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<p>An Introduction to Electron Localization-Delocalization Matrices.- The Physics of Electron Localization and Delocalization.- The Quantum Theory of Atoms in Molecules and Electron Localization and Delocalization.- Localization-Delocalization Matrix Representation of Molecules.- Molecular Fingerprinting using Localization-Delocalization Matrices: Computational Aspects.- Principal Component Analysis of Localization-Delocalization Matrices.- Localization-Delocalization Matrices Analysis for Corrosion Inhibition.- Localization-Delocalization Matrices Analysis in Predicting Mosquito Repellency.- Modeling Enzyme-Substrate Interaction with Localization-Delocalization Matrices.- Localization-Delocalization Matrices of Large Systems.- Closing remarks.</p>

<b>Chérif F. Matta</b> is Full Professor and Chair in the Department of Chemistry and Physics at the Mount Saint Vincent University (MSVU), and an Honorary Professor at the Departments of Chemistry of Universite Laval, Dalhousie University, Saint Mary’s University, all in Canada, and Zewail City for Science and Technology in Egypt. After a B.Sc. in pharmaceutical sciences from Alexandria University (Egypt), Chérif Matta received his Ph.D. in theoretical quantum chemistry from McMaster University (Canada) in 2002. He then spent time as Postdoctoral Researcher at the University of Toronto, Canada, with Nobel Laureate John C. Polanyi, and at Dalhousie University. He became Assistant Professor at MSVU in July 2006, Associate Professor in 2009, and Full Professor in 2018. Chérif F. Matta has held Adjunct Professorship at McMaster University (2004-2005) and Invited Visiting Professorship (2007-2012) at the Université Henri Poincaré (re-named Université de Lorraine) in Nancy, France, from which he also earned his Habilitation à diriger des recherches (HDR, in 2009). His research interests in theoretical chemistry are documented in numerous original publications and four books, two of which he has edited. His achievements have been honored with prestigious awards, such as his naming as Fellow of the American Association for the Advancement of Science and the African Academy of Science, or the John C. Polanyi Prize in Chemistry in 2004. Chérif Matta is an experienced and engaged teacher, lecturing university courses at different levels and supervising numerous research students. In his spare time, Chérif Matta devotes to artistic oil painting, both of non-scientific and scientific motifs, and an amateur astronomer. The latter documents his strong interest in esthetics in science and beauty of the form which amplifies the underlying formal mathematical and logical beauty.<br><p><b>Ronald L. Cook</b> is currently the CTO of&nbsp; Molecular Design Innovations, LLC., 754 S BraunSt, Lakewood CO USA (formerly a Principal Scientist TDA Research, Inc., in Golden, CO, USA). He obtained his B.A. in Chemistry from the University of North Colorado in 1977 and a Ph.D. in Organometallic Chemistry from Utah State University in 1983. In the years 1982-84, he worked as a Postdoc at the Ohio State University, before joining Eltron Research, Inc., as a Scientist/Research Manager. From 1992 to 2021, he was with TDA Research, Inc., as Principal Scientist. His current interest and research focus is on the development of novel descriptors from localization-delocalization matrices that can be used to develop predictive models for new materials and molecules. His achievements are documented in 21 patents, numerous original publications (57), and conference presentations. As Principal Scientist, Ronald Cook often leads in-house workshops on various topics, such as nanotechnology, nonlinear modeling, and data analysis and investing.<br></p><p><b>Paul W. Ayers</b> is Professor at the Department of Chemistry & Chemical Biology, McMaster University, Canada. He received his B.S. in chemistry, mathematics, and physics from Lipscomb University (Nashville, Tennessee, USA) and a Ph.D. in Chemistry from the University of North Carolina at Chapel Hill (USA) in 2001 (with Robert Parr); he was then a National Institutes of Health postdoctoral fellow at Duke University (with Weitao Yang). Since 2002, he has been a faculty member at McMaster University, rising to full professor in 2013. His research interests in developing new mathematical and computational tools for describing and predicting chemical processes, especially chemical reactions, are documented in nearly 400 publications and have been the subject of more than 300 invited presentations. He co-founded the QC-Devs international consortium for free and open-source software.<br></p>

This book builds bridges between two yet separated branches of theoretical and mathematical chemistry: Chemical Graph Theory and Electronic Structure Calculations. Although either of the fields have developed their own techniques, problems, methods, and favorite benchmark cases independent from each other, the authors have managed to bring them together by using the localization-delocalization matrix (LDM). The LDM is a novel molecular descriptor that fingerprints a molecule by condensing the complicated electronic information in one, mathematically manageable, object. In this book, the authors introduce the readers to modeling techniques based on LDMs. Their technique offers a high accuracy as well as robust predictive power, often dramatically surpassing the potential of either of the constituting methods on their own.&nbsp;In addition to the comprehensive and accessible introduction to this new field of theoretical chemistry, the authors offer their self-developed software free to download, so that readers can try running their own simulations. The described methods are very general and can easily be implemented for calculating various properties and parameters such as mosquito repelling activity, ionic liquid properties, local aromaticity of ring molecules, log P's, pKa's, LD50, corrosion inhibition activities, and Lewis acidities and basicities – to only name a few. The free downloadable software helps readers automate the analysis of the matrices described in this book and hence facilitates application of the described methodology.&nbsp;

Offers a clear link between theory/abstract concepts and numerical practical results Introduces robust statistical modeling to predict molecular properties Demonstrates the high efficacy of LDMs in various practical applications of bench chemistry