Journal of Computational Electronics

, Volume 15, Issue 4, pp 1123–1129 | Cite as

Incoherent transport in NEMO5: realistic and efficient scattering on phonons

  • James Charles
  • Prasad Sarangapani
  • Roksana Golizadeh-Mojarad
  • Robert Andrawis
  • Daniel Lemus
  • Xinchen Guo
  • Daniel Mejia
  • James E. Fonseca
  • Michael Povolotskyi
  • Tillmann Kubis
  • Gerhard Klimeck


In this work, the coherent and incoherent transport simulation capabilities of the multipurpose nanodevice simulation tool NEMO5 are presented and applied on transport in tunneling field-effect transistors. The comparison with experimental resistivity data confirms the validity of NEMO5’s phonon-scattering models. Common pitfalls of numerical implementations and the applicability of common approximations of scattering self-energies are discussed. The impact of phonon-assisted tunneling on the performance of TFETs is exemplified with a concrete Si nanowire device. The communication-efficient implementation of self-energies in NEMO5 is demonstrated with a scaling comparison of self-energies solved with blocking and nonblocking MPI-communication.


Inelastic scattering Non-equilibrium Green’s function Electron–phonon scattering Tunneling field-effect transistors 



The use of computational resources operated by the Network for Computational Nanotechnology, funded by the US National Science Foundation under Grant Nos. EEC-0228390, EEC-1227110, EEC-0228390, EEC-0634750, OCI-0438246, OCI-0832623, and OCI-0721680, is gratefully acknowledged. NEMO5 developments were critically supported by an NSF Peta-Apps award OCI-0749140 and by Intel Corp. This work was supported in part by funding from the Semiconductor Research Corporation’s Global Research Collaboration (GRC) (2653.001), and Member Specific Research Intel (MSR-Intel) (2434.001). Additional funding was provided by the Semiconductor Research Corporation membership in the Network for Computational Nanotechnology. This research is part of the Blue Waters’ sustained-petascale computing project, which is supported by the National Science Foundation (award number ACI 1238993) and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications. This work is also part of the “Accelerating Nano-scale Transistor Innovation with NEMO5 on Blue Waters” PRAC allocation support by the National Science Foundation (award number OCI-0832623). This research was supported in part through computational resources provided by Information Technology at Purdue University, West Lafayette, Indiana.


