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Variational Methods in Molecular Modeling

  • Jianzhong Wu

Part of the Molecular Modeling and Simulation book series (MMAS)

About this book

Introduction

This book presents tutorial overviews for many applications of variational methods to molecular modeling. Topics discussed include the Gibbs-Bogoliubov-Feynman variational principle, square-gradient models, classical density functional theories, self-consistent-field theories, phase-field methods, Ginzburg-Landau and Helfrich-type phenomenological models, dynamical density functional theory, and variational Monte Carlo methods. Illustrative examples are given to facilitate understanding of the basic concepts and quantitative prediction of the properties and rich behavior of diverse many-body systems ranging from inhomogeneous fluids, electrolytes and ionic liquids in micropores, colloidal dispersions, liquid crystals, polymer blends, lipid membranes, microemulsions, magnetic materials and high-temperature superconductors. 

All chapters are written by leading experts in the field and illustrated with tutorial examples for their practical applications to specific subjects. With emphasis placed on physical understanding rather than on rigorous mathematical derivations, the content is accessible to graduate students and researchers in the broad areas of materials science and engineering, chemistry, chemical and biomolecular engineering, applied mathematics, condensed-matter physics, without specific training in theoretical physics or calculus of variations.

Keywords

Classical DFT Field Theories Inhomogeneous Fluids Phase Transitions Statistical Mechanics Thermodynamics

Editors and affiliations

  • Jianzhong Wu
    • 1
  1. 1.Department of Chemical and Environmental Engineering and Department of MathematicsUniversity of CaliforniaRiversideUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-10-2502-0
  • Copyright Information Springer Science+Business Media Singapore 2017
  • Publisher Name Springer, Singapore
  • eBook Packages Engineering
  • Print ISBN 978-981-10-2500-6
  • Online ISBN 978-981-10-2502-0
  • Series Print ISSN 2364-5083
  • Series Online ISSN 2364-5091
  • Buy this book on publisher's site
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