2007 NSTI Nanotechnology Conference and Trade Show - Nanotech 2007 - 10th Annual

Advanced Nanoscale Simulation: Atoms, Materials and Devices

Sunday May 20, 2007, 8:00 am - 6:00 pm, Santa Clara, California

Core Challenges on the Nanoscale

Nanostructured materials are defined as materials with a constituent dimension less than 100nm (0,0001mm) in at least one dimension.

Characterization

nanoscale simulation tools For traditional materials, the microstructure that can be seen under a conventional light microscope and the composition, i.e. the weight fractions of the different elements in the mixture, determine their properties.

For nanostructured materials, the exact composition, i.e. what atomic species are present, and configuration, i.e. where the atoms and sometimes even electrons are exactly located on the atomic scale, determine the materials properties. Examples include the exact contact structure between leads and molecules in molecular electronic devices.

Conventional tools, such as light microscopy, X-ray diffraction, and mass spectrometry, cannot deliver such information. Combinations of atomic-level modeling and atomic-resolution characterization by analytical electron microscopy have shown the most promise in this area so far.

Fabrication - Process Modeling

For traditional materials, average properties, such as concentrations in continuum, or phase-field modeling, and equilibrium thermodynamics, using phase diagrams and diffusivity properites, are sufficient to model the evolution of a material during processing.

For nanostructured materials, single atoms need to be traced during the processing to predict the final structure and its properties. However, traditional atomic-level techniques, such as molecular dynamics, are only capable of following a few atoms reliably for times on the order of nanoseconds, i.e. not long enough for most processing steps.

The recent development of new techniques such as transition-state-theory based methods, accelerated dynamics, such as “Hyper-MD”, and physics-based Monte Carlo methods, get around this problem and enable nanoscale process modeling.

Structure-Property Relationships

polyerm structure, length ordering and side groups For traditional materials, the properties are determined by their microstructure and composition. The structure-property relationships are in many cases still poorly understood from a fundamental point of view, but a vast body of experience and theory exists how to change the structure to improve the properties.

For nanostructured materials, the structure-property relationships can only be found on the atomic level and with no background experience to indicate what to expect. An example is the scaling relationship between physical dimensions and electron transport in nanoelectronics devices which strongly differs from those of conventional devices.

The theory that is currently being developed is less heuristic and more fundamental than for traditional materials. This opens the chance of designing and understanding materials more reliably with the help of computer simulations.

Materials Design

For traditional materials, revolutionary new materials are in most cases discovered by accident. Most of the “design” work is spent on incremental improvement of known types of materials by, e.g., by alloying it with various amounts of impurities.

For nanostructured materials, computational design of hypothetical new materials is possible, including the study of stability and prediction of properties. In combination with a mature materials synthesis facility, completely new materials can be virtually designed and fabricated.

Electron Transport on the Nano-Scale

nano and molecular electronics Traditional transport models for semiconductor devices treat electrons and holes as classical particles or a classical carrier gas. A vast software resource exists for the modeling of semiconductor devices using such classical approaches.

As the device lengths decrease down to the nanometer scale, the boundaries between device and material become blurry. Quantum mechanical effects of the underlying material structure dominate device characteristics. Quantum mechanical treatments for carrier transport and materials need to be married. This is the domain where materials science meets device engineering.

Technology Focus

Besides exciting novel capabilities and opportunities, nanostructured materials pose a number of challenges that were not present in the field of traditional materials science. Whereas trial-and-error engineering was a successful approach for most of the traditional materials development, this is difficult in the field of nanoscale materials, where fundamental understanding on the atomic level is required for successful materials design. In this context, computer modeling poses incredible new chances to support new materials development for targeted design and fast time-to-market products.

Course Content

micro nano lithography and semiconductor processing This is an intermediate level course suitable for anyone interested in computational materials design of nanoelectronics devices.

