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Journal of Computational Electronics

, Volume 18, Issue 4, pp 1214–1221 | Cite as

A computational study of short-channel effects in double-gate junctionless graphene nanoribbon field-effect transistors

  • Khalil TamersitEmail author
Article

Abstract

As the channel length shrinks below the 10-nm regime, emerging materials, junctionless technology, and multiple-gate geometries provide an excellent combination to continue progress towards lower-cost high-performance ultrascaled devices. In this study, the double-gate junctionless (JL) graphene nanoribbon field-effect transistor (GNRFET) and its conventional counterpart (C-GNRFET) are compared in terms of short-channel effects (SCEs) using a quantum simulation. The computational approach is based on solving the Schrödinger equation using the mode-space nonequilibrium Green’s function formalism coupled self-consistently with a Poisson equation in the ballistic limit. The analysis of gate length downscaling shows that the JL GNRFET exhibits better leakage current, subthreshold swing (SS), drain-induced barrier lowering, and threshold voltage roll-off in comparison with the conventional GNRFET. In addition, we reveal that a decrease in the n-type doping concentration can enhance the above-mentioned characteristics of both devices. The results indicate that the JL GNRFET can mitigate critical issues and enhance the immunity to SCEs of the GNRFET, making it a promising candidate for high-performance ultrascaled (sub-5-nm) technology.

Keywords

Junctionless (JL) Graphene nanoribbon (GNR) Field-effect transistor (FET) Nonequilibrium Green’s function (NEGF) Short-channel effects (SCEs) Band-to-band tunneling (BTBT) 

