Computational chemistry Books
Elsevier Science Physical Chemistry
Table of Contents1. Overview 2. Five Important Equations in Thermodynamics 3. Gibbs Free Energy, Work, and Equilibrium 4. Thermodynamics of the Gas State 5. Thermodynamics of the Liquid State 6. Solid State 7. Quantum Principles 8. Quantum Systems With Constant Potential 9. Quantum Energies for Central Potentials 10. Electronic and Nuclear States 11. Rotation–Vibration Spectra 12. Classical Statistical Mechanics 13. Quantum Statistical Mechanics 14. Nonequilibrium Thermodynamics 15. Reaction Rates and Mechanisms
£117.30
Springer-Verlag New York Inc. An Introduction to Chemoinformatics
Book SynopsisChemoinformatics draws upon techniques from many disciplines including computer science, mathematics, computational chemistry and data visualisation to tackle these problems.Trade ReviewThis is a rather remarkable little book. Just as its title promises, it provides an introduction to a very wide variety of chemoinformatic and CADD topics. Allthough the book is written for beginning graduate students and advanced undergraduates, it could certainly provide a very helpful overview for professionals with no prior knowledge of the subject matter. Robert S. Pearlman, University of Texas at Austin. J.Am. Chem. Soc., Vol 126, No. 4, 2004.Table of ContentsPreface. Acknowledgements. 1: Representation and Manipulation of 2D Molecular Structures. 1. Introduction. 2. Computer Representations of Chemical Structures. 3. Structure Searching. 4. Substructure Searching. 5. Reaction Databases. 6. The Representation of Patents and Patent Databases. 7. Relational Database Systems. 8. Summary. 2: Representation and Manipulation of 3D Molecular Structures. 1. Introduction. 2. Experimental 3D databases. 3. 3D Pharmacophores. 4. Implementation of 3D database Searching. 5. Theoretical 3D Databases. 6. Methods to Derive 3D Pharmacophores. 7. Applications of 3D Pharmacophore Mapping and 3D Database Searching. 8. Summary. 3: Molecular Descriptors. 1. Introduction. 2. Descriptors Calculated from the 2D Structure. 3. Descriptors Based on 3D Representations. 4. Data Verification and Manipulation. 5. Summary. 4: Computational Models. 1. Introduction. 2. Historical Overview. 3. Deriving a QSAR Equation: Simple and Multiple Linear Regression. 4. Designing a QSAR 'Experiment'. 5. Principal Components Regression. 6. Partial Least Squares. 7. Molecular Field Analysis and Partial Least Squares. 8. Summary. 5: Similarity Methods. 1. Introduction. 2. Similarity Based on 2D Fingerprints. 3. Similarity Coefficients. 4. Other 2D Descriptor Methods. 5. 3D Similarity. 6. Summary. 6: Selecting Diverse SetsOf Compounds. 1. Introduction. 2. Cluster Analysis. 3. Dissimilarity-Based selection methods. 4. Cell-Based Methods. 5. Optimisation Methods. 6. Comparison and Evaluation of Selection Methods. 7. Summary. 7: Analysis of High-Throughput Screening Data. 1. Introduction. 2. Data Visualisation. 3. Data Mining Methods. 4. Summary. 8: Virtual Screening. 1. Introduction. 2. 'Drug-Likeness' and Compound Filters. 3. Structure-Based Virtual Screening. 4. The Prediction of ADMET Properties. 5. Summary. 9: Combinatorial Chemistry and Library Design. 1. Introduction. 2. Diverse and Focussed Libraries. 3. Library Enumeration. 4. Combinatorial Library Design Strategies. 5. Approaches to Product-Based Library Design. 6. Multiobjective Library Design. 7. Practical Examples of Library Design. 8. Summary. Appendix 1: Matrices, Eigenvectors and Eigenvalues. Appendix 2: Conformation, Energy Calculations and Energy Surfaces. Further Reading. References. Index.
£71.24
De Gruyter Accelerated Materials Discovery: How to Use Artificial Intelligence to Speed Up Development
Book SynopsisTypical timelines to go from discovery to impact in the advanced materials sector are between 10 to 30 years. Advances in robotics and artificial intelligence are poised to accelerate the discovery and development of new materials dramatically. This book is a primer for any materials scientist looking to future-proof their careers and get ahead of the disruption that artificial intelligence and robotic automation is just starting to unleash. It is meant to be an overview of how we can use these disruptive technologies to augment and supercharge our abilities to discover new materials that will solve world’s biggest challenges. Written by world leading experts on accelerated materials discovery from academia (UC Berkeley, Caltech, UBC, Cornell, etc.), industry (Toyota Research Institute, Citrine Informatics) and national labs (National Research Council of Canada, Lawrence Berkeley National Labs).
£80.27
