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Fragmentation: Toward Accurate Calculations on Complex Molecular Systems


Fragmentation: Toward Accurate Calculations on Complex Molecular Systems


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von: Mark S. Gordon

129,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 04.08.2017
ISBN/EAN: 9781119129264
Sprache: englisch
Anzahl Seiten: 376

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Beschreibungen

Fragmentation: Toward Accurate Calculations on Complex Molecular Systems introduces the reader to the broad array of fragmentation and embedding methods that are currently available or under development to facilitate accurate calculations on large, complex systems such as proteins, polymers, liquids and nanoparticles. These methods work by subdividing a system into subunits, called fragments or subsystems or domains. Calculations are performed on each fragment and then the results are combined to predict properties for the whole system. Topics covered include: Fragmentation methods Embedding methods Explicitly correlated local electron correlation methods Fragment molecular orbital method Methods for treating large molecules This book is aimed at academic researchers who are interested in computational chemistry, computational biology, computational materials science and related fields, as well as graduate students in these fields.
List of Contributors   xi Preface    xv 1 Explicitly Correlated Local Electron Correlation Methods       1Hans-Joachim Werner, Christoph Koppl, Qianli Ma, and Max Schwilk 1.1 Introduction 1 1.2 Benchmark Systems 3 1.3 Orbital-Invariant MP2 Theory 6 1.4 Principles of Local Correlation 9 1.5 Orbital Localization 10 1.6 Local Virtual Orbitals 12 1.7 Choice of Domains 24 1.8 Approximations for Distant Pairs 26 1.9 Local Coupled-Cluster Methods (LCCSD) 33 1.10 Triple Excitations 41 1.11 Local Explicitly Correlated Methods 41 1.12 Technical Aspects 53 1.13 Comparison of Local Correlation and Fragment Methods 57 1.14 Summary 60 Appendix A: The LCCSD Equations 63 Appendix B: Derivation of the Interaction Matrices 65 References  67 2 Density and Potential Functional Embedding: Theory and Practice  81 Kuang Yu, Caroline M. Krauter, Johannes M. Dieterich, and Emily A. Carter 2.1 Introduction  81 2.2 Theoretical Background 82 2.3 Density Functional Embedding Theory  84 2.4 Potential Functional Embedding Theory   101  2.5 Summary and Outlook 109 Acknowledgments 111 References  111 3 Modeling and Visualization for the Fragment Molecular Orbital Method with the Graphical User Interface FU, and Analyses of Protein–Ligand Binding    119 Dmitri G. Fedorov and Kazuo Kitaura 3.1 Introduction  119 3.2 Overview of FMO 120 3.3 Methodology  120 3.4 GUI Development 128 3.5 Conclusions 136 Acknowledgments 137 References 137 4 Molecules-in-Molecules Fragment-Based Method for the Accurate Evaluation of Vibrational and Chiroptical Spectra for Large Molecules  141K. V. Jovan Jose and Krishnan Raghavachari 4.1 Introduction 141 4.2 Computational Methods and Theory 142 4.3 Results and Discussion 146 4.4 Summary 157 4.5 Conclusions 158 Acknowledgments 159 References 159 5 E?ective Fragment Molecular Orbital Method     165Casper Steinmann and Jan H. Jensen 5.1 Introduction 165 5.2 E?ective Fragment Molecular Orbital Method 168 5.3 Summary and Future Developments 180 References  180 6 E?ective Fragment Potential Method: Past, Present, and Future  183Lyudmila V. Slipchenko and Pradeep K. Gurunathan 6.1 Overview of the EFP Method  183 6.2 Milestones in the Development of the EFP Method  185 6.3 Present: Chemistry at Interfaces and Photobiology 192 6.4 Future Directions and Outlook 202 References  203 7 Nucleation Using the E?ective Fragment Potential and Two-Level Parallelism    209Ajitha Devarajan, Alexander Gaenko, Mark S. Gordon, and Theresa L. Windus 7.1 Introduction  209 7.2 Methods   211 7.3 Results   217 7.4 Conclusions  223 Acknowledgments 223 References  224 8 Five Years of Density Matrix Embedding Theory  227Sebastian Wouters, Carlos A. Jime´nez-Hoyos, and Garnet K.L. Chan 8.1 Quantum Entanglement 227 8.2 Density Matrix Embedding Theory 228 8.3 Bath Orbitals from a Slater Determinant  230 8.4 The Embedding Hamiltonian 232 8.5 Self-Consistency  234 8.6 Green’s Functions  236 8.7 Overview of the Literature  237 8.8 The One-Band Hubbard Model on the Square Lattice  237 8.9 Dissociation of a Linear Hydrogen Chain 240 8.10 Summary  240 Acknowledgments 241 References  241 9 Ab initio Ice, Dry Ice, and Liquid Water     245So Hirata, Kandis Gilliard, Xiao He, Murat Kec¸eli, Jinjin Li, Michael A. Salim, Olaseni Sode, and Kiyoshi Yagi 9.1 Introduction 245 9.2 Computational Method 247 9.3 Case Studies 256 9.4 Concluding Remarks 284 9.5 Disclaimer 284 Acknowledgments 284 References 285 10 A Linear-Scaling Divide-and-Conquer Quantum Chemical Method for Open-Shell Systems and Excited States      297Takeshi Yoshikawa and Hiromi Nakai 10.1 Introduction 297 10.2 Theories for the Divide-and-Conquer Method 298 10.3 Assessment of the Divide-and-Conquer Method 307 10.4 Conclusion  318 References  319 11 MFCC-Based Fragmentation Methods for Biomolecules        323Jinfeng Liu, Tong Zhu, Xiao He, and John Z. H. Zhang 11.1 Introduction 323 11.2 Theory and Applications 324 11.3 Conclusion 345 Acknowledgments 346 References 346 Index 349
Edited by MARK S. GORDON, Department of Chemistry, Iowa State University, Ames, USA
Fragmentation: Toward Accurate Calculations on Complex Molecular Systems introduces the reader to the broad array of fragmentation and embedding methods that are currently available or under development to facilitate accurate calculations on large, complex systems such as proteins, polymers, liquids and nanoparticles. These methods work by subdividing a system into subunits, called fragments or subsystems or domains. Calculations are performed on each fragment and then the results are combined to predict properties for the whole system. Topics covered include: Fragmentation methods Embedding methods Explicitly correlated local electron correlation methods Fragment molecular orbital method Methods for treating large molecules This book is aimed at academic researchers who are interested in computational chemistry, computational biology, computational materials science and related fields, as well as graduate students in these fields.

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