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Iowa State University, USA
This edition first published 2017
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Library of Congress Cataloging-in-Publication Data
Names: Gordon, M. S. (Mark S.), editor.
Title: Fragmentation : toward accurate calculations on complex molecular systems / edited by Professor Mark S. Gordon, Iowa State University, USA.
Description: Chichester, UK ; Hoboken, NJ : John Wiley & Sons, Inc., 2017. | Includes bibliographical references and index.
Identifiers: LCCN 2016057161 (print) | LCCN 2016058050 (ebook) | ISBN 9781119129240 (cloth) | ISBN 9781119129257 (pdf) | ISBN 9781119129264 (epub)
Subjects: LCSH: Fragmentation reactions. | Electron configuration.
Classification: LCC QD281.F7 F738 2017 (print) | LCC QD281.F7 (ebook) | DDC 547/.128--dc23
LC record available at https://lccn.loc.gov/2016057161
A catalogue record for this book is available from the British Library.
Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books.
Cover Design: Wiley
Cover Images: (Background) © Esebene/Gettyimages; (Inset Images) Courtesy of the editor
School of Engineering and Applied Science, Princeton University, USA
Frick Chemistry Laboratory, Department of Chemistry, Princeton University, USA
Office of University Development, University of Michigan, USA
Department of Mechanical and Aerospace Engineering, Princeton University, USA
Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Advanced Research Computing, University of Michigan, USA
Department of Chemistry, University of Illinois at Urbana–Champaign, USA
Ames Laboratory of United States Department of Energy, USA
Department of Chemistry, Iowa State University, USA
Department of Chemistry, Purdue University, USA
School of Chemistry and Molecular Engineering, East China Normal University, China
NYU-ECNU Center for Computational Chemistry, NYU Shanghai, China
Department of Chemistry, University of Illinois at Urbana–Champaign, USA
Department of Chemistry, University of Copenhagen, Denmark
Frick Chemistry Laboratory, Department of Chemistry, Princeton University, USA
Department of Chemistry, Indiana University, USA
Department of Chemistry, University of Illinois at Urbana–Champaign, USA
Argonne National Laboratory, USA
Graduate School of System Informatics, Kobe University, Japan
Institute for Theoretical Chemistry, University of Stuttgart, Germany
Department of Mechanical and Aerospace Engineering, Princeton University, USA
Department of Chemistry, University of Illinois at Urbana–Champaign, USA
National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/Nano Electronics, Shanghai Jiao Tong University, China
School of Chemistry and Molecular Engineering, East China Normal University, China
Institute for Theoretical Chemistry, University of Stuttgart, Germany
Department of Chemistry and Biochemistry, School of Advanced Science and Engineering, Waseda University, Japan
Department of Chemistry, Indiana University, USA
Department of Chemistry, University of Illinois at Urbana–Champaign, USA
Institute for Theoretical Chemistry, University of Stuttgart, Germany
Department of Chemistry, Purdue University, USA
Department of Chemistry, University of Illinois at Urbana–Champaign, USA
Department of Chemistry, Biochemistry, and Physics, The University of Tampa, USA
Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Denmark
Institute for Theoretical Chemistry, University of Stuttgart, Germany
Ames Laboratory of United States Department of Energy, USA
Department of Chemistry, Iowa State University, USA
Center for Molecular Modelling, Ghent University, Belgium
Frick Chemistry Laboratory, Department of Chemistry, Princeton University, USA
Department of Chemistry, University of Illinois at Urbana–Champaign, USA
Theoretical Molecular Science Laboratory, RIKEN, Japan
Department of Chemistry and Biochemistry, School of Advanced Science and Engineering, Waseda University, Japan
Department of Mechanical and Aerospace Engineering, Princeton University, USA
School of Chemistry and Molecular Engineering, East China Normal University, China
NYU-ECNU Center for Computational Chemistry, NYU Shanghai, China
Department of Chemistry, New York University, USA
School of Chemistry and Molecular Engineering, East China Normal University, China
NYU-ECNU Center for Computational Chemistry, NYU Shanghai, China
Electronic structure theory, also referred to as ab initio quantum chemistry (QC), has attained a high level of maturity and reliability for gas-phase molecules of modest size. Unfortunately, the formal scaling of these methods such as Hartree–Fock (HF), density functional theory (DFT), second-order perturbation theory (MP2), coupled cluster theory (CC), and multi-reference (MR) methods hinder their application to large molecules, to condensed phase systems or to excited electronic state potential energy surfaces. These limitations are especially severe for methods that account for electron correlation, such as MP2, CC, and MR methods, since their scaling with system size is steeper than for the simpler HF and DFT methods. There is therefore a need for computational strategies that nearly retain the accuracy of the most reliable methods while greatly reducing the scaling of these methods as a function of system size. While researchers who are interested in simulations of large molecular systems have often turned to classical molecular mechanics (MM) force fields, MM methods are limited in their applicability. While there are a few exceptions, classical MM cannot realistically treat bond making/bond breaking (the essence of chemistry) or excited state phenomena.
One effective QC approach that has become increasingly popular is referred to as fragmentation (broadly defined) or embedding theory. Fragmentation commonly refers to the physical subdivision of a large molecule into fragments, each of whose energy can be computed on a different compute node, thereby making the overall computation highly parallel. Fragmentation methods of this type scale nearly linearly with system size and can take advantage of massively parallel computers. Fragmentation methods of this type are discussed in Chapters 3, 5, 6, 7, 10, and 11. An alternative approach to physical fragmentation of a molecule is to fragment the wave function, by employing localized molecular orbitals to separate the wave function into domains that can be separately correlated. This approach is based on the fact that electron correlation is short-range. Chapter 1 provides an excellent discussion of local electron correlation methods by one of the leaders in the field.
Embedding methods are similar to fragmentation methods in that a total system is partitioned into multiple subsystems, in a manner that allows the incorporation of interactions among the subsystems. Like fragmentation and local orbital approaches, embedding methods reduce the steep scaling of traditional electronic structure methods. Embedding methods frequently involve multiple levels of theory. Approaches to embedding methods are discussed in Chapters 2, 4, 8, and 9.
The methods that are discussed in this book provide an exciting path forward to the accurate study of large molecules and condensed phase phenomena.