Notes

References

  1. 1.
    Lee, C.-W., Afzalian, A., Akhavan, N.D., Yan, R., Ferain, I., Colinge, J.-P.: Junctionless multigate field-effect transistor. Appl. Phys. Lett. 94(5), 053511 (2009).  https://doi.org/10.1063/1.3079411 CrossRefGoogle Scholar
  2. 2.
    Colinge, J.-P., Lee, C.-W., Afzalian, A., Akhavan, N.D., Yan, R., Ferain, I., Razavi, P., O’Neill, B., Blake, A., White, M., Kelleher, A.-M., McCarthy, B., Murphy, R.: Nanowire transistors without junctions. Nat. Nanotechnol. 5(3), 225–229 (2010).  https://doi.org/10.1038/nnano.2010.15 CrossRefGoogle Scholar
  3. 3.
    Lee, C.-W., Ferain, I., Afzalian, A., Yan, R., Akhavan, N.D., Razavi, P., Colinge, J.-P.: Performance estimation of junctionless multigate transistors. Solid-State Electron. 54(2), 97–103 (2010).  https://doi.org/10.1016/j.sse.2009.12.003 CrossRefGoogle Scholar
  4. 4.
    Lou, H., Zhang, L., Zhu, Y., Lin, X., Yang, S., He, J., Chan, M.: A junctionless nanowire transistor with a dual-material gate. IEEE Trans. Electron Devices 59(7), 1829–1836 (2012).  https://doi.org/10.1109/TED.2012.2192499 CrossRefGoogle Scholar
  5. 5.
    Han, M.-H., Chang, C.-Y., Chen, H.-B., Wu, J.-J., Cheng, Y.-C., Wu, Y.-C.: Performance comparison between bulk and SOI junctionless transistors. IEEE Electron Device Lett. 34(2), 169–171 (2013).  https://doi.org/10.1109/LED.2012.2231395 CrossRefGoogle Scholar
  6. 6.
    Ansari, L., Feldman, B., Fagas, G., Colinge, J.-P., Greer, J.C.: Simulation of junctionless Si nanowire transistors with 3 nm gate length. Appl. Phys. Lett. 97(6), 062105 (2010).  https://doi.org/10.1063/1.3478012 CrossRefGoogle Scholar
  7. 7.
    Barraud, S., Berthome, M., Coquand, R., Casse, M., Ernst, T., Samson, M.-P., Perreau, P., Bourdelle, K.K., Faynot, O., Poiroux, T.: Scaling of trigate junctionless nanowire MOSFET With gate length down to 13 nm. IEEE Electron Device Lett. 33(9), 1225–1227 (2012).  https://doi.org/10.1109/LED.2012.2203091 CrossRefGoogle Scholar
  8. 8.
    Agarwal, T., Sorée, B., Radu, I., Raghavan, P., Fiori, G., Iannaccone, G., Thean, A., Heyns, M., Dehaene, W.: Comparison of short-channel effects in monolayer MoS2 based junctionless and inversion-mode field-effect transistors. Appl. Phys. Lett. 108(2), 023506 (2016).  https://doi.org/10.1063/1.4939933 CrossRefGoogle Scholar
  9. 9.
    Guo, J.: Modeling of graphene nanoribbon devices. Nanoscale 4(18), 5538–5548 (2012).  https://doi.org/10.1039/C2NR31437A CrossRefGoogle Scholar
  10. 10.
    Wang, X., Ouyang, Y., Li, X., Wang, H., Guo, J., Dai, H.: Room-temperature all-semiconducting sub-10-nm graphene nanoribbon field-effect transistors. Phys. Rev. Lett. 100(20), 206803 (2008).  https://doi.org/10.1103/PhysRevLett.100.206803 CrossRefGoogle Scholar
  11. 11.
    Llinas, J.P., Fairbrother, A., Borin Barin, G., Shi, W., Lee, K., Wu, S., Yong Choi, B., Braganza, R., Lear, J., Kau, N., Choi, W., Chen, C., Pedramrazi, Z., Dumslaff, T., Narita, A., Feng, X., Müllen, K., Fischer, F., Zettl, A., Ruffieux, P., Yablonovitch, E., Crommie, M., Fasel, R., Bokor, J.: Short-channel field-effect transistors with 9-atom and 13-atom wide graphene nanoribbons. Nat. Commun. (2017).  https://doi.org/10.1038/s41467-017-00734-x CrossRefGoogle Scholar
  12. 12.
    Marmolejo-Tejada, J.M., Velasco-Medina, J.: Review on graphene nanoribbon devices for logic applications. Microelectron. J. 48, 18–38 (2016).  https://doi.org/10.1016/j.mejo.2015.11.006 CrossRefGoogle Scholar
  13. 13.
    Barik, M.A., Deka, R., Dutta, J.C.: Carbon nanotube-based dual-gated junctionless field-effect transistor for acetylcholine detection. IEEE Sens. J. 16(2), 280–286 (2016).  https://doi.org/10.1109/JSEN.2015.2481604 CrossRefGoogle Scholar
  14. 14.
    Barik, M.A., Dutta, J.C.: Fabrication and characterization of junctionless carbon nanotube field effect transistor for cholesterol detection. Appl. Phys. Lett. 105(5), 053509 (2014).  https://doi.org/10.1063/1.4892469 CrossRefGoogle Scholar
  15. 15.
