SKIP NAVIGATION    NATIONAL NANOTECHNOLOGY INFRASTRUCTURE NETWORK   
SEARCH:        
spacer
Logo: NNIN HOW TO START A PROJECT  Yellow square  REU  Yellow square  FAQs: GENERAL · TECHNICAL  Yellow square  MULTIMEDIA  Yellow square  EVENTS  Yellow square  ANNOUNCEMENTS  Yellow square  CONTACT   
Logo: NNIN
Logo: NNIN Molecule fade
Logo: NNIN
Logo: NNIN
yellow dot pattern

Computation and Simulation

 


NNIN offers a wide range of computational resources, primarily at the Harvard and Cornell nodes, as outlined below.

Additional complementary computation and simulation resources are available through the Network for Computational Nanotechnology, NCN, via the Nanohub. (opens in new window).

 

 

 

NNIN/C

The National Nanotechnology Infrastructure Network’s computational drive (NNIN/C) is a multi-university initiative, funded by the National Science Foundation (NSF) as part of NNIN, to establish a national computing resource for nanotechnology. This network is open to the academic and industrial research community and provides hardware resources and simulation tools dedicated to nanoscience research. Strong technical and scientific support is provided by staff experts so that the tools and resources can benefit interdisciplinary research. The software tools include commercial software packages for design, characterization and analysis of nanometer scale devices as well as some of the latest academic advances in nanoscale modeling and simulation software.

 

Unlike traditional sciences where immutable nature is the object of study and the goal is to uncover her underlying principles, nanoscience is a field of directed discovery requiring the fabrication of new systems and materials which fulfill sophisticated functions that answer to human needs. The object of nanoscience is not to make big things small and therefore easy to carry. Rather it is to permit control of the constituents of nature on their most elementary scale, be it for molecular sensing, photon manipulation, or the spin and space quantum states of a single electron, in order to reach unprecedented thresholds of coherence, speed and performance as well as to use the principles of matter at the nanoscale to create new functionalities.

                                                                                                                                                                       

Many of the features of nanoscale objects of invention and study cannot be predicted, designed or analyzed without computer modeling. The reasons for this are the following:

  • Nanoscale systems are necessarily multi-scale. Fabrication, measurement and operation of nano-devices entails connection to the macro-scale. The physics and chemistry throughout the range of dimensions can only be approached through computer modeling.
  • Nanoscale systems are inhomogeneous. Being neither periodic nor isolated, the equations which govern nanoscale systems and particularly the boundary conditions of those equations are almost always too complex for analytic theory. Computation is the only other choice.
  • Nanoscale systems are characterized by multiple degrees of freedom with overlapping energy scales. Electromagnetic, vibrational, quantum mechanical and configurational processes, to name a few of the most prominent, compete in nanoscale systems to determine their operation. Without computation these controlling phenomena become hopelessly entangled. 

 

Modeling of nanoscale systems is not only essential, it is essential for a variety of specific ends.  

  • Since the parameter space of a typical nano-system is so huge, design to specification requires computer modeling. Experimentalists cannot investigate proposed devices with an operational target through trial and error. Flexible, user-friendly computational tools with known ingredients but without the need for a comprehension of the guiding equations are prerequisite to successful fabrication.
  • Analysis of data is a primary function of computer modeling. It is also essential in the discovery of new phenomena that emerge from the complexity of interacting physical laws or which presage physical principles not incorporated in the models.
  • Inverse engineering is desirable in many nanoscale projects. Often it is known what output or performance is desired from a device but the configuration to produce that output is unknown. The sophisticated process of inverse engineering cycles a model of the system through its parameter space searching for specified output via artificial intelligence techniques such as the genetic algorithm. 

Goals of NNIN/C

NNIN/C is the computational initiative of the National Nanotechnology Infrastructure Network, an NSF-funded collaboration of 13 Nanotechnology Centers dedicated to providing state-of-the-art fabrication, characterization and simulation research tools to the broader nanoscience community. The goals of NNIN/C are:

  • Assemble a suite of robust software tools that address critical issues in the molecular and electronic structure and physical and chemical dynamics of artificial and natural nanoscale structures.
  • Maintain and, where necessary, modify simulations to address a widening scope of research problems.
  • Provide strong technical support and thorough instruction on the software tools so as to permit even novice users to progress rapidly to the solutions of their own research problems.
  • Provide web-based graphical user interfaces (GUIs) for user-friendly access to simulation tools as well as web-based resources for instruction and feedback.
  • Expand the code base by recruiting computational scientists to provide nanotechnology codes to the NNIN/C repository.

