Phosphine and Selenoether peri -Substituted Acenaphthenes and Their Transition-Metal Complexes: Structural and NMR Investigations.
Lutao ZhangFrancesca A ChristieAnna E TarczaHelena G LancasterLaurence J TaylorMichael BűhlOlga L MalkinaJ Derek WoollinsCameron L Carpenter-WarrenDavid Bradford CordesAlexandra M Z SlawinBrian A ChalmersPetr KilianPublished in: Inorganic chemistry (2023)
A series of peri -substituted acenaphthene-based phosphine selenoether bidentate ligands Acenap( i Pr 2 P)(SeAr) ( L1 - L4 , Acenap = acenaphthene-5,6-diyl, Ar = Ph, mesityl, 2,4,6-trisopropylphenyl and supermesityl) were prepared. The rigid acenaphthene framework induces a forced overlap of the phosphine and selenoether lone pairs, resulting in a large magnitude of through-space 4 J PSe coupling, ranging from 452 to 545 Hz. These rigid ligands L1 - L4 were used to prepare a series of selected late d-block metals, mercury, and borane complexes, which were characterized, including by multinuclear NMR and single-crystal X-ray diffraction. The Lewis acidic motifs (BH 3 , Mo(CO) 4 , Ag + , PdCl 2 , PtCl 2 , and HgCl 2 ) bridge the two donor atoms (P and Se) in all but one case in the solid-state structures. Where the bridging motif contained NMR-active nuclei ( 11 B, 107 Ag, 109 Ag, 195 Pt, and 199 Hg), J PM and J SeM couplings are observed directly, in addition to the altered J PSe in the respective NMR spectra. The solution NMR data are correlated with single-crystal diffraction data, and in the case of mercury(II) complexes, they are also correlated with the solid-state NMR data and coupling deformation density calculations. The latter indicate that the through-space interaction dominates in free L1 , while in the L1HgCl 2 complex, the main coupling pathway is via the metal atom and not through the carbon framework of the acenaphthene ring system.
Keyphrases
- solid state
- electronic health record
- big data
- quantum dots
- room temperature
- molecular dynamics
- particulate matter
- density functional theory
- highly efficient
- computed tomography
- magnetic resonance imaging
- machine learning
- air pollution
- climate change
- ionic liquid
- heavy metals
- human health
- magnetic resonance
- deep learning
- fluorescent probe