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Multimillion Atom Simulations with Nemo3D

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Abbreviations

Nanostructures:

Nanostructures have at least two physical dimensions of size less than 100 nm. Their size lies between atomic/molecular and microscopic structures/particles. Realistically sized nanostructures are usually composed of millions of atoms. These devices demonstrate new capabilities and functionalities where the quantum nature of charge carriers plays an important role in determining the overall device properties and performance.

Quantum dots:

Quantum dots (QDs) are solid-state nanostructures that provide confinement of charge carriers (electrons, holes, excitons) in all three spatial dimensions typically on the nanometer scale. This work focuses on semiconductor based quantum dots.

Atomistic simulation:

For device sizes in the range of tens of nanometers, the atomistic granularity of constituent materials cannot be neglected. Effects of atomistic strain, surface roughness, unintentional doping, the underlying crystal symmetries, or distortions of the crystal lattice can have a dramatic impact on the device operation and performance. In an atomistic simulation, one takes into account both the atomistic/granular and quantum properties of the underlying nanostructure.

Strain:

Strain is the deformation caused by the action of stress on a physical body. In nanoelectronic devices, strain typically originates from the assembly of lattice‐mismatched semiconductors. Strain can be atomistically inhomogeneous and a small mechanical distortion of 2–5% can strongly modify the energy spectrum, in particular the optical bandgap, of the system by 30–100%.

Band structure:

Band structure of a solid originates from the wave nature of particles and depicts the allowed and forbidden energy states of electrons in the material. The knowledge of the band structure is the first and essential step towards the understanding of the device operation and reliable device design for semiconductor devices. Bandstructure is based on the assumption of an infinitely extended (bulk) material without spatial fluctuations (outside a simple repeated unit cell). For nanometer scale devices with spatial variations on the atomic scale the traditional concept of bandstructure is called into question.

Piezoelectricity:

A variety of advanced materials of interest, such as GaAs, InAs, GaN, are piezoelectric. Piezoelectricity arises due to charge imbalances on the bonds between atoms. Modifications of the bond angles or distances result in alterations in charge imbalance. Any spatial non‐symmetric distortion/strain in nanostructures made of these materials will create piezoelectric fields, which may significantly modify the electrostatic potential landscape.

Tight binding:

Tight binding is an empirical model that enables calculation of single‐particle energies and wave functions in a solid. The essential idea is the representation of the electronic states of the valence electrons with a local basis that contains the critical physical elements needed. The basis may contain orthogonal s, p, d orbitals on one atom that connect/talk to orbitals of a neighboring atom. The connection between atoms and the resulting overlapping wavefunctions form the bandstructure of a solid.

NEMO 3-D:

NEMO 3-D stands for NanoElectronic Modeling in three dimensions. This versatile, open source software package currently allows calculating single‐particle electronic states and optical response of various semiconductor structures including bulk materials, quantum dots, impurities, quantum wires, quantum wells and nanocrystals.

nanoHUB:

The nanoHUB is a rich, web-based resource for research, education and collaboration in nanotechnology (www.nanoHUB.org). It was created by the NSF‐funded Network for Computational Nanotechnology (NCN) with a vision to pioneer the development of nanotechnology from science to manufacturing through innovative theory, exploratory simulation, and novel cyberinfrastructure. The nanoHUB offers online nanotechnology simulation tools which one can freely access from his/her web browser.

Rappture:

Rappture (www.rappture.org) is a software toolkit that supports and enables the rapid development of graphical user interfaces (GUIs) for different applications. It is developed by Network for Computational Nanotechnology at Purdue University, West Lafayette.

Bibliography

Primary Literature

  1. Agnello PD (2002) Process requirements for continued scaling of CMOS—the need and prospects for atomic‐level manipulation. IBM J Res Dev 46:317–338

    Google Scholar 

  2. Ahmed S, Usman M, Heitzinger C, Rahman R, Schliwa A, Klimeck G (2007) Atomistic simulation of non‐degeneracy and optical polarization anisotropy in zincblende quantum dots. In: 2nd Annual IEEE International Conference on Nano/Micro Engineered and Molecular Systems (IEEE-NEMS), Bangkok, Thailand

    Google Scholar 

  3. Arakawa Y, Sasaki H (1982) Multidimensional quantum well laser and temperature dependence of its threshold current. Appl Phys Lett 40:939

