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ACS Editors' Choice! Untangling the Condensation Network of Organosiloxanes on Nanoparticles...

posted Aug 25, 2014, 8:57 AM by Daniel Lee   [ updated Oct 1, 2014, 1:30 AM ]


Untangling the Condensation Network of Organosiloxanes on Nanoparticles using 2D 29Si-29Si Solid-State NMR enhanced by Dynamic Nuclear Polarization

Silica (SiO2) nanoparticles (NPs) were functionalized by silanization to produce a surface covered with organosiloxanes. Information about the surface coverage and the nature, if any, of organosiloxane polymerization, whether parallel or perpendicular to the surface, is highly desired. To this extent, two-dimensional homonuclear 29Si solid-state NMR could be employed. However, owing to the sensitivity limitations associated with the low natural abundance (4.7%) of 29Si and the difficulty and expense of isotopic labeling here, this technique would usually be deemed impracticable. Nevertheless, we show that recent developments in the field of dynamic nuclear polarization under magic angle spinning (MAS-DNP) could be used to dramatically increase the sensitivity of the NMR experiments, resulting in a timesaving factor of ∼625 compared to conventional solid-state NMR. This allowed the acquisition of previously infeasible data. Using both through-space and through-bond 2D 29Si–29Si correlation experiments, it is shown that the required reaction conditions favor lateral polymerization and domain growth. Moreover, the natural abundance correlation experiments permitted the estimation of 2JSi–O–Si-couplings (13.8 ± 1.4 Hz for surface silica) and interatomic distances (3.04 ± 0.08 Å for surface silica) since complications associated with many-spin systems and also sensitivity were avoided. The work detailed herein not only demonstrates the possibility of using MAS-DNP to greatly facilitate the acquisition of 2D 29Si–29Si correlation spectra but also shows that this technique can be used in a routine fashion to characterize surface grafting networks and gain structural constraints, which can be related to a system’s chemical and physical properties.