Chemical Modelling: Applications and Theory Volume 7 (Specialist Periodical Reports, Band 7) - Hardcover

Hardcover

ISBN 10: 1847550754 ISBN 13: 9781847550750

Verlag: Royal Society of Chemistry, 2010

Inhaltsangabe

Chemical Modelling: Applications and Theory comprises critical literature reviews of all aspects of molecular modelling. Molecular modelling in this context refers to modelliing the structure, properties and reactions of atoms, molecules and materials. Each chapter provides a selective review of recent literature, incorporating sufficient historical perspective for the non-specialist to gain an understanding. With chemical modelling covering such a wide range of subjects, this Specialist Periodical Report serves as the first port of call to any chemist, biochemist, materials scientist or molecular physicist needing to acquaint themselves with major developments in the area.

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Über die Autorin bzw. den Autor

Prof. Dr. Michael Springborg heads up of the three groups in Physical Chemistry at the University of Saarland where the main activities concentrate on teaching and research. The major part of Prof. Dr. Michael Springborg's research concentrates on the development and application of theoretical methods, including accompanying computer programs, for the determination of materials properties. Quantum theory forms the theoretical foundation for most of our work. The materials of the group's interest range from atoms, via clusters and polymers, to solids. They study their structural, electronic, energetic, and opitcal properties.

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Chemical Modelling: Applications and Theory comprises critical literature reviews of all aspects of molecular modelling. Molecular modelling in this context refers to modelling the structure, properties and reactions of atoms, molecules and materials. Each chapter provides a selective review of recent literature, incorporating sufficient historical perspective for the non-specialist to gain an understanding. With chemical modelling covering such a wide range of subjects, this Specialist Periodical Report serves as the first port of call to any chemist, biochemist, materials scientist or molecular physicist needing to acquaint themselves with major developments in the area.

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Chemical Modelling Applications and Theory Volume 7

A Review of the Literature Published Between June 2008 and December 2009

By M. Springborg

The Royal Society of Chemistry

Copyright © 2010 The Royal Society of Chemistry
All rights reserved.

ISBN: 978-1-84755-075-0

Contents

Preface Michael Springborg, v, 
Neural network potential-energy surfaces for atomistic simulations Jörg Behler, 1, 
X Polarizabilities and hyperpolarizabilities Benoît Champagne, 43, 
Protein folding Leonor Cruzeiro, 89, 
Orbital-dependent exact-exchange methods in density functional theory Fabio Della Sala, 115, 
Elongation method and its applications to NLO materials Feng Long Gu and Yuriko Aoki, 163, 
Modelling proton transport Jan-Ole Joswig, 193, 
Computer-aided drug design 2007–2009 Richard A. Lewis, 213, 
Electron structure quantum Monte Carlo Arne Lüchow and René Petz, 237, 
The properties of the P-stability and exponential fitting for the numerical solution of the Schrödinger equation Theodore E. Simos, 261, 

CHAPTER 1

Neural network potential-energy surfaces for atomistic simulations

Jörg Behler

DOI: 10.1039/9781849730884-00001

Studying chemical reactions in computer simulations requires a reliable description of the atomic interactions. While for systems of moderate size precise electronic structure calculations can be carried out to determine the energy and the forces, for large systems it is necessary to employ more efficient potentials. In past decades a huge number of such potentials has been developed for a variety of systems. Still, for the investigation of many chemical problems the accuracy of the available potentials is not yet satisfactory. In particular, chemical reactions at surfaces, strongly varying bonding patterns in materials science, and the complex reactivity of metal centers in coordination chemistry are prominent examples where most existing potentials are not sufficiently accurate. In recent years, a new class of interatomic potentials based on artificial neural networks has emerged. These potentials have a very flexible functional form and can therefore accurately adapt to a reference set of electronic structure energies. To date, neural network potentials have been constructed for a number of systems. They are promising candidates for future applications in large-scale molecular dynamics simulations, because they can be evaluated several orders of magnitude faster than the underlying electronic structure energies. However, further methodical developments are needed to reach this goal. In this review the current status of neural network potentials is summarized. Open problems and limitations of the hitherto proposed methods are discussed, and some possible solutions are presented.