    ADS  Google Scholar 

  4. Bae H, Clark S, Haley B, Klimeck G, Korkusinski M, Lee S, Naumov M, Ryu H, Saied F (2007) Electronic structure computations of quantum dots with a billion degrees of freedom. Supercomputing 07, Reno, NV, USA

    Google Scholar 

  5. Bester G, Wu X, Vanderbilt D, Zunger A (2006) Importance of second‐order piezoelectric effects in zinc‐blende semiconductors. Phys Rev Lett 96:187602

    ADS  Google Scholar 

  6. Bester G, Zunger A (2005) Cylindrically shaped zinc‐blende semiconductor quantum dots do not have cylindrical symmetry: Atomistic symmetry, atomic relaxation, and piezoelectric effects. Phys Rev B 71:045318. Also see references therein

    ADS  Google Scholar 

  7. Bowen R, Klimeck G, Lake R, Frensley W, Moise T (1997) Quantitative resonant tunneling diode simulation. J Appl Phys 81:207

    Google Scholar 

  8. Boykin T, Bowen R, Klimeck G (2001) Electromagnetic coupling and gauge invariance in the empirical tight‐binding method. Phys Rev B 63:245314

    ADS  Google Scholar 

  9. Boykin T, Kharche N, Klimeck G (2007) Brillouin zone unfolding of perfect supercells composed of non‐equivalent primitive cells. Phys Rev B 76:035310

    ADS  Google Scholar 

  10. Boykin T, Kharche N, Klimeck G, Korkusinski M (2007) Approximate bandstructures of semiconductor alloys from tight‐binding supercell calculations. J Phys: Condens Matter 19:036203

    ADS  Google Scholar 

  11. Boykin T, Klimeck G (2005) Practical application of zone‐folding concepts in tight‐binding. Phys Rev B 71:115215

    ADS  Google Scholar 

  12. Boykin T, Klimeck G, Bowen R, Oyafuso F (2002) Diagonal parameter shifts due to nearest‐neighbor displacements in empirical tight‐binding theory. Phys Rev B 66:125207

    ADS  Google Scholar 

  13. Boykin T, Klimeck G, Oyafuso F (2004) Valence band effective mass expressions in the sp3d5s\( { ^{\ast} } \) empirical tight‐binding model applied to a new Si and Ge parameterization. Phys Rev B 69:115201

    ADS  Google Scholar 

  14. Boykin T, Klimeck G, Eriksson M, Friesen M, Coppersmith S, Allmen P, Oyafuso F, Lee S (2004) Valley splitting in strained Si quantum wells. Appl Phys Lett 84:115

    ADS  Google Scholar 

  15. Boykin T, Klimeck G, Eriksson M, Friesen M, Coppersmith S, Allmen P, Oyafuso F, Lee S (2004) Valley splitting in low‐density quantum‐confined heterostructures studied using tight‐binding models. Phys Rev B 70:165325

    ADS  Google Scholar 

  16. Boykin T, Klimeck G, Allmen P, Lee S, Oyafuso F (2005) Valley‐splitting in V‑shaped quantum wells. J Appl Phys 97:113702

    ADS  Google Scholar 

  17. Boykin T, Luisier M, Schenk A, Kharche N, Klimeck G (2007) The electronic structure and transmission characteristics of disordered AlGaAs nanowires. IEEE Trans Nanotechnology 6:43

    ADS  Google Scholar 

  18. Boykin T, Vogl P (2001) Dielectric response of molecules in empirical tight‐binding theory. Phys Rev B 65:035202

    ADS  Google Scholar 

  19. Bradbury F et al (2006) Stark tuning of donor electron spins in silicon. Phys Rev Lett 97:176404

    ADS  Google Scholar 

  20. Calder`on MJ, Koiler B, Hu X, Das Sarma S (2006) Quantum control of donor electrons at the Si-SiO2 interface. Phys Rev Lett 96:096802

    ADS  Google Scholar 

  21. Canning A, Wang LW, Williamson A, Zunger A (2000) Parallel empirical pseudopotential electronic structure calculations for million atom systems. J Comp Phys 160:29

    MathSciNet  ADS  MATH  Google Scholar 

  22. Chen P, Piermarocchi C, Sham L (2001) Control of exciton dynamics in nanodots for quantum operations. Phys Rev Lett 87:067401

