Chemical Modelling: Applications and Theory, Volume 10 (Specialist Periodical Reports, Band 10) - Hardcover

Hardcover

ISBN 10: 1849735867 ISBN 13: 9781849735865

Verlag: ROYAL SOCIETY OF CHEMISTRY, 2013

Inhaltsangabe

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.

The tenth volume of the series brings Jan Ole Joswig to the editorial team, and a wealth of new reviews spanning several disciplines. For example, materials scientists will benefit from the review on Inverse Molecular Design for Materials and Modelling PAHs will be of interest to environmental scientists. Other reviews have detailed focus on modelling, such as Reaction Kinetics and Accurate Modelling of Electric Properties of Polyatomic molecules from the first principles.

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.

Über diesen Titel

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.

The tenth volume of the series brings Jan Ole Joswig to the editorial team, and a wealth of new reviews spanning several disciplines. For example, materials scientists will benefit from the review on Inverse Molecular Design for Materials and Modelling PAHs will be of interest to environmental scientists. Other reviews have detailed focus on modelling, such as Reaction Kinetics and Accurate Modelling of Electric Properties of Polyatomic molecules from the first principles.

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 10

A Review of Recent Literature

By J-O Joswig, M. Springborg

The Royal Society of Chemistry

Copyright © 2014 The Royal Society of Chemistry
All rights reserved.

ISBN: 978-1-84973-586-5

Contents

Preface Michael Springborg and Jan-Ole Joswig, v, 
Inverse molecular design for materials discovery Dequan Xiao, Ingolf Warnke, Jason Bedford and Victor S. Batista, 1, 
Complete basis set results in electron correlation methods using F12 theory Andreas Köhn, 32, 
Reactive intermediates with large amplitude degrees of freedom Rex T. Skodje, 64, 
Modelling electron quantum dynamics in large molecular systems Diego A. Hoff and Luis G. C. Rego, 102, 
Modelling polycyclic aromatic hydrocarbons and their derivatives Mathias Rapacioli, 127, 
Surface reactivity of the sulfide minerals Guilherme Ferreira de Lima, Heitor Avelino de Abreu and Hélio Anderson Duarte, 153, 
Electric dipole moments of small polyatomic molecules from first principles Sergei N. Yurchenko, 183, 

CHAPTER 1

Inverse molecular design for materials discovery

Dequan Xiao, Ingolf Warnke, Jason Bedford and Victor S. Batista

DOI: 10.1039/9781849737241-00001

1 Introduction

Discovering materials with optimum properties is a long-term dream for both experimental and theoretical researchers. Historically, scientists used an approach of 'trial and error' to find new materials that exhibit desired properties. Owing to the development in modern theoretical and computational chemistry (e.g., density functional theory), predicting molecular properties using accurate and efficient quantum chemistry methods becomes more and more practical. As a consequence, inverse molecular design has emerged as an attractive computational approach to take on the challenges in materials discovery.

Inverse molecular design is a general term describing strategies in molecular design, that are in contrast to direct design methods. In direct design, a new molecule is proposed first, and then the molecular property is computed or measured to check its potential use. In contrast, inverse molecular design aims at searching for optimum points on hypersurfaces defining property-structure relationships, and then mapping out the molecular structures at the optimum points. Hence, using the idea of inverse molecular design could significantly enhance the efficiency and success rate of molecular design and save costs in materials discovery.

Inverse molecular design has been implemented as an optimization method in theory, assisting the search for optimum chemical structures using global optimization algorithms.

[MATHEMATICAL EXPRESSION OMITTED] (1)

Here, finv is a notation for the operation of inverse molecular design. Ô denotes a molecular property (an observable), which is a functional of the Hamiltonian operator H. λ1, λ2, ..., λn are the set of user-defined variables for varying the Hamiltonian. For example, these variables could be the indices defining a molecule as a composition of molecular fragments, a set of nuclear coordinates, or even atomic numbers.

OT denotes a given target value of a molecular property, e.g. a maximum point of the molecular property. The minimization operation 'min' may be performed through a variety of different optimization algorithms that minimize the quantity |Ô[H[λ1, λ2, ...,] - OT]|. Thus, [Florin]inv aims at finding a particular set {λ1, λ2, ... λn} (and thereby a molecular structure) that has the best match to the target molecular property. This is a general formulation for the idea of inverse molecular design. When applied to specific systems, the formulation may be transformed for the purpose of optimizing particular target molecular properties.

In this work, we focus on reviewing inverse molecular design based on hypersurfaces of molecular properties vs. molecular structures that are constructed through direct calculations of molecular properties from variable Hamiltonians (for representing different chemical structures). Alternatively, analogous hypersurfaces relating property and structure have been constructed based on statistical models for molecular properties with respect to sets of chosen molecular descriptors (for molecular structures or properties). Such hypersurfaces are used extensively for the inverse design based on quantitive structure activity relationship (QSAR). We refer interested readers to literature on inverse QSAR, which is not the focus of this review.

In molecular structure space, the Hamiltonian variables are associated with the atom types and their spatial arrangement. Different stochastic and deterministic optimization algorithms have been adapted to work in inverse molecular design methods. The choice of an optimization method depends on how the particular Hamiltonian, linking structure and property, is varied during a search (i.e. depends on the set of Hamiltonian parameters/variables that are varied).

We begin with reviewing optimization algorithms that are based on discrete molecular objects such as genetic algorithms and Monte Carlo methods. Then, we describe an emerging approach named linear combination of atomic potentials (LCAP) developed by Beratan and Yang for inverse molecular design. This approach allows us to search for optimum molecules using continuous or discrete optimization algorithms. In particular, we will review recent progress made in applying LCAP in the tight-binding (TB) framework, which could provide an efficient way for molecule search. Finally, we review applications of TB-LCAP for optimizing non-linear optical materials and dye-sensitized solar cells. In particular, novel materials have been proposed by TB-LCAP and verified by experiments. Due to the low computational cost of tight-binding electronic structure calculations, we envision that the TB-LCAP will be a promising inverse molecular design method for taking on challenges in materials discovery such as catalysts design and solar fuels applications.

2 Strategies in inverse molecular design

Genetic algorithms and Monte Carlo methods are commonly used as optimizers for inverse molecular design in discrete molecular structure space of chemically representable candidates.

2.1 Genetic algorithms

Genetic algorithms are methods tailored to address complicated multi-dimensional optimization problems. They belong to a broader class of evolutionary algorithms which originated in the 60s and 70s when scientists started to explore the possibility of using basic principles of evolution to develop adaptive and highly efficient and general optimization schemes. Nowadays, GAs find extensive use in a large variety of scientific fields. Notably, over the past 30 years, they have graduated to become a major tool for computational disciplines in physics, chemistry and materials science where they are used for atomistic and electronic structure level optimizations of molecular geometries, energies and properties.

In inverse molecular design, GAs may be applied as optimization algorithms to locate vectors X = {λ1, λ2, ... λn} such that |Ô|[H[λ1, λ2, ...,] - OT]| becomes minimal. In electronic structure calculations there is generally no simple relationship between X and the property of interest |Ô|[H[λ1, λ2, ...,] - OT]|. The calculation of these properties often is complicated and comes at high...

Details zur Ausgabe

• Verlag: ROYAL SOCIETY OF CHEMISTRY
• Erscheinungsdatum: 2013
• Sprache: Englisch
• ISBN 10: 1849735867
• ISBN 13: 9781849735865
• Einband: Gebundene Ausgabe
• Anzahl der Seiten: 238
• Herausgeber: Springborg Michael, Joswig Jan-Ole
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: Nicht verfügbar