Buch, Englisch, 318 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 450 g
A Nonspecialist's Guide to Practical and Predictive Simulations
Buch, Englisch, 318 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 450 g
ISBN: 978-0-443-34211-0
Verlag: Elsevier Science
Computational Chemistry for Experimentalists: A Nonspecialist's Guide to Practical and Predictive Simulations empowers chemists-especially those at emerging institutions or in small and medium enterprises-by transforming foundational chemical concepts into practical computational skills. A modular approach, paired with hands-on video tutorials, ensures that even nonspecialists can confidently apply simulations to their research, regardless of career stage or specialization. Beyond its accessible structure, the book features six modules covering core topics such as electronic structure theory and molecular dynamics. Ten experimental modules focus on simulating specific laboratory techniques-reaction mechanisms, NMR, UV/vis, band structures, XPS, and organometallic chemistry.
Regularly updated online tutorials complement the material, providing project-based, real-world training. By bridging theory and practice, this guide serves mid-career professionals, undergraduate and graduate students, and early-career researchers, making computational chemistry approachable and practical for all experimental chemists.
Ben's free online course complimenting this book is available on GitHub:
https://github.com/bjanesko/ComputationalChemistryForExperimentalists
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
- Naturwissenschaften Chemie Analytische Chemie Massenspektrometrie, Spektroskopie, Spektrochemie
- Naturwissenschaften Chemie Chemie Allgemein Chemometrik, Chemoinformatik
- Naturwissenschaften Chemie Organische Chemie
- Naturwissenschaften Chemie Physikalische Chemie
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
Weitere Infos & Material
1. Introduction and Motivation
Section I: Core Modules
2. Molecular Orbitals and Basis Sets
3. Geometry Optimization
4. Orbitals and Densities
5. Dynamics and Conformational Sampling
6. Atomic Charges, Electrostatic Potentials, and Multipole Moments
7. Mean-Field Electronic Structure Approximations
8. Data Processing
Section II: Shared Modules
9. Free Energies of Formation
10. Transition States and Reaction Rates
11. Continuum Solvent
12. Ab Initio Wavefunctions
13. Databases and Machine Learning
Section III: Specific Experiments
14. Ionization Potentials, Electron Affinities, and Redox Potentials
15. Infrared and Raman Spectra
16. NMR Spectra
17. Band Structures
18. pKa
19. Absorption and Emission Spectroscopy
Section IV: Summary Examples
20. Transition Metal Catalysis
21. Drug Design