    ADS  Google Scholar 

  23. Colinge JP (2004) Multipole‐gate SOI MOSFETs. Solid-State Elect 48:897–905

    ADS  Google Scholar 

  24. Cui Y, Lauhon L, Gudiksen M, Wang J, Lieber C (2001) Diameter-controlled synthesis of single-crystal silicon nanowire. Appl Phys Lett 78:2214

    ADS  Google Scholar 

  25. Debernardi A et al (2006) Computation of the Stark effect in P impurity states in silicon. Phys Rev B 74:035202

    ADS  Google Scholar 

  26. Dobers M, Klitzing K, Schneider J, Weimann G, Ploog K (1998) Electrical detection of nuclear magnetic resonance in GaAs-Al x Ga1−x As heterostructures. Phys Rev Lett 61:1650

    ADS  Google Scholar 

  27. Eriksson M, Friesen M, Coppersmith S, Joynt R, Klein L, Slinker K, Tahan C, Mooney P, Chu J, Koester S (2004) Spin-based quantum dot quantum computing in Silicon. Quantum Inf Process 3:133

    MATH  Google Scholar 

  28. Fafard S, Hinzer K, Raymond S, Dion M, Mccaffrey J, Feng Y, Charbonneau S (1996) Red‐emitting semiconductor quantum dot lasers. Science 22:1350

    ADS  Google Scholar 

  29. Friesen M et al (2005) Theory of the Stark effect for P donors in Si. Phys Rev Lett 94:186403

    ADS  Google Scholar 

  30. Friesen M, Rugheimer P, Savage D, Lagally M, van der Weide D, Joynt R, Eriksson M (2003) Practical design and simulation of silicon-based quantum-dot qubits. Phys Rev B 67:121301

    ADS  Google Scholar 

  31. Goswami S, Slinker KA, Friesen M, McGuire LM, Truitt JL, Tahan C, Klein LJ, Chu JO, Mooney PM, van der Weide DW, Joynt R, Coppersmith SN, Eriksson MA (2007) Controllable valley splitting in silicon quantum devices. Nat Phys 3:41

    Google Scholar 

  32. Graf M, Vogl P (1995) Electromagnetic fields and dielectric response in empirical tight‐binding theory. Phys Rev B 51:4940

    ADS  Google Scholar 

  33. Greentree A, Cole J, Hamilton A, Hollenberg L (2004) Coherent electronic transfer in quantum dot systems using adiabatic passage. Phys Rev B 70:235317

    ADS  Google Scholar 

  34. Greytak A, Lauhon L, Gudiksen M, Lieber C (2004) Growth and transport properties of complementary germanium nanowire field-effect transistors. Appl Phys Lett 84:4176

    ADS  Google Scholar 

  35. Grundmann M, Stier O, Bimberg D (1995) InAs/GaAs pyramidal quantum dots: Strain distribution, optical phonons, and electronic structure. Phys Rev B 52:11969

    ADS  Google Scholar 

  36. Hollenberg L et al (2004) Charge-based quantum computing using single donors in semiconductors. Phys Rev B 69:113301

    MathSciNet  ADS  Google Scholar 

  37. Hollenberg L et al (2006) Two-dimensional architectures for donor-based quantum computing. Phys Rev B 74:045311

    ADS  Google Scholar 

  38. Klimeck G, Mannino M, McLennan M, Qiao W, Wang X (2008) https://www.nanohub.org/simulation_tools/qdot_tool_information

  39. Hu X et al (2005) Charge qubits in semiconductor quantum computer architecture: Tunnel coupling and decoherence. Phys Rev B 71:235332

    ADS  Google Scholar 

  40. Jancu J, Scholz R, Beltram F, Bassani F (1998) Empirical spds* tight‐binding calculation for cubic semiconductors: General method and material parameters. Phys Rev B 57:6493

    ADS  Google Scholar 

  41. Kane B (1998) A silicon‐based nuclear spin quantum computer. Nature 393:133

    ADS  Google Scholar 

  42. Keating P (1966) Effect of invariance requirements on the elastic strain energy of crystals with application to the diamond structure. Phys Rev :145

