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Encyclopedia of Complexity and Systems Science pp 1–69Cite as

Multimillion Atom Simulation of Electronic and Optical Properties of Nanoscale Devices Using NEMO 3-D

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Definition of the Subject and Its Importance

The rapid progress in nanofabrication technologies has led to the emergence of new classes of nanodevices and structures which are expected to bring about fundamental and revolutionary changes in electronic, photonic, computation, information processing, biotechnology, and medical industries. At the atomic scale of novel nanostructured semiconductors, the distinction between new device and new material is blurred, and device physics and material science meet. The quantum mechanical effects in the electronic states of the device and the granular, atomistic representation of the underlying material become important. Modeling and simulation approaches based on a continuum representation of the underlying material typically used by device engineers and physicists become invalid. Typical ab initio methods used by material scientists do not represent the bandgaps and masses precisely enough for device design or they do not scale to realistically...

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Abbreviations

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.

Bandstructure:

Bandstructure 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 bandstructure is the first and essential step toward 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.

nanoHUB:

The nanoHUB is a rich, Web-based resource for research, education, and collaboration in nanotechnology (http://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.

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.

NEMO 3D:

NEMO 3D 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.

Piezoelectricity:

A variety of advanced materials of interest, such as GaAs, InAs, and 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 nonsymmetric distortion/strain in nanostructures made of these materials will create piezoelectric fields, which may significantly modify the electrostatic potential landscape.

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.

Rappture:

Rappture (http://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 the Network for Computational Nanotechnology at Purdue University, West Lafayette.

Spontaneous (pyroelectric) polarization:

The intrinsic asymmetry of the bonding in the equilibrium (unstrained) crystal structure leads to a spontaneous polarization in wurtzite III-N structures even in the absence of external electrical fields. Spontaneous polarization is strain independent and results in a built-in potential that, in many nitride nanostructures, becomes comparable to the piezoelectric counterpart.

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 %.

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, and d orbitals on one atom that connect/talk to orbitals of a neighboring atom. The connection between atoms and the resulting overlapping wave functions form the bandstructure of a solid.

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Acknowledgment

The work has been supported by the Indiana 21st Century Fund, Army Research Office, Office of Naval Research, Semiconductor Research Corporation, ARDA, and the National Science Foundation. The work described in this publication was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The development of the NEMO 3D 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. Shaikh Ahmed acknowledges NSF Grant Nos. CCF-1218839 and EECS-1102192. Access to the Blue Gene was made available through the auspices of the Computational Center for Nanotechnology Innovations (CCNI) at Rensselaer Polytechnic Institute. Access to the Oak Ridge National Lab XT3/4 was provided by the National Center for Computational Sciences project. We would also like to thank the Rosen Center for Advanced Computing at Purdue for their support. NanoHUB computational resources were used for part of this work.

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    1. School of Electrical and Computer Engineering and Network for Computational Nanotechnology, Purdue University, West Lafayette, IN, 47907, USA

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

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

      Shaikh Ahmed

    3. Rosen Center for Advanced Computing, Purdue University, West Lafayette, IN, 47907, USA

      Steve Clark, Faisal Saied, Rick Kennel & Michael McLennan

    4. Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA

      Maxim Naumov

    5. Institute for Microstructural Sciences, National Research Council of Canada, 1200 Montreal Road, Ottawa, ON, K1A 0R6, Canada

      Marek Korkusinski

    6. Electrical and Computer Engineering Department, The University of Alabama in Huntsville, Huntsville, AL, 35899, USA

      Timothy B. Boykin

    7. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA

      Gerhard Klimeck

    8. School of Physics, University of Melbourne, Parkville, VIC, Australia

      Muhammad Usman

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    Ahmed, S. et al. (2015). Multimillion Atom Simulation of Electronic and Optical Properties of Nanoscale Devices Using NEMO 3-D. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27737-5_343-2

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