We will introduce the area of simulation techniques and tools on the nanoscale level and discuss applications and approaches with focus on advanced materials design and nanoscale engineering for nanoelectronics devices. We will address core areas of nanoscale computation, including computer-assisted characterization, nanoscale process modeling, and structure-property relationships for properties such as conductance, which governs electron transport. We will also discuss methods for ‘computational alchemy’, which means computational design of new materials with sets of desired properties.

Hands-on Case Studies

Hands-on case studies will be part of the course. Detailed step-by-step instructions and all necessary software will be provided.

To participate, please bring a laptop with Microsoft Windows operating system.

Course Objectives

On completion of the course, you will be

  • Familiar with the challenges in the design of nanostructured materials and of nanoelectronics devices 
  • Able to assess the role that materials computation can play to meet these challenges 
  • Familiar with strategies, methods, and programs for such computations and the availability of appropriate software 
  • Familiar with successful applications of nanoscale simulation tools and how they can serve as templates for your applications 

Course Outline

Nanoscale Modeling

  • What Makes a Material ‘nano’? 
  • The Role of Surfaces and Interfaces 
  • Importance of Modeling for Nanomaterials 
  • Nanoscale Challenges for Modeling and Simulation 

Review of Single-scale Nanoscale Simulation and Modeling Methods

  • Classical Molecular Dynamics Simulations 
  • Electronic-structure Methods with Focus on Ab-Initio Calculations 
  • Monte Carlo Simulations 
  • Mesoscopic Methods 
  • Continuum Methods 

Case Studies: Simulating Simple Nano-systems 

Characterization

  • Concept of Simulation-assisted Nanoscale Characterization
  • Candidate-structure Selection
  • Simulation Methods to extract atomic-scale Information - from not necessarily atomic-resolution - experimental techniques such as TEM images, EELS and XPS spectra, or Raman and infrared spectra

Case Studies: Nanoelectronics Devices

Fabrication - Process modeling

  • Concept of Nanoscale Process Modeling 
  • Multiscale and Atomic-scale Process Modeling
  • Ab-initio to Continuum
  • Ab-initio to Monte Carlo 
  • Accelerated Dynamics Methods 

Case Studies: Molecular Electronics and Nanoelectronics Devices 

Structure-Property Relationships in Nanoelectronic Devices

  • Concept of Nanoscale Property Simulation: 
    - Calculation of spatially resolved band structures 
    - Identification of traps and charged defects
    - Electron transport from electronic structure calculations 

Case Studies: Nanoelectronics Devices — CNT transistors and others 

Materials Design

  • Concept of ‘Computational Alchemy’
  • Free Energies as Measure of Stability
  • Property Calculations: Mechanical, electronic, and optical 
  • Optimization Techniques to find materials with the optimum properties 

Case Studies: Computer-assisted Materials Design 

Course Instructors

Wolfgang Windl

Wolfgang Windl, Ph.D., Associate Professor at the Ohio State University, Columbus, USA. Professor Windl works in the area of Nanoscale Computational Materials Science. His field of expertise is in the area of atomistic simulations, especially within density-functional theory. Currently, he works on nanostructured interfaces and molecule-surface interactions of semiconductor device systems. Previously, he spent four years with Motorola, first as Senior Staff Scientist in Motorola's Computational Materials Group at Los Alamos National Laboratory, and later as a Principal Staff Scientist in the Digital DNA Laboratories in Austin, Texas, where he was working in the area of multiscale modeling of semiconductor processing. Before that, he held postdoctoral positions at Los Alamos National Laboratory and Arizona State University. He received his diploma and doctoral degree in physics from the University of Regensburg, Germany. Wolfgang Windl is on the editorial board of the Journal of Computational Electronics and the Journal of Theoretical and Computational Nanoscience. Among others, he has been Chairman of the International Conference on Computational Nanoscience (www.nsti.org) and is recipient of 1998 and 1999 Patent and Licensing Awards from Los Alamos National Laboratory for his contributions to the molecular modeling code CLSMAN. He has given more than 30 invited talks at international conferences and research institutions and has been awarded twice the “Best Teacher” recognition of the Department of Materials Science and Engineering at The Ohio State University.

 
 

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