  1. 1.
    International Technology Roadmap for Semiconductors. [Online]. Available:
  2. 2.
    Mehrotra, S., Kim, S., Kubis, T., Povolotskyi, M., Lundstrom, M.S., Klimeck, G.: Engineering nanowire n-MOSFETs at. IEEE Trans. Electron Devices 60(7), 2171–2177 (2013)CrossRefGoogle Scholar
  3. 3.
    Cui, Y., Zhong, Z., Wang, D., Wang, W.U., Lieber, C.M.: High performance silicon nanowire field effect transistors. Nano Lett. 3(2), 149–152 (2003)CrossRefGoogle Scholar
  4. 4.
    Appenzeller, J., Lin, Y.-M., Knoch, J., Avouris, P.: Band-to-band tunneling in carbon nanotube field-effect transistors. Phys. Rev. Lett. 93(19), 196805 (2004)CrossRefGoogle Scholar
  5. 5.
    Zhu, Y., Hudait, M.K.: Low-power tunnel field effect transistors using mixed As and Sb based heterostructures. Nanotechnol. Rev. 2(6), 637–678 (2013)CrossRefGoogle Scholar
  6. 6.
    Ilatikhameneh, H., Klimeck, G., Rahman, R.: Can homojunction tunnel FETs scale below 10nm? IEEE EDL 37(1), 115–118 (2016)CrossRefGoogle Scholar
  7. 7.
    Sarkar, D., Xie, X., Liu, W., Cao, W., Kang, J., Gong, Y., Kraemer, S., Ajayan, P.M., Banerjee, K.: A subthermionic tunnel field-effect transistor with an atomically thin channel. Nature 526(7571), 91–95 (2015)CrossRefGoogle Scholar
  8. 8.
    Li, M.O., Esseni, D., Nahas, J.J., Jena, D., Xing, H.G.: Two-dimensional heterojunction interlayer tunneling field effect transistors (Thin-TFETs). IEEE J. Electron Devices Soc. 3(3), 200–207 (2015)CrossRefGoogle Scholar
  9. 9.
    Dewey, G., Chu-Kung, B., Boardman, J., Fastenau, J., Kavalieros, J., Kotlyar, R., Liu, W., Lubyshev, D., Metz, M., Mukherjee, N.: Fabrication, characterization, and physics of III-V heterojunction tunneling field effect transistors (H-TFET) for steep sub-threshold swing. IEEE Int. Electron Devices Meet. (IEDM). 33–6 (2011)Google Scholar
  10. 10.
    Mohata, D., Mookerjea, S., Agrawal, A., Li, Y., Mayer, T., Narayanan, V., Liu, A., Loubychev, D., Fastenau, J., Datta, S.: Experimental staggered-source and N+ pocket-doped channel III-V tunnel field-effect transistors and their scalabilities. Appl. Phys. Exp 4(2), 024105 (2011)CrossRefGoogle Scholar
  11. 11.
    Trivedi, A.R., Amir, M.F., Mukhopadhyay, S.: Ultra-low power electronics with Si/Ge tunnel FET. Des. Autom. Test Eur. Conf. Exhib. (DATE) 2014, 1–6 (2014)Google Scholar
  12. 12.
    Zhao, Q.-T., Richter, S., Schulte-Braucks, C., Knoll, L., Blaeser, S., Luong, G.V., Trellenkamp, S., Schafer, A., Tiedemann, A., Hartmann, J.-M.: Strained Si and SiGe nanowire tunnel FETs for logic and analog applications. IEEE J. Electron Devices Soc. 3(3), 103–114 (2015)CrossRefGoogle Scholar
  13. 13.
    Tomioka, K., Yoshimura, M., Fukui, T.: Steep-slope tunnel field-effect transistors using III-V nanowire/Si heterojunction. 2012 symposium on VLSI technology (VLSIT), pp. 47–48. (2012)Google Scholar
  14. 14.
    Kobayashi, M., Hiramoto, T.: Experimental study on quantum confinement effects in silicon nanowire metal-oxide-semiconductor field-effect transistors and single-electron transistors. J. Appl. Phys. 103(5), 053709 (2008)CrossRefGoogle Scholar
  15. 15.
    Cui, Y., Lauhon, L.J., Gudiksen, M.S., Wang, J., Lieber, C.M.: Diameter-controlled synthesis of single-crystal silicon nanowires. Appl. Phys. Lett. 78(15), 2214–2216 (2001)CrossRefGoogle Scholar
  16. 16.
    Lake, R., Klimeck, G., Bowen, R.C., Fernando, C., Moise, T., Kao, Y., Leng, M.: Interface roughness, polar optical phonons, and the valley current of a resonant tunneling diode. Superlattices Microstruct. 20(3), 279–285 (1996)CrossRefGoogle Scholar
  17. 17.
    Roblin, P., Liou, W.-R.: Three-dimensional scattering-assisted tunneling in resonant-tunneling diodes. Phys. Rev. B 47(4), 2146 (1993)CrossRefGoogle Scholar
  18. 18.
    Kubis, T., Vogl, P.: Assessment of approximations in nonequilibrium Green’s function theory. Phys. Rev. B 83(19), 195304 (2011)CrossRefGoogle Scholar
  19. 19.
    Gmachl, C., Capasso, F., Sivco, D.L., Cho, A.Y.: Recent progress in quantum cascade lasers and applications. Rep. Prog. Phys. 64(11), 1533 (2001)CrossRefGoogle Scholar
  20. 20.
    Luisier, M., Klimeck, G.: Simulation of nanowire tunneling transistors: from the Wentzel-Kramers-Brillouin approximation to full-band phonon-assisted tunneling. J. Appl. Phys. 107(8), 084507 (2010)CrossRefGoogle Scholar
  21. 21.
    Koswatta, S.O., Lundstrom, M.S., Nikonov, D.E.: Influence of phonon scattering on the performance of p-i-n band-to-band tunneling transistors. Appl. Phys. Lett. 92(4), 043125 3 (2008)CrossRefGoogle Scholar
  22. 22.
