Annual Reports on Computaional Chemistry, Volume 20 highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors.
1. 1 Introduction - p. 64 2. 2 Formal roots: wavefunction theory, DFT, and adiabatic projections - p. 68 3. 3 Our general formalism - p. 72 4. 4 Kohn-Sham DFT and global hybrids - p. 74 5. 5 Range-separated hybrids and range-separated wavefunction+DFT - p. 79 6. 6 Perdew-Zunger self-interaction correction - p. 83 7. 7 CAS-in-DFT - p. 88 8. 8 DFT+U - p. 92 9. 9 Summary - p. 99 10. References - p. 100 11. Chapter Three: Super-ccCA: Robust transition metal thermochemistry - p. 111 12. Chapter Four: Accessible and predictable QM-cluster model building for enzymes with the Residue Interaction Network Residue Selector - p. 131 13. Chapter Five: Recent advances in X-ray absorption near edge structure (XANES) simulations for catalysis: Theories and applications - p. 157 14. Chapter Six: Machine learning and deep learning based scoring functions in deciphering ligand-receptor binding: An application in drug design for GPCRs - p. 189 15. Chapter Seven: Toward AI/ML-assisted discovery of transition metal complexes - p. 225 16. Chapter Eight: Federated quantum machine learning for drug discovery and healthcare - p. 269
Annual Reports on Computaional Chemistry, Volume 20 highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors.
1. 1 Introduction - p. 64 2. 2 Formal roots: wavefunction theory, DFT, and adiabatic projections - p. 68 3. 3 Our general formalism - p. 72 4. 4 Kohn-Sham DFT and global hybrids - p. 74 5. 5 Range-separated hybrids and range-separated wavefunction+DFT - p. 79 6. 6 Perdew-Zunger self-interaction correction - p. 83 7. 7 CAS-in-DFT - p. 88 8. 8 DFT+U - p. 92 9. 9 Summary - p. 99 10. References - p. 100 11. Chapter Three: Super-ccCA: Robust transition metal thermochemistry - p. 111 12. Chapter Four: Accessible and predictable QM-cluster model building for enzymes with the Residue Interaction Network Residue Selector - p. 131 13. Chapter Five: Recent advances in X-ray absorption near edge structure (XANES) simulations for catalysis: Theories and applications - p. 157 14. Chapter Six: Machine learning and deep learning based scoring functions in deciphering ligand-receptor binding: An application in drug design for GPCRs - p. 189 15. Chapter Seven: Toward AI/ML-assisted discovery of transition metal complexes - p. 225 16. Chapter Eight: Federated quantum machine learning for drug discovery and healthcare - p. 269
