2021
DOI: 10.1002/ange.202110417
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Synthesis of Functionalized Silsesquioxane Nanomaterials by Rhodium‐Catalyzed Carbene Insertion into Si−H Bonds

Abstract: We report carbene insertion into Si À H bonds of polyhedral oligomeric silsesquioxanes (POSS) for the synthesis of highly functionalized siloxane nanomaterials. Dirhodium(II) carboxylates catalyze insertion of aryl-diazoacetates as carbene precursors to afford POSS structures containing both ester and aryl groups as orthogonal functional handles for further derivatization of POSS materials. Four diverse and structurally varied silsesquioxane core scaffolds with one, three, or eight SiÀH bonds were evaluated wi… Show more

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Cited by 1 publication
(3 citation statements)
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“…The shoulder signal at around −18 ppm potentially could be attributed to a signal of the D structures having different distance distributions to the T structures. [44][45][46][47][48][49] The MAS solid-state 13 C-NMR spectrum of Py-CSSE exhibits a signal at 0.9 ppm, corresponding to the sp 3 methyl carbon of siloxane chains. The spectrum also showed broad multiple signals around 132-134 ppm, corresponding to sp 2 carbons derived from the abundant vinyl groups of OVS (Fig.…”
Section: Synthesis and Characterizationmentioning
confidence: 99%
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“…The shoulder signal at around −18 ppm potentially could be attributed to a signal of the D structures having different distance distributions to the T structures. [44][45][46][47][48][49] The MAS solid-state 13 C-NMR spectrum of Py-CSSE exhibits a signal at 0.9 ppm, corresponding to the sp 3 methyl carbon of siloxane chains. The spectrum also showed broad multiple signals around 132-134 ppm, corresponding to sp 2 carbons derived from the abundant vinyl groups of OVS (Fig.…”
Section: Synthesis and Characterizationmentioning
confidence: 99%
“…Importantly, the signals associated with pyrene are absent from the spectrum. This is due to the limited sensitivity of the MAS solid-state 13 C-NMR technique, which inhibited the detection of signals resulting from the small amount of Mono-PySQ introduced into Py-CSSE (Fig. S2 †).…”
Section: Synthesis and Characterizationmentioning
confidence: 99%
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