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Applied Computational Materials Modeling

Theory, Simulation and Experiment

  • Book
  • © 2007

Overview

Editors:
  1. Guillermo Bozzolo

    1. Ohio Aerospace Institute, Cleveland, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Ronadl D. Noebe

    1. NASA Glenn Research Center, Cleveland, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Phillip B. Abel

    1. NASA Glenn Research Center, Cleveland, USA

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  4. D.R. Vij
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  • Computational materials modeling is presented as a set of tools available for aiding the materials engineer/scientist
  • Each chapter describes one or more particular computational tool and how they are best used
  • Provides detailed examples of application to real problems
  • Suggests how to acquire the programs (tools) if the software is publicly available
  • Focuses on the integration of the modeling methods within experimental programs
  • Includes supplementary material: sn.pub/extras

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xvi
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  2. Ab initio modeling of alloy phase equilibria

    • Axel van de Walle, Gautam Ghosh, Mark Asta
    Pages 1-34

  3. Use of computational thermodynamics to identify potential alloy compositions for metallic glass formation

    • Y. Austin Chang
    Pages 35-53

  4. How does a crystal grow? Experiments, models and simulations from the nano- to the micro-scale regime

    • J. L. Rodríguez-López, J. M. Montejano-Carrizales, M. José-Yacamán
    Pages 55-84

  5. Structural and electronic properties from first-principles

    • X. Q. Wang
    Pages 85-108

  6. Synergy between material, surface science experiments and simulations

    • C. Creemers, S. Helfensteyn, J. Luyten, M. Schurmans
    Pages 109-169

  7. Integration of first-principles calculations, calphad modeling, and phase-field simulations

    • Zi-Kui Liu, Long-Qing Chen
    Pages 171-213

  8. Quantum approximate methods for the atomistic modeling of multicomponent alloys

    • Guillermo Bozzolo, Jorge Garcés, Hugo Mosca, Pablo Gargano, Ronald D. Noebe, Phillip Abel
    Pages 215-254

  9. Molecular orbital approach to alloy design

    • Masahiko Morinaga, Yoshinori Murata, Hiroshi Yukawa
    Pages 255-306

  10. Application of computational and experimental techniques in intelligent design of age-hardenable aluminum alloys

    • Aiwu Zhu, Gary J. Shiflet, Edgar A. Starke Jr.
    Pages 307-342

  11. Multiscale modeling of intergranular fracture in metals

    • Vesselin Yamakov, Dawn R. Phillips, Erik Saether, Edward H. Glaessgen
    Pages 343-367

  12. Multiscale modeling of deformation and fracture in metallic materials

    • Diana Farkas, Jeffrey M. Rickman
    Pages 369-390

  13. Frontiers in surface analysis: Experiments and modeling

    • Daniel Farías, Guillermo Bozzolo, Jorge Garcés, Rodolfo Miranda
    Pages 391-414

  14. The evolution of composition and structure at metal-metal interfaces: Measurements and simulations

    • Richard J. Smith
    Pages 415-449

  15. Modeling of low enrichment uranium fuels for research and test reactors

    • Jorge Garcés, Guillermo Bozzolo, Jeffrey Rest, Gerard Hofman
    Pages 451-483

  16. Back Matter

    Pages 485-491
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Keywords

About this book

While it is tempting to label computational materials modeling as an emerging field of research, the truth is that both in nature and foundation, it is just as much an established field as the concepts and techniques that define it. It is the recent enormous growth in computing power and communications that has brought the activity to the forefi-ont, turning it into a possible com­ ponent of any modem materials research program. Together with its increased role and visibility, there is also a dynamic change in the way computational modeling is perceived in such a vast field as materials science with its wide range of length and time scales. As the pace of materials research accelerates and the need for often inaccessible information continues to grow, the de­ mands and expectations on existing modeling techniques have progressed that much faster. Primarily because there is no one technique that can provide all the answers at every length and time scale in materials science, excessive expectations of computational materials modeling should be avoided if pos­ sible. While it is apparent that computational modeling is the most efficient method for dealing with complex systems, it should not be seen as an alter­ native to traditional experimentation. Instead there is another option, which is perhaps the one that is most likely to become the defining characteristic of computational materials modeling.

Editors and Affiliations

  • Ohio Aerospace Institute, Cleveland, USA

    Guillermo Bozzolo

  • NASA Glenn Research Center, Cleveland, USA

    Ronadl D. Noebe, Phillip B. Abel

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