 

Are you a future NNIN community member ?

NNIN/C comprises a broad community that includes both users and contributors. In deciding whether joining the NNIN/C community is right for you, the appropriate questions to ask are:

  • Are you an experimentalist fabricating and measuring nanoscale devices where numerical simulations can optimize your output either by accelerating device design or analyzing results of measurement ?
  • Are you a theorist or computational specialist seeking to employ state-of-the-art simulations in nanoscience but lacking access either to the hardware or software ? Do you need help reducing the steep learning curve that some software packages present ? Do you have students who would profit and strengthen your group by learning new computational techniques ?
  • Are you a researcher interested in particular materials or device configurations for which currently available simulation tools do not exist?
  • Have you developed a specific code that you think could be of use to a community of researchers in the same field ? Would you be interested in accelerating the development of your code by expanding your developer and user base ? Are you interested in taking your code from a command line interface and working with Information Technology specialists to develop an easily accessible graphical user interface (GUI) for your software ?

If your answer to any of these questions is “yes,” then please contact us to begin a dialogue on how your research program can benefit from NNIN/C.

 

NNIN Workshops and Conferences

The NNIN/C is committed to providing events that help researchers explore the nanoscale regime.  This has taken the form of a series of workshops with tutorials and hands-on sessions and also conferences linking experiment and simulation at the nanoscale.  More information, including lectures and calculation examples can be found below:

 

Software Resources

Software packages hosted by NNIN/C include the following, which are available, installed, and supported by NNIN staff at the NNIN computation sites. Some licensing restrictions my apply to some users.
 

  • HARES (High performance fortran Adaptive grid Real space Electronic Structure) calculates atomic level electronic structure of crystals and small molecules using a real space, adaptive grid. [Waghmere et al., cond-mat/0006183].
  • Abinit- A plane wave pseudopotential first principles code.
  • EDIP (Environment Dependent Interatomic Potential) computes interatomic forces in covalent solids and liquids which incorporates recent theoretical advances in understanding the environment dependence of (sigma) chemical bonding in condensed phases. [N. A. Marks, Phys. Rev. B 63 035401 (2001), M. Bazant et al., Phys. Rev. B 56, 8542 (1997)].
  • SETE (Single Electron Tunneling Elements) calculates electronic structure, in the effective mass approximation, of two dimensional electron gas (2DEG) based heterostructures such as quantum dots and wires. [M. Stopa, Phys. Rev. B 54, 13767 (1996)].
  • LM Suite – Linear Muffin tin orbital software package does ASA and full potential calculations and can be used for fully non-equilibrium transport calculations using a Green’s function approach.
  • NWChem is a computational chemistry package that is designed to run on high-performance parallel supercomputers as well as conventional workstation clusters.
  • SEMC-2D (Schrödinger Equation Monte-Carlo) simulation for quantum transport and scattering in nanoscale non-classical CMOS employing non-equilibrium Green function techniques.
  • UTQUANT is a quasi-static CV simulator for one-dimensional silicon MOS structures.
  • ANEBA (Adaptive Nudged Elastic Band Approach) locates the saddle point in the potential energy surface between an initial and a final state in a physical transition process such as a chemical reaction or diffusion process.
  • MIT Photonic Bands (MPB)  Package to compute the band structure and electromagnetic modes of periodic dielectric structures.
  • MEEP This is an open source finite difference time domain (FDTD) simulation code developed at MIT.
  • UT-MARLOWE is a neutron transport simulator which models scattering, electronic stopping, and damage accumulation. [see: http://homer.mer.utexas.edu/utmarlowe ].
  • TOMCAT (TOpography based Monte CArlo Transport) is a general-purpose Monte Carlo simulator of particle transport in arbitrary 2-D structures.  The main application of TOMCAT is in the simulation of ion implantation.  For more info see http://homer.mer.utexas.edu/tomcat02/
  • CPMD (Carr-Parrinello Molecular Dynamics code) – is used to perform ab-initio molecular dynamics.  It allows for time-dependent DFT, wavefunction optimization, and path integral molecular dynamics.
  • PARSEC (Pseudopotential Algorithms for Real Space Energy Calculations) solves the atomistic electronic structure problem for using a real space approach.  This technique is ideal for modeling small clusters, molecules, and finite nanowires.
  • Quantum Espresso (also known as PWscf) This plane wave density functional code takes advantage of ultra-soft pseudopotentials to accelerate calculations.  In addition, it has the ability to handle magnetic nanostructures, calculate phonon dispersions, and perform structural relaxations.
  • Siesta - (Spanish Initiative for Electronic Simulations with Thousands of Atoms)  This code uses numerically truncated orbitals (single, double, and triple zeta approach) to build on order-N density functional functional code.  This code is ideal for modeling large scale nanostructures (i.e. nanotubes, nanowires, and clusters)
  • LAMMPS - general purpose molecular dynamics simulator that has the option to use leonard-jones potentials, embedded atom potentials, and potentials for biomolecules and proteins.  This parallel code can easily handle systems with thousands of atoms.  The ability to incorporate the effect of temperature is an important complement to density functional techniques.
  • Elmer - This multiphysics package allows you to model coupled problems using finite element techniques.  This could include current induced heating, vibrations in cantilevers, and fluid flow in microchannels.

