Two‐coordinate carbene Cu(Ι) amide complexes with sterically bulky groups such as the diisopropyl phenyl (dipp) on the carbenes have been shown to have comparable performance to the phosphorescent emitters bearing heavy atoms such as iridium and platinum. These bulky groups enforce a coplanar molecular structure and suppress the nonradiative decay rates. Here, three different two‐coordinate Cu(Ι) complexes were investigated that bear a common thiazole carbene, 3‐(2,6‐diisopropylphenyl)‐4,5‐dimethylthiazol‐2‐ylidene, with only a single dipp group, and carbazolyl ligands with substituents of varying steric bulkorthoto N. These substituents have a negligible impact on luminescence energies of the complexes but serve to modulate the rotation barriers along the metal–ligand coordinate bond. The geometric arrangement of ligands (syn‐ oranti‐conformer) in complexes with alkyl substituents were found to differ, beingsynin the solid state versusantiin solution as revealed by crystallographic analysis and nuclear magnetic resonance spectroscopy. In addition, calculations were performed to determine potential energy surfaces for different conformations of the three complexes to provide a theoretical evaluation of rotation barriers around the metal–ligand bond axis. The relationship between rotation barriers and photophysical properties demonstrate that rates for nonradiative decay decrease with increasing bulk of the substituents on the carbazolyl ligand.
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SMARTpy: A Python Package for the Generation of Cavity-Specific Steric Molecular Descriptors and Applications to Diverse Systems
Steric molecular descriptors designed for machine learning (ML) applications are critical for connecting structure-function relationships to mechanistic insight. However, many of these descriptors are not suitable for application to com-plex systems, such as catalyst reactive site pockets. In this context, we recently disclosed a new set of 3D steric molecular descriptors that were originally designed for dirhodium(II) tetra-carboxylate catalysts. Herein, we expand the Spatial Molding for Rigid Targets (SMART) descriptor toolkit by releasing SMARTpy; an automated, open-source Python API package for computational workflow integration of SMART descriptors. The impact of the structure of the molecular probe for generation of SMART descriptors was analyzed. Resultant SMART descriptors and pocket features were found to be highly dependent upon probe selection, and do not scale linearly. Flexible probes with smaller substituents can explore narrow pocket regions resulting in a higher resolution pocket imprint. Macrocyclic probes with larger substituents are more applicable to larger cavities with smooth boundaries, such as dirhodium paddlewheel complexes. In these cases, SMARTpy provides comparable descriptors to the original calculation method using UCSF Chimera. Finally, we analyzed a series of case studies demonstrating how SMART descriptors can impact other areas of catalysis, such as organocatalysis, biocatalysis, and protein pocket analysis.
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- Award ID(s):
- 2154502
- PAR ID:
- 10639361
- Publisher / Repository:
- ChemRxIv
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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