1. Introduction

Molecular dynamics (MD) and Monte Carlo simulations have significantly contributed to the detailed understanding of a variety of chemical processes at the atomic level. However, the outcome of the simulations critically depends on the accuracy of the energies and atomic forces, i.e., on the quality of the underlying potential-energy surface (PES). The PES is defined as a high-dimensional function providing the potential-energy as a function of the atomic positions. Individual points on the PES can be calculated using a variety of quantum chemical methods like e.g. Hartree Fock theory, Møller Plesset perturbation theory or coupled cluster theory. However, these methods are computationally too demanding to be applicable in molecular simulations on a routine basis. The only first-principles electronic structure method, which is sufficiently fast to perform MD simulations "on-the-fly" for systems of moderate size is density-functional theory (DFT). In spite of some limitations of currently available approximate exchange-correlation functionals, the resulting "ab initio molecular dynamics" is without doubt the most accurate method to follow chemical reactions in complex systems dynamically without relying on the construction of intermediate PESs. Nevertheless, in many cases even the most efficient implementations of ab initio MD are computationally simply too expensive to be carried out on the currently available supercomputers, and this situtation is unlikely to change in the next decade. Additionally, it is a frustrating fact that in ab initio MD simulations a lot of time is spent on recalculating similar structures again and again, even if closely related atomic configurations have been visited before. Therefore, it would be desirable to collect and reuse the information about the PES gained in these simulations.

To extend the time and length scales of molecular simulations, a huge number of more efficient approximate potentials for various applications has been developed in the past decades. For very simple systems like diatomic molecules or weakly interacting noble gas atoms very accurate analytic forms can be constructed based on chemical knowledge and intuition. These potentials, e.g. the Lennard Jones potential or the Morse potential, depend only on a few parameters that can be determined from experiment or ab initio calculations. However, these simple pair potentials already fail for three-atomic systems, because usually the interactions between atoms are not pairwise additive.

The most basic approach to carry out MD simulations for larger systems is to use classical force fields. A variety of different force fields for molecular mechanics (MM) simulations has been developed, which are mainly intended to describe the non-reactive dynamics of large systems. In particular in the field of biochemistry force fields play an essential role to study the complex properties of large biomolecules. However, classical force fields require the specification of the connectivity of the atoms. Therefore, they are not able to describe chemical reactions, i.e., the making and breaking of bonds. To describe reactions, they can be combined with quantum mechanical (QM) methods in so-called QM/MM simulations. In recent years also "reactive force fields", e.g. ReaxFF, have been introduced, which overcome this limitation. However, these reactive force fields are typically highly adapted to specific systems by analytic terms customized to describe e.g. certain bonding situations, and only a few applications have been reported so far.

Mainly in the field of materials science various types of potentials have been developed based on the concept of the bond order. Like for reactive force fields also for the application of these potentials a specification of the atomic positions is sufficient. Although many of these potentials like the Tersoff potential, the Stillinger-Weber potential, the Brenner potential and many others have been introduced already one or two decades ago, they are still frequently used in materials simulations, in particular for semiconductors. For metallic systems the embedded atom method (EAM) and the modified embedded atom method (MEAM) introduced by Baskes and coworkers are widely distributed.

In parallel to these methods also a variety of simplified electronic structure methods like tight binding and semiempirical methods have been developed. Since these methods still contain essential parts of the underlying quantum mechanics, they usually provide a good transferability at the expense of larger computational costs.

In general, the construction of accurate potentials is a tedious task and can result in several months of "laborious iterative fitting". Once an acceptable...

Details zur Ausgabe

• Verlag: Royal Society of Chemistry
• Erscheinungsdatum: 2010
• Sprache: Englisch
• ISBN 10: 1847550754
• ISBN 13: 9781847550750
• Einband: Gebundene Ausgabe
• Anzahl der Seiten: 350
• Herausgeber: Springborg Michael
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: gpsr@libri.de; gpsr@libri.de; ; Friedensallee 273; Hamburg; 22763; Deutschland