In this contribution we assess the computational machinery to calculate the phosphorescence properties of a large pool of heteroleptic [Ir(C^N)2(N^N)]+ complexes (where N^N is an ancillary ligand and C^N is a cyclometalating ligand) including their phosphorescent rates and their emission spectra. Efficient computational protocols are next proposed. Specifically, different flavors of DFT functionals were benchmarked against DLPNO-CCSD(T) for the phosphorescence energies. Transition density matrix and decomposition analysis of the emitting triplet excited state enables to categorize the studied complexes into different cases, from e.g., predominant triplet ligand-centered (3LC) character to predominant charge-transfer (3CT) character, either of metal-to-ligand charge transfer (3MLCT), ligand-to-ligand charge transfer (3LLCT) or a combination of the two. We have also calculated the vibronically resolved phosphorescent spectra and rates. Ir (III) complexes with predominant 3CT character are characterized by less vibronically-resolved bands as compared to those with predominant 3LC character. Furthermore, some of the complexes are characterized by close-lying triplet excited states, so that the calculation of their phosphorescence properties poses additional challenges. In these scenarios, it is necessary to perform geometry optimizations of higher-lying triplet excited states (i.e., Tn). We demonstrate that in the latter scenarios all the close-lying triplet species must be considered to recover the shape of the experimental emission spectra. The global analysis of computed emission energies, shape of the computed emission spectra, computed rates, etc. enable us to unambiguously pinpoint for the first time the triplet states involved in the emission process and to provide a general classification of Ir (III) complexes with regards to their phosphorescent properties.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Pseudoatom databanks, collecting parameters of multipole model of electron densities for various atom types, are used to replace Independent Atom Model by the more accurate Transferable Aspherical Atom Model (TAAM) in crystal structure refinement. They may also be used to reconstruct electron density of a molecule, crystal or biomacromolecular complex in fast yet quite accurate way and compute from it various properties, like energy of electrostatic interactions, for example. Even faster, but similarly accurate in electrostatic energy estimations model exists, the aug-PROmol. Model analogous to aug-PROmol cannot be built from the current pseudoatom databanks, as they perform badly when truncated to the monopole level. Here we searched for new strategies of multipole model refinements, leading to better parametrization already at the monopole level. This would allow to create in a single route of model parametrization a pseudoatom databank, which would be suitable for both crystal structure refinement and rapid electrostatic energy calculations. Such a route does not exist yet, because as we show here, the aug-PROmol model, alternative to the current pseudoatom databanks, is not suitable for crystal X-ray structure refinement. Here we show that cumulative approach to multipole model refinements, as oppose to simultaneous or iterative refinements of all multipole model parameters (Pv, κ, Plm, κ') leads to substantially different models of electron density. Cumulative refinement of Plm first and then κ' parameters is much worse than simultaneous. It results in electron density model giving wrong estimates of electrostatic interaction energies and atomic displacement parameters. Cumulative refinement of two blocks of parameters, Pv and κ first and then Plm and κ', on the other hand, leads to the Pv𝜅|Plm𝜅’ model having promising properties. It is similarly good as University at Buffalo DataBank (UBDB) of pseudoatoms in X-ray structure TAAM refinement and electrostatic energy estimations, especially for less polar molecules. When truncated to monopole level, the Pv𝜅 model has a chance to replace the aug-PROmol in fast yet accurate electrostatics energy calculations, although some improvements in κ parametrization for polar functional groups are still needed. The Pv𝜅|Plm𝜅’ model is also a source of point charges which behave similarly to the RESP charges in electrostatic interaction energy estimations.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Pseudoatom databanks, collections of parameters from the multipole model of electron densities for various atom types, are used to replace the Independent Atom Model with the more accurate Transferable Aspherical Atom Model (TAAM) in crystal structure refinements. The databanks are also employed to reconstruct the electron density of a molecule, crystal or biomacromolecular complex in a fast yet accurate way and compute various properties such as the energy of electrostatic interactions, for example. A even faster but similarly accurate model for estimations of electrostatic energy exists called aug-PROmol [Bojarowski, Kumar & Dominiak (2016). ChemPhysChem , 17 , 2455–2460]. A model analogous to aug-PROmol cannot be built from the current pseudoatom databanks, as they perform badly when truncated to the monopole level. Here, new strategies for multipole model refinements were sought, leading to better parametrization at the monopole level. This would allow the creation of a pseudoatom databank in a single route of model parametrization, which would be suitable for both crystal structure refinement and rapid electrostatic energy calculations. Here it is shown that the cumulative approach to multipole model refinements, as opposed to simultaneous or iterative refinements of all multipole model parameters ( P v , κ, P lm , κ′), leads to substantially different models of electron density. Cumulative refinement of two blocks of parameters, the first with P v and κ and then the second with P lm and κ′, leads to the P v κ| P lm κ′ model having promising properties. The P v κ| P lm κ′ model is as good as the University at Buffalo DataBank (UBDB) in X-ray structure TAAM refinements and electrostatic energy estimations, especially for less polar molecules. When truncated to the monopole level, the P v κ model has a chance to replace aug-PROmol in fast yet accurate electrostatics energy calculations, although some improvements in κ parametrization for polar functional groups are still needed. The P v κ model is also a source of point charges which behave similarly to restrained electrostatic potential (RESP) charges in electrostatic interaction energy estimations.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

A fast and accurate operational model of electron density is crucial in many scientific disciplines including crystallography, molecular biology, pharmaceutical, and structural chemistry. In quantum crystallography, the aspherical refinement of crystal structures is becoming increasingly popular because of its accurate description in terms of physically meaningful properties. The transferable aspherical atom model (TAAM) is quick and precise, though it requires a robust algorithm for atom typing and coverage of the most popular atom types present in small organic molecules. Thus, the University at Buffalo Databank (UBDB) has been renamed to the Multipolar Atom Types from Theory and Statistical clustering (MATTS) data bank, broadened, restructured, and implemented into the software DiSCaMB with 651 atom types obtained from 2316 small-molecule crystal structures containing C, H, N, O, P, S, F, Cl, and Br atoms. MATTS2021 data bank now covers most of the small molecules, peptides, RNA, DNA, and some frequently occurring cations and anions in biological, pharmaceutical, and organic materials, including the majority of known crystal structures composed of the above elements. The multipole model parameters (Pval, κ, κ′, Plm) obtained for different atom types were greatly influenced by neighboring atom types, hybridization, geometrical strain in the ring system, and charges on the molecule. Contrary to previous findings, the atoms showing variable oxidation states and ions deviate from the linear dependence of monopole-derived charges on the expansion–contraction κ parameter.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.