    Khayer, M.A., Lake, R.K.: Effects of band-tails on the subthreshold characteristics of nanowire band-to-band tunneling transistors. J. Appl. Phys. 110(7), 074508 (2011)CrossRefGoogle Scholar
  23. 23.
    Datta, S.: Nanoscale device modeling: the Green’s function method. Superlattices Microstruct. 28(4), 253–278 (2000)CrossRefGoogle Scholar
  24. 24.
    Taylor, J., Guo, H., Wang, J.: Ab initio modeling of quantum transport properties of molecular electronic devices. Phys. Rev. B 63(24), 245407 (2001)CrossRefGoogle Scholar
  25. 25.
    Wang, J.-S., Wang, J., Lü, J.: Quantum thermal transport in nanostructures. Eur. Phys. J. B 62(4), 381–404 (2008)CrossRefGoogle Scholar
  26. 26.
    Sadasivam, S., Che, Y., Huang, Z., Chen, L., Kumar, S., Fisher, T.S.: The atomistic Greens function method for interfacial phonon transport. Ann. Rev. Heat Transfer 17, 89–145 (2014)CrossRefGoogle Scholar
  27. 27.
    Steiger, S., Veprek, R.G., Witzigmann, B.: Electroluminescence from a quantum-well LED using NEGF. In: 13th International workshop on computational electronics, IWCE’09 2009, pp. 1–4. (2009)Google Scholar
  28. 28.
    Stewart, D.A., Leónard, F.: Energy conversion efficiency in nanotube optoelectronics. Nano Lett. 5(2), 219–222 (2005)CrossRefGoogle Scholar
  29. 29.
    Boykin, T.B., Klimeck, G., Oyafuso, F.: Valence band effective-mass expressions in the sp3d5s* empirical tight-binding model applied to a Si and Ge parametrization. Phys. Rev. B 69(11), 115201 (2004)CrossRefGoogle Scholar
  30. 30.
    Jacoboni, C., Reggiani, L.: The Monte Carlo method for the solution of charge transport in semiconductors with applications to covalent materials. Rev. Mod. Phys. 55(3), 645 (1983)CrossRefGoogle Scholar
  31. 31.
    Lake, R., Klimeck, G., Bowen, R.C., Jovanovic, D.: Single and multiband modeling of quantum electron transport through layered semiconductor devices. J. Appl. Phys. 81(12), 7845–7869 (1997)CrossRefGoogle Scholar
  32. 32.
    Anantram, M., Lundstrom, M.S., Nikonov, D.E.: Modeling of nanoscale devices. Proc. IEEE 96(9), 1511–1550 (2008)CrossRefGoogle Scholar
  33. 33.
    Springer Materials The Landolt-BörnsteinDatabaseGoogle Scholar
  34. 34.
    Esposito, A., Frey, M., Schenk, A.: Quantum transport including nonparabolicity and phonon scattering: application to silicon nanowires. J. Comput. Electron. 8(3 4), 336–348 (2009)CrossRefGoogle Scholar
  35. 35.
    Datta, S.: A simple kinetic equation for steady-state quantum transport. J. Phys. Condens. Matter 2(40), 8023 (1990)CrossRefGoogle Scholar
  36. 36.
    Mahan, G.D.: Many-Particle Physics. Springer, New York (2013)Google Scholar
  37. 37.
    Steiger, S., Povolotskyi, M., Park, H.-H., Kubis, T., Klimeck, G.: Nemo5: a parallel multiscale nanoelectronics modeling tool. IEEE Trans Nano 10, 1464 (2011)CrossRefGoogle Scholar
  38. 38.
    Niquet, Y.-M., Nguyen, V.-H., Triozon, F., Duchemin, I., Nier, O., Rideau, D.: Quantum calculations of the carrier mobility: methodology. Matthiessens rule, and comparison with semi-classical approaches. J. Appl. Phys. 115(5), 054512 (2014)CrossRefGoogle Scholar
  39. 39.
  40. 40.
    Luisier, M.: A parallel implementation of electron-phonon scattering in nanoelectronic devices up to 95k cores. In: 2010 International conference for high performance computing, networking, storage and analysis (SC), pp. 1–11. (2010)Google Scholar
  41. 41.
    Thurber, W. R.: The relationship between resistivity and dopant density for phosphorus-and boron-doped silicon, 400(64). US Department of Commerce, National Bureau of Standards, (1981)Google Scholar
  42. 42.
    Learning and research in the cloud” Published online 07 November 2013, Nature Nanotechnology, 8, 786–789 (2013). doi: 10.1038/nnano.2013.231
  43. 43. cloud-based services for nanoscale modeling, simulation, and education, Nanotechnology Reviews, 2(1), 107–117 (2013). doi: 10.1515/ntrev-2012-0043. ISSN (Online) 2191-9097, ISSN (Print) 2191-9089
  44. 44.

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • James Charles
    • 1
    • 2
  • Prasad Sarangapani
    • 1
    • 2
  • Roksana Golizadeh-Mojarad
    • 3
  • Robert Andrawis
    • 1
  • Daniel Lemus
    • 1
    • 2
  • Xinchen Guo
    • 1
    • 2
  • Daniel Mejia
    • 1
    • 2
  • James E. Fonseca
    • 2
  • Michael Povolotskyi
    • 2
  • Tillmann Kubis
    • 2
  • Gerhard Klimeck
    • 1
    • 2
  1. 1.School of Electrical and Computer EngineeringPurdue UniversityWest LafayetteUSA
  2. 2.Network for Computational NanotechnologyPurdue UniversityWest LafayetteUSA
  3. 3.Intel CorporationSanta ClaraUSA

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