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Computational Nanoscience
Applications for Molecules, Clusters, and Solids

£69.99

  • Date Published: April 2011
  • availability: In stock
  • format: Hardback
  • isbn: 9781107001701
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  • Computer simulation is an indispensable research tool in modeling, understanding and predicting nanoscale phenomena. However, the advanced computer codes used by researchers are too complicated for graduate students wanting to understand computer simulations of physical systems. This book gives students the tools to develop their own codes. Describing advanced algorithms, the book is ideal for students in computational physics, quantum mechanics, atomic and molecular physics, and condensed matter theory. It contains a wide variety of practical examples of varying complexity to help readers at all levels of experience. An algorithm library in Fortran 90, available online at www.cambridge.org/9781107001701, implements the advanced computational approaches described in the text to solve physical problems.

    • Gives students the tools needed to understand advanced computer codes and develop their own codes
    • Contains a wide variety of practical examples of varying complexity to help readers at all levels of experience
    • An algorithm library in Fortran 90, available at www.cambridge.org/9781107001701, gives readers the necessary software tools
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    Customer reviews

    06th Jul 2019 by Songzhigang

    very well this book. I love it. It solved my problem and teach me How to sovle numerical problem

    Review was not posted due to profanity

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    Product details

    • Date Published: April 2011
    • format: Hardback
    • isbn: 9781107001701
    • length: 444 pages
    • dimensions: 254 x 181 x 25 mm
    • weight: 1.01kg
    • contains: 175 b/w illus. 33 tables
    • availability: In stock
  • Table of Contents

    Preface
    Part I. 1D Problems:
    1. Variational solution of the Schrödinger equation
    2. Solution of bound state problems using a grid
    3. Solution of the Schrödinger equation for scattering states
    4. Periodic potentials: band structure in 1D
    5. Solution of time-dependent problems in quantum mechanics
    6. Solution of Poisson's equation
    Part II. 2D and 3D Systems:
    7. 3D real space approach: from quantum dots to Bose–Einstein condensates
    8. Variational calculations in 2D: quantum dots
    9. Variational calculations in 3D: atoms and molecules
    10. Monte Carlo calculations
    11. Molecular dynamics simulations
    12. Tight binding approach to electronic structure calculations
    13. Plane wave density functional calculations
    14. Density functional calculations with atomic orbitals
    15. Real-space density functional calculations
    16. Time-dependent density functional calculations
    17. Scattering and transport in nanostructures
    18. Numerical linear algebra
    Appendix: code descriptions
    References
    Index.

  • Resources for

    Computational Nanoscience

    Kálmán Varga, Joseph A. Driscoll

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    Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other lecturers may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.

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  • Instructors have used or reviewed this title for the following courses

    • Introduction to nanophysics; https://wiki.physics.udel.edu/phys824
    • Materials Research
    • Mathematical Methods of Theoretical Physics ll
    • Principles in Physical Chemistry: Theory to Experiment
  • Authors

    Kálmán Varga, Vanderbilt University, Tennessee
    Kálmán Varga is an Assistant Professor in the Department of Physics and Astronomy, Vanderbilt University. His main research interest is computational nanoscience, focusing on developing novel computational methods for electronic structure calculations.

    Joseph A. Driscoll, Bradley University, Illinois
    Joseph Driscoll has a PhD in Electrical Engineering from Vanderbilt University, where his research was in the area of intelligent robotics. He has worked in industry as a software developer in the areas of Internet content delivery and bioinformatics. He was an Assistant Professor of Computer Science at Middle Tennessee State University. Dr Driscoll also has a PhD in Physics, where his interests include theoretical and computational physics of nanoscale systems. In 2011 he moved to Bradley University, where he was first an Assistant Professor of Engineering Physics, and then became an Assistant Professor of Electrical and Computer Engineering. Dr Driscoll's primary research areas are intelligent robotics, high-performance computing, and MEMS/NEMS (micro/nano electromechanical system) device simulation. He works with neural networks, genetic algorithms, computer vision, and other forms of artificial intelligence. Many types of robots are used in his experiments, including flying, walking, and wheeled robots.

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