    Ansari, L., Feldman, B., Fagas, G., Lacambra, C.M., Haverty, M.G., Kuhn, K.J., Shankar, S., Greer, J.C.: First principle-based analysis of single-walled carbon nanotube and silicon nanowire junctionless transistors. IEEE Trans. Nanotechnol. 12(6), 1075–1081 (2013).  https://doi.org/10.1109/TNANO.2013.2279424 CrossRefGoogle Scholar
  16. 16.
    Barbastegan, S., Shahhoseini, A.: Performance analysis of junctionless carbon nanotube field effect transistors using NEGF formalism. Mod. Phys. Lett. B 30(10), 1650125 (2016).  https://doi.org/10.1142/S0217984916501256 CrossRefGoogle Scholar
  17. 17.
    Pourian, P., Yousefi, R., Ghoreishi, S.S.: Effect of uniaxial strain on electrical properties of CNT-based junctionless field-effect transistor: numerical study. Superlattices Microstruct. 93, 92–100 (2016).  https://doi.org/10.1016/j.spmi.2016.03.014 CrossRefGoogle Scholar
  18. 18.
    Bala, S., Khosla, M.: Design and analysis of electrostatic doped tunnel CNTFET for various process parameters variation. Superlattices Microstruct. 124, 160–167 (2018).  https://doi.org/10.1016/j.spmi.2018.10.007 CrossRefGoogle Scholar
  19. 19.
    Guo, J., Datta, S., Lundstrom, M., Anantam, M.P.: Toward multiscale modeling of carbon nanotube transistors. Int. J. Multisc. Comput. Eng. 2(2), 257–276 (2004).  https://doi.org/10.1615/IntJMultCompEng.v2.i2.60 CrossRefGoogle Scholar
  20. 20.
    Koswatta, S.O., Lundstrom, M.S., Anantram, M.P., Nikonov, D.E.: Simulation of phonon-assisted band-to-band tunneling in carbon nanotube field-effect transistors. Appl. Phys. Lett. 87(25), 253107 (2005).  https://doi.org/10.1063/1.2146065 CrossRefGoogle Scholar
  21. 21.
    Koswatta, S.O., Nikonov, D.E., Lundstrom, M.S.: Computational study of carbon nanotube p–i–n tunnel FETs. In: IEEE International Electron Devices Meeting. IEDM Technical Digest, pp. 518–521 (2005).  https://doi.org/10.1109/IEDM.2005.1609396
  22. 22.
    Zhao, P., Guo, J.: Modeling edge effects in graphene nanoribbon field-effect transistors with real and mode space methods. J. Appl. Phys. 105(3), 034503-1–034503-7 (2009).  https://doi.org/10.1063/1.3073875 CrossRefGoogle Scholar
  23. 23.
    Son, Y.-W., Cohen, M.L., Louie, S.G.: Energy gaps in graphene nanoribbons. Phys. Rev. Lett. 97(21), 216803-1–216803-4 (2006).  https://doi.org/10.1103/PhysRevLett.97.216803 CrossRefGoogle Scholar
  24. 24.
    Chin, S.-K., Seah, D., Lam, K.-T., Samudra, G.S., Liang, G.: Device physics and characteristics of graphene nanoribbon tunneling FETs. IEEE Trans. Electron Devices 57(11), 3144–3152 (2010).  https://doi.org/10.1109/TED.2010.2065809 CrossRefGoogle Scholar
  25. 25.
    Tamersit, K., Djeffal, F.: Double-gate graphene nanoribbon field-effect transistor for DNA and gas sensing applications: simulation study and sensitivity analysis. IEEE Sensors J. 16(11), 4180–4191 (2016).  https://doi.org/10.1109/JSEN.2016.2550492 CrossRefGoogle Scholar
  26. 26.
    Tamersit, K., Djeffal, F.: Boosting the performance of a nanoscale graphene nanoribbon field-effect transistor using graded gate engineering. J. Comput. Electron. 17(3), 1276–1284 (2018).  https://doi.org/10.1007/s10825-018-1209-6 CrossRefGoogle Scholar
  27. 27.
    Datta, S.: Nanoscale device modeling: the Green’s function method. Superlattices Microstruct. 28(4), 253–278 (2000).  https://doi.org/10.1006/spmi.2000.0920 CrossRefGoogle Scholar
  28. 28.
    Anantram, M.P., Lundstrom, M.S., Nikonov, D.E.: Modeling of nanoscale devices. Proc. IEEE 96(9), 1511–1550 (2008).  https://doi.org/10.1109/JPROC.2008.927355 CrossRefGoogle Scholar
  29. 29.
    Tamersit, K., Djeffal, F.: A novel graphene field-effect transistor for radiation sensing application with improved sensitivity: proposal and analysis. Nucl. Instrum. Methods Phys. Res. Sect. A 901, 32–39 (2018).  https://doi.org/10.1016/j.nima.2018.05.075 CrossRefGoogle Scholar
  30. 30.
