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Computational Approaches for the Prediction of pKa Values
The pKa of a compound describes its acidity or basicity and, therefore, is one of its most important properties. Its value determines what form of the compound-positive ion, negative ion, or neutral species-will be present under different circumstances. This is crucial to the action and detection of the compound as a drug, pollutant, or other activ
Modeling Chemical Systems using Cellular Automata
Modeling Chemical Systems using Cellular Automata provides a practical introduction to an exciting modeling paradigm for complex systems. The book first discusses the nature of scientific inquiry using models and simulations, and then describes the nature of cellular automata models. It then gives detailed descriptions, with examples and exercises, of how cellular automata models can be used in the study of a wide variety chemical, physical, and biochemical phenomena. Topics covered include models of water itself, solution phenomena, solution interactions with stationary systems, first- and second-order kinetic phenomena, enzyme kinetics, vapor-liquid equilibrium, and atomic and molecular ex...
Computational Approaches for the Prediction of pKa Values
The pKa of a compound describes its acidity or basicity and, therefore, is one of its most important properties. Its value determines what form of the compound—positive ion, negative ion, or neutral species—will be present under different circumstances. This is crucial to the action and detection of the compound as a drug, pollutant, or other active chemical agent. In many cases it is desirable to predict pKa values prior to synthesizing a compound, and enough is now known about the salient features that influence a molecule’s acidity to make these predictions. Computational Approaches for the Prediction of pKa Values describes the insights that have been gained on the intrinsic and ex...
Computational Approaches for the Prediction of pKa Values
The pKa of a compound describes its acidity or basicity and, therefore, is one of its most important properties. Its value determines what form of the compound—positive ion, negative ion, or neutral species—will be present under different circumstances. This is crucial to the action and detection of the compound as a drug, pollutant, or other active chemical agent. In many cases it is desirable to predict pKa values prior to synthesizing a compound, and enough is now known about the salient features that influence a molecule’s acidity to make these predictions. Computational Approaches for the Prediction of pKa Values describes the insights that have been gained on the intrinsic and ex...
Reviews in Computational Chemistry, Volume 32
REVIEWS IN COMPUTATIONAL CHEMISTRY THE LATEST VOLUME IN THE REVIEWS IN COMPUTATIONAL CHEMISTRY SERIES, THE INVALUABLE REFERENCE TO METHODS AND TECHNIQUES IN COMPUTATIONAL CHEMISTRY Reviews in Computational Chemistry reference texts assist researchers in selecting and applying new computational chemistry methods to their own research. Bringing together writings from leading experts in various fields of computational chemistry, Volume 32 covers topics including global structure optimization, time-dependent density functional tight binding calculations, non-equilibrium self-assembly, cluster prediction, and molecular simulations of microphase formers and deep eutectic solvents. In keeping with ...
Advances in Quantum Chemistry
Advances in Quantum Chemistry presents surveys of current topics in this rapidly developing field that has emerged at the cross section of the historically established areas of mathematics, physics, chemistry, and biology. It features detailed reviews written by leading international researchers. This series provides a one-stop resource for following progress in this interdisciplinary area. - Publishes articles, invited reviews and proceedings of major international conferences and workshops - Written by leading international researchers in quantum and theoretical chemistry - Highlights important interdisciplinary developments
Reviews in Computational Chemistry, Volume 28
The Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered around 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 28 include: Free-energy Calculations with Metadynamics Polarizable Force Fields for Biomolecular Modeling Modeling Protein Folding Pathways Assessing Structural Predictions of Protein-Protein Recognition Kinetic Monte Carlo Simulation of Electrochemical Systems Reactivity and Dynamics at Liquid Interfaces
Reviews in Computational Chemistry, Volume 26
Computational chemistry is increasingly used in conjunction with organic, inorganic, medicinal, biological, physical, and analytical chemistry, biotechnology, materials science, and chemical physics. This series is essential in keeping those individuals involved in these fields abreast of recent developments in computational chemistry.
Reviews in Computational Chemistry, Volume 27
This volume, like those prior to it, features chapters by experts in various fields of computational chemistry. Volume 27 covers brittle fracture, molecular detailed simulations of lipid bilayers, semiclassical bohmian dynamics, dissipative particle dynamics, trajectory-based rare event simulations, and understanding metal/metal electrical contact conductance from the atomic to continuum scales. Also included is a chapter on career opportunities in computational chemistry and an appendix listing the e-mail addresses of more than 2500 people in that discipline. FROM REVIEWS OF THE SERIES "Reviews in Computational Chemistry remains the most valuable reference to methods and techniques in computational chemistry." —JOURNAL OF MOLECULAR GRAPHICS AND MODELLING "One cannot generally do better than to try to find an appropriate article in the highly successful Reviews in Computational Chemistry. The basic philosophy of the editors seems to be to help the authors produce chapters that are complete, accurate, clear, and accessible to experimentalists (in particular) and other nonspecialists (in general)." —JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
Advances in Quantative Structure - Property Relationships
The object of this series is to provide interesting and timely reviews covering all aspects of the field. It is our hope that this will encourage the transfer of new methods, techniques, and parameterizations from the field in which they were developed to other areas that can make good use of them.·Quantitative Structure Property Relationships (QSPR) have developed into a major method of chemical research in many scientific disciplines·Provides much needed cross fertilization between disciplines researching QSPR