    Google Scholar 

  43. Kharche N, Luisier M, Boykin T, Klimeck G (2008) Electronic structure and transmission characteristics of SiGe nanowire. J Comput Electron 7:350; Klimeck G, Ahmed S, Bae H, Kharche N, Clark S, Haley B, Lee S, Naumov M, Ryu H, Saied F, Prada M, Korkusinski M, Boykin T (2007) Atomistic simulation of realistically sized nanodevices using NEMO 3-D: Part I – Models and benchmarks. IEEE Trans Electron Devices 54:2079; Klimeck G, Ahmed S, Kharche N, Korkusinski M, Usman M, Prada M, Boykin T (2007) Atomistic simulation of realistically sized nanodevices using NEMO 3-D: Part II – Applications. IEEE Trans Electron Devices 54:2090

    Google Scholar 

  44. Kharche N, Prada M, Boykin T, Klimeck G (2007) Valley‐splitting in strained silicon quantum wells modeled with 2 degree miscuts, step disorder, and alloy disorder. Appl Phys Lett 90:092109

    ADS  Google Scholar 

  45. Kim C, Yang J, Lee H, Jang H, Joa M, Park W, Kim Z, Maeng S (2007) Fabrication of Si1−x Ge x alloy nanowire field-effect transistors. Appl Phys Lett 91:033104

    ADS  Google Scholar 

  46. Klimeck G, Boykin T, Chris R, Lake R, Blanks D, Moise T, Kao Y, Frensley W (1997) Quantitative simulation of strained InP-based resonant tunneling diodes. In: Proceedings of the 1997 55th IEEE Device Research Conference Digest:92

    Google Scholar 

  47. Klimeck G, Bowen R, Boykin T, Cwik T (2000) sp3s\( { ^{\ast} } \) tight‐binding parameters for transport simulations in compound semiconductors. Superlattices Microstruct 27:519–524

    ADS  Google Scholar 

  48. Klimeck G, Bowen R, Boykin T, Salazar-Lazaro C, Cwik T, Stoica A (2000) Si tight‐binding parameters from genetic algorithm fitting. Superlattices Microstruct 27:77–88

    ADS  Google Scholar 

  49. Klimeck G, Oyafuso F, Boykin T, Bowen R, Allman P (2002) Development of a nanoelectronic 3‑D (NEMO 3‑D) simulator for multimillion atom simulations and its application to alloyed quantum dots. Comput Model Eng Sci 3:601

    MATH  Google Scholar 

  50. Klimeck G, Boykin T, Luisier M, Kharche N, Schenk A (2006) A Study of alloyed nanowires from two perspectives: approximate dispersion diagrams and transmission coefficients. In: Proceedings of the 28th International Conference on the Physics of Semiconductors ICPS 2006, Vienna, Austria

    Google Scholar 

  51. Kohn W, Luttinger J (1995) Theory of donor states in silicon. Phys Rev 98:915

    ADS  Google Scholar 

  52. Koiller B, Hu X, Das Sarma S (2006) Electric-field driven donor-based charge qubits in semiconductors. Phys Rev B 73:045319

    ADS  Google Scholar 

  53. Korkusinski M, Klimeck G (2006) Atomistic simulations of long-range strain and spatial asymmetry molecular states of seven quantum dots. J Phys Conf Ser 38:75–78

    ADS  Google Scholar 

  54. Korkusinski M, Klimeck G, Xu H, Lee S, Goasguen S, Saied F (2005) Atomistic simulations in nanostructures composed of tens of millions of atoms: Importance of long-range strain effects in quantum dots. Proceedings of 2005 NSTI Conference, Anaheim, CA

    Google Scholar 

  55. Korkusinski M, Saied F, Xu H, Lee S, Sayeed M, Goasguen S, Klimeck G (2005) Large scale simulations in nanostructures with NEMO 3‑D on linux clusters. In: Linux Cluster Institute Conference, Raleigh, NC

    Google Scholar 

  56. Lanczos C (1950) An iteration method for the solution of the eigenvalue problem of linear differential and integral operators. J Res Natl Bur Stand 45

    Google Scholar 

  57. Lansbergen GP, Rahman R, Wellard CJ, Woo I, Caro J, Collaert N, Biesemans S, Klimeck G, Hollenberg LCL, Rogge S (2008) Gate induced quantum confinement transition of a single dopant atom in a Si FinFET. Nature Phys 4:656

    Google Scholar 

  58. Lazarenkova O, Allmen P, Oyafuso F, Lee S, Klimeck G (2004) Effect of anharmonicity of the strain energy on band offsets in semiconductor nanostructures. Appl Phys Lett 85:4193

