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.

Autorentext

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.

Klappentext

Deep, theoretical resource on the essence of chemistry, explaining a variety of important concepts including redox states and bond types Exploring Chemical Concepts Through Theory and Computation provides a comprehensive account of how the three widely used theoretical frameworks of valence bond theory, molecular orbital theory, and density functional theory, along with a variety of important chemical concepts, can between them describe and efficiently and reliably predict key chemical parameters and phenomena. By comparing the three main theoretical frameworks, readers will become competent in choosing the right modeling approach for their task. The authors go beyond a simple comparison of existing algorithms to show how data-driven theories can explain why chemical compounds behave the way they do, thus promoting a deeper understanding of the essence of chemistry. The text is contributed to by top theoretical and computational chemists who have turned computational chemistry into today's data-driven and application-oriented science. Exploring Chemical Concepts Through Theory and Computation discusses topics including:

• Orbital-based approaches, density-based approaches, chemical bonding, partial charges, atoms in molecules, oxidation states, aromaticity and antiaromaticity, and acidity and basicity
• Electronegativity, hardness, softness, HSAB, sigma-hole interactions, charge transport and energy transfer, and homogeneous and heterogeneous catalysis
• Electrophilicity, nucleophilicity, cooperativity, frustration, homochirality, and energy decomposition

• Chemical concepts in solids, excited states, spectroscopy and machine learning, and catalysis and machine learning, as well as key connections between related concepts Aimed at both novice and experienced computational, theoretical, and physical chemists, Exploring Chemical Concepts Through Theory and Computation is an essential reference to gain a deeper, more advanced holistic understanding of the field of chemistry as a whole.

  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
  21. Chemical Concepts from Molecular Orbital Theory
  22. Chemical Concepts from Ab Initio Valence Bond Theory
  23. Chemical Concepts from Conceptual Density Functional Theory
  24. Chemical Concepts from Density-Based Approaches in Density Functional Theory
  25. Chemical Bonding
  26. Partial Charges
  27. Atoms in Molecules
  28. Effective Oxidation States Analysis
  29. Aromaticity and Antiaromaticity
  30. Acidity and Basicity
  31. Sigma Hole Supported Interactions: Qualitative Features, Various Incarnations, and Disputations
  32. On the Generalization of Marcus Theory for Two-State Photophysical Processes
  33. Computational Modeling of CO2 Reduction and Conversion via Heterogeneous and Homogeneous Catalysis
  34. Excited States in Conceptual DFT
  35. Modeling the Photophysical Processes of Organic Molecular Aggregates with Inclusion of Intermolecular Interactions and Vibronic Couplings
  36. Duality of Conjugated Electrons
  37. Energy Decomposition Analysis and Its Applications
  38. Chemical Concepts in Solids
  39. Toward Interpretable Machine Learning Models for Predicting Spectroscopy, Catalysis, and Reactions
  40. Learning Design Rules for Catalysts Through Computational Chemistry and Machine Learning