled device array. Moreover, at room temperature, the signal-to-noise ratio of the proposed nonscaled coupled device network is much better than that of aggressively scaled device arrays. These results confirm that efficient coupled networks enable the operation of supersensitive single-electron device sensors at room temperature.

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References

  1. Averin, D.V., Likharev, K.K.: Coulomb blockade of single-electron tunneling. J. Low Temp. Phys. 62(3), 346–373 (1986)

    Google Scholar 

  2. Likharev, K.K.: Single-electron devices and their applications. Proc. IEEE 87, 606–632 (1999)

    Article  Google Scholar 

  3. Ohshima, T., Kiehl, R.A.: Operation of bistable phase-locked single-electron tunneling logic elements. J. Appl. Phys. 80, 912–923 (1996)

    Article  Google Scholar 

  4. Wei, Y., Weis, J., Klitzing, K., Eberl, K.: Single-electron transistor as an electrometer measuring chemical potential variations. Appl. Phys. Lett. 71, 2514–2516 (1997)

    Article  Google Scholar 

  5. Nishiguchi, K., Koechlin, C., Ono, Y., Fujiwara, A., Inokawa, H., Yamaguchi, H.: Single-electron-resolution electrometer based on field-effect transistor. Jpn. J. Appl. Phys. 47, 8305–8310 (2008)

    Article  Google Scholar 

  6. Kumar, O., Kaur, M.: Single electron transistor: applications and problems. Int. J. VLSI Des. Commun. Syst. 1(4), 24–29 (2010)

    Article  Google Scholar 

  7. Nakamura, S., Pashkin, Y.A., Tsai, J., Kaneko, N.: Single-electron pumping by parallel SINIS turnstiles for quantum current standard. IEEE Trans. Instrum. Meas. 64(6), 1696–1701 (2015)

    Article  Google Scholar 

  8. Karre, P., Acharya, M., Kundsen, W.: Single electron transistor-based gas sensing with tungsten nanoparticles at room temperature. IEEE Sens. J. 8, 797–802 (2010)

    Article  Google Scholar 

  9. Beaumont, A., Dubuc, C., Beauvais, J., Drouin, D.: Room temperature single-electron transistor featuring gate-enhanced ON-state current. IEEE Electron Device Lett. 30(7), 766–768 (2009)

    Article  Google Scholar 

  10. Deshpande, V., Wacquez, R., Vinet, M., Jehl, X.: 300 K operating full-CMOS integrated single electron transistor (SET)-FET circuits. In: Electron Devices Meeting, pp. 8.7.1-8.7.4 (2012)

  11. Sun, Y., Singh, N.: Room-temperature operation of silicon single-electron transistor fabricated using optical lithography. IEEE Trans. Nanotechnol. 10(1), 96–98 (2011)

    Article  Google Scholar 

  12. Zheng, H., Asbahi, M., Mukherjee, S., et al.: Room temperature Coulomb blockade effects in Au nanocluster/pentacene single electron transistors. Nanotechnology 26(35), 355204–355221 (2015)

    Article  Google Scholar 

  13. Karbasian, G., McConnell, M.S., George, H.: Metal-insulator-metal single electron transistors with tunnel barriers prepared by atomic layer deposition. Appl. Sci. 7, 246–268 (2017)

    Article  Google Scholar 

  14. Lu, C., Raghunathan, V., Roy, K.: Efficient design of micro-scale energy harvesting systems. IEEE J. Emerg. Sel. Top. Circuits Syst. 1(3), 254–266 (2011)

    Article  Google Scholar 

  15. Utagawa, A., Asai, T.: Noise-driven image processing based on array-enhanced stochastic resonance with population heterogeneity. In: International Symposium on Intelligent Signal Processing and Communication Systems, pp. 437–440 (2009)

  16. Querlioz, D., Trauchessec, V.: Stochastic resonance in an analog current-mode neuromorphic circuit. In: IEEE International Symposium on Circuits and Systems, pp. 1596–1599 (2013)

  17. Imai, Y., et al.: Detection of weak biological signal utilizing stochastic resonance in a GaAs-based nanowire FET and its parallel summing network. Jpn. J. Appl. Phys. 53(6S), 06JE01 (2014)