    ADS  Google Scholar 

  59. Lee S, Kim J, Jönsson L, Wilkins J, Bryant G, Klimeck G (2002) Many-body levels of multiply charged and laser‐excited InAs nanocrystals modeled by empirical tight binding. Phys Rev B 66:235307

    Google Scholar 

  60. Lee S, Lazarenkova O, Oyafuso F, Allmen P, Klimeck G (2004) Effect of wetting layers on the strain and electronic structure of InAs self‐assembled quantum dots. Phys Rev B 70:125307

    ADS  Google Scholar 

  61. Lee S, Oyafuso F, Allmen P, Klimeck G (2004) Boundary conditions for the electronic structure of finite‐extent, embedded semiconductor nanostructures with empirical tight‐binding model. Phys Rev B 69:045316

    ADS  Google Scholar 

  62. Liang G, Xiang J, Kharche N, Klimeck G, Lieber C, Lundstrom M (2006) Performance analysis of a Ge/Si core/shell nanowire field effect transistor. cond-mat 0611226

    Google Scholar 

  63. Loss D, DiVincenzo DP (1998) Quantum computation with quantum dots. Phys Rev A 57:120

    ADS  Google Scholar 

  64. Luisier M, Schenk A, Fichtner W, Klimeck G (2006) Atomistic simulation of nanowires in the sp\( { ^{3}d^{5}s^{\ast} } \) tight‐binding formalism: From boundary conditions to strain calculations. Phys Rev B 74:205323

    ADS  Google Scholar 

  65. Martins A et al (2004) Electric-field control and adiabatic evolution of shallow donor impurities in silicon. Phys Rev B 69:085320

    ADS  Google Scholar 

  66. Maschhoff K, Sorensen D (1996) A portable implementation of ARPACK for distributed memory parallel architectures. Copper Mountain Conference on Iterative Methods, Copper Mountain, 9–13 April 1996

    Google Scholar 

  67. Maximov M, Shernyakov Y, Tsatsul’nikov A, Lunev A, Sakharov A, Ustinov V, Egorov A, Zhukov A, Kovsch A, Kop’ev P, Asryan L, Alferov Z, Ledentsov N, Bimberg D, Kosogov A, Werner P (1998) High-power continuous‐wave operation of a InGaAs/AlGaAs quantum dot laser. J Appl Phys 83:5561

    Google Scholar 

  68. Michler P, Kiraz A, Becher C, Schoenfeld W, Petroff P, Zhang L, Hu E, Imamoglu A (2000) A quantum dot single‐photon turnstile device. Science 290:2282–2285

    ADS  Google Scholar 

  69. Moore G (1975) Progress in digital integrated electronics. IEDM Tech Digest, pp 11–13

    Google Scholar 

  70. Moreau E, Robert I, Manin L, Thierry-Mieg V, Gérard J, Abram I (2001) Quantum cascade of photons in semiconductor quantum dots. Phys Rev Lett 87:183601

    Google Scholar 

  71. Naumov M, Lee S, Haley B, Bae H, Clark S, Rahman R, Ryu H, Saied F, Klimeck G (2007) Eigenvalue solvers for atomistic simulations of electronic structureswith NEMO-3D. 12th International Workshop on Computational Electronics, Amherst, USA, 7–10 Oct 2007

    Google Scholar 

  72. Oberhuber R, Zandler G, Vogl P (1998) Subband structure and mobility of two–dimensional holes in strained Si/SiGe MOSFET’s. Phys Rev B 58:9941–9948

    ADS  Google Scholar 

  73. Open Science Grid at http://www.opensciencegrid.org

  74. Oyafuso F, Klimeck G, Allmen P, Boykin T, Bowen R (2003) Strain effects in large-scale atomistic quantum dot simulations. Phys Stat Sol (b) 239:71

    ADS  Google Scholar 

  75. Oyafuso F, Klimeck G, Bowen R, Boykin T, Allmen P (2003) Disorder induced broadening in multimillion atom alloyed quantum dot systems. Phys Stat Sol (c) 4:1149

    Google Scholar 

  76. Persson A, Larsson M, Steinström S, Ohlsson B, Samuelson L, Wallenberg L (2004) Solid phase diffusion mechanism for GaAs NW growth. Nat Mater 3:677