    Ortiz-Conde, A., Garcı́a Sánchez, F.J., Liou, J.J., Cerdeira, A., Estrada, M., Yue, Y.: A review of recent MOSFET threshold voltage extraction methods. Microelectron. Reliab. 42(4–5), 583–596 (2002).  https://doi.org/10.1016/S0026-2714(02)00027-6 CrossRefGoogle Scholar
  31. 31.
    Fiori, G., Iannaccone, G.: Simulation of graphene nanoribbon field-effect transistors. IEEE Electron Device Lett. 28(8), 760–762 (2007).  https://doi.org/10.1109/LED.2007.901680 CrossRefGoogle Scholar
  32. 32.
    Tamersit, K.: Quantum simulation of a junctionless carbon nanotube field-effect transistor with binary metal alloy gate electrode. Superlattices Microstruct. 128, 252–259 (2019).  https://doi.org/10.1016/j.spmi.2019.02.001 CrossRefGoogle Scholar
  33. 33.
    Naderi, A., Tahne, B.A.: Review—methods in improving the performance of carbon nanotube field effect transistors. ECS J. Solid State Sci. Technol. 5(12), M131–M140 (2016).  https://doi.org/10.1149/2.0021612jss CrossRefGoogle Scholar
  34. 34.
    Naderi, A., Keshavarzi, P.: Electrically-activated source extension graphene nanoribbon field effect transistor: novel attributes and design considerations for suppressing short channel effects. Superlattices Microstruct. 72, 305–318 (2014).  https://doi.org/10.1016/j.spmi.2014.05.003 CrossRefGoogle Scholar
  35. 35.
    Yousefi, R., Shabani, M., Arjmandi, M., Ghoreishi, S.S.: A computational study on electrical characteristics of a novel band-to-band tunneling graphene nanoribbon FET. Superlattices Microstruct. 60, 169–178 (2013).  https://doi.org/10.1016/j.spmi.2013.05.003 CrossRefGoogle Scholar
  36. 36.
    Naderi, A.: Theoretical analysis of a novel dual gate metal–graphene nanoribbon field effect transistor. Mater. Sci. Semicond. Process. 31, 223–228 (2015).  https://doi.org/10.1016/j.mssp.2014.11.051 CrossRefGoogle Scholar
  37. 37.
    Akbari Eshkalak, M., Anvarifard, M.K.: A novel graphene nanoribbon FET with an extra peak electric field (EFP-GNRFET) for enhancing the electrical performances. Phys. Lett. A 381(16), 1379–1385 (2017).  https://doi.org/10.1016/j.physleta.2017.02.032 CrossRefGoogle Scholar
  38. 38.
    Ouyang, Y., Yoon, Y., Guo, J.: Scaling behaviors of graphene nanoribbon FETs: a three-dimensional quantum simulation study. IEEE Trans. Electron Devices 54(9), 2223–2231 (2007).  https://doi.org/10.1109/TED.2007.902692 CrossRefGoogle Scholar
  39. 39.
    Owlia, H., Keshavarzi, P.: Investigation of the novel attributes of a double-gate graphene nanoribbon FET with AlN high-κ dielectrics. Superlattices Microstruct. 75, 613–620 (2014).  https://doi.org/10.1016/j.spmi.2014.09.003 CrossRefGoogle Scholar
  40. 40.
    Akbari Eshkalak, M., Faez, R., Haji-Nasiri, S.: A novel graphene nanoribbon field effect transistor with two different gate insulators. Physica E 66, 133–139 (2015).  https://doi.org/10.1016/j.physe.2014.10.021 CrossRefGoogle Scholar
  41. 41.
    Tamersit, K.: Performance assessment of a new radiation dosimeter based on carbon nanotube field-effect transistor: a quantum simulation study. IEEE Sens. J. 19(9), 3314–3321 (2019).  https://doi.org/10.1109/JSEN.2019.2894440 CrossRefGoogle Scholar
  42. 42.
    Rawat, B., Paily, R.: Modeling of graphene-based field-effect transistors through a 1-D real-space approach. J. Comput. Electron. 17(1), 90–100 (2017).  https://doi.org/10.1007/s10825-017-1069-5 CrossRefGoogle Scholar
  43. 43.
    Tamersit, K.: An ultra-sensitive gas nanosensor based on asymmetric dual-gate graphene nanoribbon field-effect transistor: proposal and investigation. J. Comput. Electron. (2019).  https://doi.org/10.1007/s10825-019-01349-9 CrossRefGoogle Scholar
  44. 44.
    Tamersit, K., Djeffal, F.: A computationally efficient hybrid approach based on artificial neural networks and the wavelet transform for quantum simulations of graphene nanoribbon FETs. J. Comput. Electron. (2019).  https://doi.org/10.1007/s10825-019-01350-2 CrossRefGoogle Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Electronics and TelecommunicationsUniversité 8 Mai 1945 GuelmaGuelmaAlgeria

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