Exploring Chemical Concepts Through Theory and Computation
A comprehensive account of how to use theoretical models to describe and predict key chemical parameters and phenomena, from electron transfer to bond strength, and from acid-base behavior to aromaticity.
1. Chemical Concepts from Molecular Orbital Theory
1. Chemical Concepts from Molecular Orbital Theory
2. Chemical Concepts from Ab Initio Valence Bond Theory
3. Chemical Concepts from Conceptual Density Functional Theory
4. Chemical Concepts from Density-Based Approaches in Density Functional Theory
5. Chemical Bonding
6. Partial Charges
7. Atoms in Molecules
8. Effective Oxidation States Analysis
9. Aromaticity and Antiaromaticity
10. Acidity and Basicity
11. Sigma Hole Supported Interactions: Qualitative Features, Various Incarnations, and Disputations
12. On the Generalization of Marcus Theory for Two-State Photophysical Processes
13. Computational Modeling of CO2 Reduction and Conversion via Heterogeneous and Homogeneous Catalysis
14. Excited States in Conceptual DFT
15. Modeling the Photophysical Processes of Organic Molecular Aggregates with Inclusion of Intermolecular Interactions and Vibronic Couplings
16. Duality of Conjugated ¿¿ Electrons
17. Energy Decomposition Analysis and Its Applications
18. Chemical Concepts in Solids
19. Toward Interpretable Machine Learning Models for Predicting Spectroscopy, Catalysis, and Reactions
20. Learning Design Rules for Catalysts Through Computational Chemistry and Machine Learning
1. Chemical Concepts from Molecular Orbital Theory
2. Chemical Concepts from Ab Initio Valence Bond Theory
3. Chemical Concepts from Conceptual Density Functional Theory
4. Chemical Concepts from Density-Based Approaches in Density Functional Theory
5. Chemical Bonding
6. Partial Charges
7. Atoms in Molecules
8. Effective Oxidation States Analysis
9. Aromaticity and Antiaromaticity
10. Acidity and Basicity
11. Sigma Hole Supported Interactions: Qualitative Features, Various Incarnations, and Disputations
12. On the Generalization of Marcus Theory for Two-State Photophysical Processes
13. Computational Modeling of CO2 Reduction and Conversion via Heterogeneous and Homogeneous Catalysis
14. Excited States in Conceptual DFT
15. Modeling the Photophysical Processes of Organic Molecular Aggregates with Inclusion of Intermolecular Interactions and Vibronic Couplings
16. Duality of Conjugated ¿¿ Electrons
17. Energy Decomposition Analysis and Its Applications
18. Chemical Concepts in Solids
19. Toward Interpretable Machine Learning Models for Predicting Spectroscopy, Catalysis, and Reactions
20. Learning Design Rules for Catalysts Through Computational Chemistry and Machine Learning
Liu, Shubin
| ISBN | 9783527352487 |
|---|---|
| Article number | 9783527352487 |
| Media type | Book |
| Edition number | 1. Auflage |
| Copyright year | 2024 |
| Publisher | Wiley-VCH |
| Length | 592 pages |
| Illustrations | 18 Tabellen |
| Language | English |