    Google Scholar 

  77. Petroff PM (2003) Single quantum dots: Fundamentals, applications, and new concepts. Springer, Berlin

    Google Scholar 

  78. Prada M, Kharche N, Klimeck G (2007) Electronic structure of Si/InAs composite channels. In: MRS Spring conference, Symposium G: Extending Moore’s Law with Advanced Channel Materials, San Francisco, 9–13 April 2007

    Google Scholar 

  79. Pryor C, Kim J, Wang L, Williamson A, Zunger A (1998) Comparison of two methods for describing the strain profiles in quantum dots. J Apl Phys 83:2548

    ADS  Google Scholar 

  80. Qiao W, Mclennan M, Kennell R, Ebert D, Klimeck G (2006) Hub-based simulation and graphics hardware accelerated visualization for nanotechnology applications. IEEE Trans Vis Comput Graph 12:1061–1068

    Google Scholar 

  81. Rahman A, Klimeck G, Lundstrom M (2005) Novel channel materials for ballistic nanoscale MOSFETs bandstructure effects. In: 2005 IEEE International Electron Devices Meeting, Washington, DC 601-604

    Google Scholar 

  82. Rahman R et al (2007) High precision quantum control of single donor spins in silicon. Phys Rev Lett 99:036403

    ADS  Google Scholar 

  83. Ramdas A et al (1981) Spectroscopy of the solid-state analogues of the hydrogen atom: donors and acceptors in semiconductors. Rep Prog Phys 44

    Google Scholar 

  84. Reed M (1993) Quantum dots. Sci Am 268:118

    ADS  Google Scholar 

  85. Reed M, Randall J, Aggarwal R, Matyi R, Moore T, Wetsel A (1988) Observation of discrete electronic states in a zero‐dimensional semiconductor nanostructure. Phys Rev Lett 60:535

    ADS  Google Scholar 

  86. Sameh A, Tong Z (2000) The trace minimization method for the symmetric generalized eigenvalue problem. J Comp Appl Math 123:155–175

    MathSciNet  ADS  MATH  Google Scholar 

  87. Sellier H et al (2006) Transport spectroscopy of a single dopant in a gated silicon nanowire. Phys Rev Lett 97:206805

    ADS  Google Scholar 

  88. Semiconductor Industry Association (2001) International technology roadmap for semiconductors. (http://public.itrs.net/Files/2001ITRS/Home.htm)

  89. Slater J, Koster G (1954) Simplified LCAO method for the periodic potential problem. Phys Rev 94:1498–1524

    ADS  MATH  Google Scholar 

  90. Slater J, Koster G (1954) Simplified LCAO method for the periodic potential problem. Phys Rev 94:1498

    ADS  MATH  Google Scholar 

  91. Stegner A et al (2006) Electrical detection of coherent P spin quantum states. Nat Phys 2:835

    Google Scholar 

  92. Stier O, Grundmann M, Bimberg D (1999) Electronic and optical properties of strained quantum dots modeled by 8-band \( { k.p } \) theory. Phys Rev B 59:5688

    ADS  Google Scholar 

  93. Sze S, May G (2003) Fundamentals of semiconductor fabrication. John Wiley

    Google Scholar 

  94. TeraGrid at http://www.teragrid.org

  95. Usman M, Ahmed S, Korkusinski M, Heitzinger C, Klimeck G (2006) Strain and electronic structure interactions in realistically scaled quantum dot stacks. In: Proceedings of the 28th International Conference on the Physics of Semiconductors ICPS 2006, Vienna, Austria

    Google Scholar 

  96. Vasileska D, Khan H, Ahmed S (2005) Quantum and Coulomb effects in nanodevices. Int J Nanosci 4:305–361

    Google Scholar 

  97. Vrijen R et al (2000) Electron-spin-resonance transistors for quantum computing in silicon-germanium heterostructures. Phys Rev A 62:012306

    ADS  Google Scholar 

  98. Wang J, Rahman A, Ghosh A, Klimeck G, Lundstrom M (2005) Performance evaluation of ballistic silicon nanowire transistors with atomic‐basis dispersion relations. Appl Phys Lett 86:093113

    ADS  Google Scholar 

  99. Wang L, Zunger A (1994) Solving Schrödinger’s equation around a desired energy: Application to silicon quantum dots. J Chem Phys 100:2394

