Matta / Ayers / Cook

Electron Localization-Delocalization Matrices

Springer

ISBN 978-3-031-51432-6

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Bibliografische Daten

Fachbuch

Buch. Hardcover

2024

22 s/w-Abbildungen, 66 Farbabbildungen.

In englischer Sprache

Umfang: xix, 222 S.

Format (B x L): 15,5 x 23,5 cm

Verlag: Springer

ISBN: 978-3-031-51432-6

Produktbeschreibung

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. 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.

Autorinnen und Autoren

Kundeninformationen

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

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