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Reviews in Computational Chemistry, Volume 31


Reviews in Computational Chemistry, Volume 31


Reviews in Computational Chemistry 1. Aufl.

von: Abby L. Parrill, Kenny B. Lipkowitz

249,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 15.10.2018
ISBN/EAN: 9781119518051
Sprache: englisch
Anzahl Seiten: 352

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Beschreibungen

The Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered on molecular modeling, such as computer-assisted molecular design (CAMD), quantum chemistry, molecular mechanics and dynamics, and quantitative structure-activity relationships (QSAR). This volume, like those prior to it, features chapters by experts in various fields of computational chemistry.  Topics in Volume 31 include:<br /><br />Lattice-Boltzmann Modeling of Multicomponent Systems:  An Introduction<br />Modeling Mechanochemistry from First Principles<br />Mapping Energy Transport Networks in Proteins<br />The Role of Computations in Catalysis<br />The Construction of Ab Initio Based Potential Energy Surfaces<br />Uncertainty Quantification for Molecular Dynamics
<p>List of Contributors ix</p> <p>Preface xi</p> <p>Contributors to Previous Volumes xv</p> <p><b>1 Lattice-Boltzmann Modeling of Multicomponent Systems: An Introduction 1<br /></b><i>Ulf D. Schiller and Olga Kuksenok</i></p> <p>Introduction 1</p> <p>The Lattice Boltzmann Equation: A Modern Introduction 4</p> <p>A Brief History of the LBM 5</p> <p>The Lattice Boltzmann Equation 7</p> <p>The Fluctuating Lattice Boltzmann Equation 23</p> <p>Boundary Conditions 25</p> <p>Fluid–Particle Coupling 30</p> <p>LBM for Multiphase Fluids 37</p> <p>Governing Continuum Equations 37</p> <p>Lattice Boltzmann Algorithm for Binary Fluid: Free-Energy Approach 42</p> <p>Minimizing Spurious Velocities 47</p> <p>Conclusions 50</p> <p>References 51</p> <p><b>2 Mapping Energy Transport Networks in Proteins 63<br /></b><i>David M. Leitner and Takahisa Yamato</i></p> <p>Introduction 63</p> <p>Thermal and Energy Flow in Macromolecules 65</p> <p>Normal Modes of Proteins 65</p> <p>Simulating Energy Transport in Terms of Normal Modes 69</p> <p>Energy Diffusion in Terms of Normal Modes 70</p> <p>Energy Transport from Time Correlation Functions 73</p> <p>Energy Transport in Proteins is Inherently Anisotropic 75</p> <p>Locating Energy Transport Networks 77</p> <p>Communication Maps 77</p> <p>CURrent calculations for Proteins (CURP) 80</p> <p>Applications 83</p> <p>Communication Maps: Illustrative Examples 83</p> <p>CURP: Illustrative Examples 89</p> <p>Future Directions 98</p> <p>Summary 99</p> <p>Acknowledgments 100</p> <p>References 100</p> <p><b>3 Uncertainty Quantification for Molecular Dynamics 115<br /></b><i>Paul N. Patrone and Andrew Dienstfrey</i></p> <p>Introduction 115</p> <p>From Dynamical to Random: An Overview of MD 118</p> <p>System Specification 119</p> <p>Interatomic Potentials 121</p> <p>Hamilton’s Equations 123</p> <p>Thermodynamic Ensembles 128</p> <p>Where Does This Leave Us? 131</p> <p>Uncertainty Quantification 131</p> <p>What is UQ? 132</p> <p>Tools for UQ 136</p> <p>UQ of MD 143</p> <p>Tutorial: Trajectory Analysis 143</p> <p>Tutorial: Ensemble Verification 148</p> <p>Tutorial: UQ of Data Analysis for the Glass-Transition Temperature 151</p> <p>Concluding Thoughts 161</p> <p>References 162</p> <p><b>4 The Role of Computations in Catalysis 171<br /></b><i>Horia Metiu, Vishal Agarwal, and Henrik H. Kristoffersen</i></p> <p>Introduction 171</p> <p>Screening 172</p> <p>Sabatier Principle 173</p> <p>Scaling Relations 175</p> <p>BEP Relationship 176</p> <p>Volcano Plots 180</p> <p>Some Rules for Oxide Catalysts 189</p> <p>Let Us Examine Some Industrial Catalysts 191</p> <p>Sometimes Selectivity is More Important than Rate 191</p> <p>Sometimes We Want a Smaller Rate! 191</p> <p>Sometimes Product Separation is More Important than the Reaction Rate 193</p> <p>Some Reactions are Equilibrium-limited 193</p> <p>The Cost of Making the Catalyst is Important 194</p> <p>The Catalyst Should Contain Abundant Elements 194</p> <p>A Good Catalyst Should not be Easily Poisoned 195</p> <p>Summary 195</p> <p>References 196</p> <p><b>5 The Construction of Ab Initio-Based Potential Energy Surfaces 199<br /></b><i>Richard Dawes and