    ADS  Google Scholar 

  100. Wellard C, Hollenberg L (2005) Donor electron wave functions for phosphorus in silicon: Beyond effective-mass theory. Phys Rev B 72:085202

    ADS  Google Scholar 

  101. Williamson A, Wang L, Zunger A (2000) Theoretical interpretation of the experimental electronic structure of lens‐shaped self‐assembled InAs/GaAs quantum dots. Phys Rev B 62:12963–12977

    ADS  Google Scholar 

  102. Welser J, Hoyt J, Gibbons J (1992) NMOS and PMOS transistors fabricated in strained silicon/relaxed silicon‐germanium structures. IEDM Tech Dig, pp 1000–1002

    Google Scholar 

  103. Wong HS (2002) Beyond the conventional transistor. IBM J Res Dev 46:133–168

    Google Scholar 

  104. http://www.intel.com/cd/software/products/asmo-na/eng/307757.htm

  105. Zandviet H, Elswijk H (1993) Morphology of monatomic step edges on vicinal Si(001). Phys Rev B 48:14269

    ADS  Google Scholar 

  106. Zheng Y, Rivas C, Lake R, Alam K, Boykin T, Klimeck G (2005) Electronic properties of Silicon nanowires. IEEE Tran Elec Dev 52:1097–1103

    ADS  Google Scholar 

  107. Zhirnov VV, Cavin III R K, Hutchby JA, Bourianoff GI (2003) Limits to binary logic switch–a Gedanken model. Proc IEEE 91:1934–1939

    Google Scholar 

  108. Zhu W, Han JP, Ma T (2004) Mobility measurement and degradation mechanisms of MOSFETs made with ultrathin high-k dielectrics. IEEE Trans Electron Dev 51:98–105

    ADS  Google Scholar 

Books and Reviews

  1. Bimberg D, Grundmann M, Ledentsov N (1999) Quantum dot heterostructures. Wiley

    Google Scholar 

  2. Datta S (2005) Quantum transport: Atom to transistor. Cambridge University Press

    Google Scholar 

  3. Harrison P (2005) Quantum wells, wires and dots: Theoretical and computational physics of semiconductor nanostructures, 2nd edn. Wiley-Interscience

    Google Scholar 

Download references

Acknowledgments

The work has been supported by the Indiana 21st Century Fund, Army Research Office, Office of NavalResearch, Semiconductor Research Corporation, ARDA, the National Science Foundation. The work described in this publication was carried out in part at theJet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeronautics and Space Administration. Thedevelopment of the NEMO 3‑D tool involved a large number of individuals at JPL and Purdue, whose work has been cited. Drs. R. Chris Bowen,Fabiano Oyafuso, and Seungwon Lee were key contributors in this large effort at JPL. The authors acknowledge an NSF Teragrid award DMR070032. Access tothe Bluegene was made available through the auspices of the Computational Center for Nanotechnology Innovations (CCNI) at Rensselaer PolytechnicInstitute. Access to the Oak Ridge National Lab XT3/4 was provided by the National Center for Computational Sciences project. We would also like to thankthe Rosen Center for Advanced Computing at Purdue for their support. nanoHUB computational resources were used for part of this work.

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Authors and Affiliations

  1. School of Electrical and Computer Engineering and Network for Computational Nanotechnology, Purdue University, West Lafayette, USA

    Shaikh Ahmed*, Neerav Kharche*, Rajib Rahman*, Muhammad Usman*, Sunhee Lee*, Hoon Ryu, Hansang Bae, Benjamin Haley & Gerhard Klimeck

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

    Shaikh Ahmed*

  3. Rosen Center for Advanced Computing, Purdue University, West Lafayette, USA

    Steve Clark, Faisal Saied, Rick Kennel & Michael McLennan

  4. Department of Computer Science, Purdue University, West Lafayette, USA

    Maxim Naumov

  5. Institute for Microstructural Sciences, National Research Council of Canada, Ottawa, Canada

    Marek Korkusinski

  6. Electrical and Computer Engineering Dept., The University of Alabama, Huntsville, USA

    Timothy B. Boykin

  7. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA

    Gerhard Klimeck

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  1. RAMTECH LIMITED, 122 Escalle Lane, Larkspur, CA, 94939, USA

    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

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© 2009 Springer-Verlag

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Ahmed*, S. et al. (2009). Multimillion Atom Simulations with Nemo3D. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_343

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