Additionally, subject to licensing restrictions, NNIN will provide a series of commercial packages and mathematics libraries that include: Matlab, Femlab, ATLAS (self-optimizing LAPACK/BLAS), SILVACO, CADENCE (Electronic layout, modeling, synthesis tool), IntelliSuite (Mechanical modeling tool), Gnu scientific library, FFTW and Intel MKL libraries.

 

 

 

 

 

    • Hardware Resources

    • At Harvard University --NNIN users have access to the Crimson Cluster, comprised of 48 dual 32 bit Xeon blades (~3 GHz) each with 2 ½ GB of RAM with gigabit ethernet. P655 IBM Power 4 Plus processors, total of 20 processors with 80 GB RAM. 4 units of 4-way 32 GB Opterons from SUN Microsystems, total of 128 GB RAM. NNIN AMD Opteron cluster: 112 processors, 56 connected with Infiniband, 56 with gigabit ethernet.
    • At Cornell University – 52  node dual processor Xeon (3.06 GHz) cluster connected by gigabit Ethernet lines donated by Intel; Fifteen 64 Bit Opteron workstations.  The Opteron workstations were donated by AMD Corporation.
    • Code Acquisition: Matching Computation and Experiment

    • NNIN/C continually seeks to expand its suite of codes by recruiting computational scientists, particularly those engaged in research relevant to NNIN experimental initiatives, to contribute user-friendly versions of their calculations to the NNIN/C repository. Currently under acquisition:

    • Microfluidics: Immiscible Flow. Metin Muradoglu, ( Koc University, Istanbul). Computational model of interfacial flows in Micro/Biofluidic systems.
    • Quantum Monte-Carlo calculations John Shumway, ( Arizona State University). Path integral simulations of semiconductor nanostructures.
    • Casimir Force Computation. Martin Tajmar, Space Propulsion ARC Seibersdorf research, Austria. Finite-Element Simulation of Casimir Forces in Arbitrary Geometries.
    • Quantum Dynamics. Toshi Iitaka and Shintaro Nomura (RIKEN and Tskuba, resp.) Numerical Integration of the time-dependent Schrödinger equation by the explicit symmetric multistep scheme
  •  
     

Computational Advice and Support

Critical to NNIN's concept of a user facility is provision of adequate technical support to make the resources useful. This holds for both experimental and computational resources. There is a lot of scientific and technical expertise that is required to properly use the right computational code for the right problem in the right way.  This high level of technical support is provided, free of charge, to NNIN computational users through our computational technical liaisons. These include Dr. Michael Stopa stopa@deas.harvard.edu  of Harvard and  Dr. Derek Stewart  stewart@cnf.cornell.edu  of Cornell  They are published scientists with expertise in a variety of physical systems and computational resources. They can be an effective  part of your project.

 To get an idea of past projects and how our services may help you, please see the list of publications from the Cornell cluster. 

Information

For information on any NNIN computational resource or to find out more about starting a project, please contact  Dr. Michael Stopa stopa@deas.harvard.edu  or Dr. Derek Stewart  stewart@cnf.cornell.edu .  As with all NNIN resources, computational resources and support are available on an open basis to all users.

 

Last Revised 5/8/2008 Derek Stewart



blue dot pattern
spacer HOME · BACK TO THE TOP blue dot pattern
spacer
Logo: National Science Foundation


spacer