    Article  Google Scholar 

  18. McNamara, B., Wiesenfeld, K.: Theory of stochastic resonance. Phys. Rev. A 39, 4854–4869 (1989)

    Article  Google Scholar 

  19. Maass, W.: Noise as a resource for computation and learning in networks of spiking neurons. Proc. IEEE 102(5), 860–880 (2014)

    Article  Google Scholar 

  20. Oya, T., Asai, T., Amemiya, Y.: Stochastic resonance in an ensemble of single-electron neuromorphic devices and its application to competitive neural networks. Chaos Solitons Fractals 32(2), 855–861 (2007)

    Article  Google Scholar 

  21. Kasai, S.: Stochastic resonance in nanodevice parallel systems. In: International Symposium on Intelligent Signal Processing and Communication Systems, pp. 363–366 (2009)

  22. Sato, S., Nakajima, K.: Application of single electron devices utilizing stochastic dynamics. Int. J. Nanotechnol. Mol. Comput. 1(2), 29–42 (2009)

    Article  Google Scholar 

  23. Oya, T.: Stochastic resonance in a balanced pair of single-electron boxes. Fluct. Noise Lett. 10(3), 267–275 (2011)

    Article  Google Scholar 

  24. Weber, J., Weis, J., Hauser, M., Klitzing, K.: Fabrication of an array of single-electron transistors for a scanning probe microscope sensor. Nanotechnology 19(37), 375301 (2008)

    Article  Google Scholar 

  25. Korotkov, A.: Single-electron transistor controlled with a RC circuit. Phys. Rev. B 49(23), 518–522 (1994)

    Article  Google Scholar 

  26. Oya, T., Takahashi, Y., Ikebe, M., Asai, T., Amemiya, Y.: A single-electron circuit as a discrete dynamical system. Superlattices Microstruct. 34, 253–258 (2003)

    Article  Google Scholar 

  27. Oya, T., Asai, T., Fukui, T., Amemiya, Y.: Reaction–diffusion systems consisting of single-electron oscillators. Int. J. Unconv. Comput. 1, 177–194 (2005)

    Google Scholar 

  28. Guo, D., Wu, S., Sbitnev, V.I., Chua, L.O.: Stochastic resonance of SET device implemented for nanoscale sensor operating in room temperature. In: Proceedings of Pacific Rim Workshop on Transducers and Micro/Nano, pp. 425–428 (2002)

  29. Fujino, H., Oya, T.: Analysis of electron transfer among quantum dots in two-dimensional quantum dot network. Jpn. J. Appl. Phys. 53(6S), 06JE02 (2014)

    Article  Google Scholar 

  30. Babiker, S.F., Naeem, R.: Shot noise suppression in single electron transistors. IEEE Trans. Nanotechnol. 11(6), 1267–1272 (2012)

    Article  Google Scholar 

  31. Martinez, C., Beivide, R., Stafford, E., Moreto, M., Gabidulin, E.M.: Modeling toroidal networks with the Gaussian integers. IEEE Trans. Comput. 57, 1046–1056 (2008)

    Article  MathSciNet  Google Scholar 

  32. Wu, Y., Zhao, J., Chen, D., Guo, D.: Modeling of Gaussian network-based reconfigurable network-on-chip designs. IEEE Trans. Comput. 65, 2134–2142 (2016)

    Article  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Department of Electronic Engineering, School of Information Science and Engineering, Xiamen University, Xiamen, 361005, China

    Yangbing Wu & Donghui Guo

  2. Department of Electrical and Computer Engineering, Southern Illinois University Carbondale, Carbondale, IL, 62901, USA

    Rujie Zhao & Chao Lu

Authors
  1. Yangbing Wu
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  2. Rujie Zhao
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  3. Chao Lu
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  4. Donghui Guo
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Correspondence to Chao Lu or Donghui Guo.

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Wu, Y., Zhao, R., Lu, C. et al. Modeling of single-electron tunneling networks for supersensitive sensors at room temperature. J Comput Electron 19, 222–233 (2020). https://doi.org/10.1007/s10825-019-01436-x

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  • DOI: https://doi.org/10.1007/s10825-019-01436-x

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