Ernesto Quintas-Sánchez</i></p> <p>Introduction and Overview 199</p> <p>What is a PES? 199</p> <p>Significance and Range of Applications of PESs 204</p> <p>Challenges for Theory 207</p> <p>Terminology and Concepts 209</p> <p>The Schrödinger Equation 209</p> <p>The BO Approximation 210</p> <p>Mathematical Foundations of (Linear) Fitting 215</p> <p>Quantum Chemistry Methods 221</p> <p>General Considerations 221</p> <p>Single Reference Methods 223</p> <p>Multireference Methods 225</p> <p>Compound Methods or Protocols 227</p> <p>Fitting Methods 229</p> <p>General Considerations and Desirable Attributes of a PES 229</p> <p>Non-Interpolative Fitting Methods 231</p> <p>Interpolative Fitting Methods 239</p> <p>Applications 242</p> <p>The Automated Construction of PESs 242</p> <p>Concluding Remarks 248</p> <p>Acknowledgements 250</p> <p>Acronyms/Abbreviations 250</p> <p>References 251</p> <p><b>6 Modeling Mechanochemistry from First Principles 265<br /></b><i>Heather J. Kulik</i></p> <p>Introduction and Scope 265</p> <p>Potential Energy Surfaces and Reaction Coordinates 266</p> <p>Theoretical Models of Mechanochemical Bond Cleavage 268</p> <p>Linear Model (Kauzmann, Eyring, and Bell) 268</p> <p>Tilted Potential Energy Profile Model 270</p> <p>First-Principles Models for Mechanochemical Bond Cleavage 271</p> <p>Constrained Geometries Simulate External Force (COGEF) 271</p> <p>Force-Modified Potential Energy Surfaces 273</p> <p>Covalent Mechanochemistry 278</p> <p>Overview of Characterization Methods 278</p> <p>Representative Mechanophores 280</p> <p>Representative Mechanochemistry Case Studies 281</p> <p>Benzocyclobutene 281</p> <p>gem-Difluorocyclopropane 285</p> <p>PPA: Heterolytic Bond Cleavage 288</p> <p>Mechanical Force for Sampling: Application to Lignin 292</p> <p>Best Practices for Mechanochemical Simulation 296</p> <p>Conclusions 298</p> <p>Acknowledgments 299</p> <p>References 300</p> <p>Index 313<b> </b></p>
<p><b>ABBY L. PARRILL, Ph.D.,</b> is a Professor in the Department of Chemistry at the University of Memphis, TN. Her research interests are in bioorganic chemistry, protein modeling, and rational ligand design and synthesis. <p><b>KENNY B. LIPKOWITZ, Ph.D.,</b> was one of the founding co-editors of Reviews in Computational Chemistry. He spent 28 years as an academician and then moved to the Office of Naval Research where he is a Program Manager in Computer-Aided Materials Design.
<p><b>A VALUABLE REFERENCE TO THE METHODS AND TECHNIQUES IN COMPUTATIONAL CHEMISTRY</b> <p><i>Reviews in Computational Chemistry, Volume 31</i> brings together in one book a collection of writings from noted authorities in the field. Volume 31 is designed for use by both those new to the field and for seasoned researchers to aid them in selecting and applying new computational chemistry methods to their own research problems. The book's tutorial-style chapters provide both mini-tutorials for novices as well as critical literature reviews highlighting advanced applications. <p>Two themes connect many of the chapters: modeling of soft matter systems such as polymers and proteins and the first principle methods necessary for modeling chemical reactions. The contributors cover a wealth of topics centered on molecular modeling, such as modeling mechanochemical processes and protein internal energy transfer networks, lattice Boltzmann simulations, ab initio potential energy surface construction, catalyst optimization, and uncertainty quantification. This important resource: <ul> <li>Offers a guide to the both the background and theory and the strategies for using methods correctly</li> <li>Includes information on the pitfalls to avoid, applications, and references</li> <li>Presents a detailed subject index to help quickly discover particular topics</li> <li>Uses a tutorial manner and non-mathematical style, that helps to access computational methods outside one's immediate area of expertise</li> </ul> <p>Written for computational chemists, theoretical chemists, pharmaceutical chemists, biological chemists, chemical engineers, and others. <i>Reviews in Computational Chemistry, Volume 31</i> is an essential guide to the modeling of soft manner systems and explains the principle methods needed for modeling chemical reactions.

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