Exploring Chemical Concepts Through Theory and Computation (eBook)

Shubin Liu (Herausgeber)

eBook Download: EPUB

2024
1062 Seiten
Wiley-VCH GmbH (Verlag)
978-3-527-84341-1 (ISBN)

Infos

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.

Autor

Dr. Shubin Liu is a Senior Computational Scientist at the Research Computing Center, University of North Carolina at Chapel Hill. He obtained his Ph.D. degree with Robert G. Parr in 1996 and postdoctoral training with Weitao Yang of Duke University. He has been an independent researcher since 2000, focusing on developing a chemical reactivity theory using density functional theory language. Dr. Shubin Liu has authored over 200 peer-reviewed publications and is recognized in the field by various scientific awards including the Wiley-IJQC Young Investigator Award.

Inhalt

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

Produkt-Details

• Erscheint lt. Verlag: 15.5.2024
• Sprache: englisch
• Themenwelt: Naturwissenschaften ► Chemie
• Schlagworte: acidity • Antiaromaticity • aromaticity • atoms • basicity • charge transport • chemical bonding • Chemie • Chemistry • chemistry concepts • chemistry frameworks • chemistry theory • Computational Chemistry • Computational Chemistry & Molecular Modeling • Computational Chemistry u. Molecular Modeling • Electrophilicity • HSAB • machine learning • Mathematical & Computational Physics • Mathematische Physik • Molecules • Nucleophilicity • oxidation states • partial charges • Physics • Physik • Quantenchemie • Quantum Chemistry
• ISBN-10: 3-527-84341-8 / 3527843418
• ISBN-13: 978-3-527-84341-1 / 9783527843411