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Characterization of Nanocrystal Size Distribution using Raman Spectroscopy with a Multi-particle Phonon Confinement Model
Published on: August 22, 2015
Trends in the Raman spectra of silica prenucleation clusters revealed through experiments and DFT
Fileto Rodríguez1, Ionut Tranca1, Pablo Beato2
1General Chemistry ALGC - Materials Modelling Group, Vrije Universiteit Brussel, Pleinlaan 2, Brussel, Belgium.
Abstract:
Understanding the early stages of silica nucleation in solution remains a major challenge due to the challenging characterization of the involved species. Raman spectroscopy offers a powerful alternative provided that quality reference spectra are available. In this work, we present a systematic computational study of the Raman spectra of silica prenucleation oligomers, focusing on the structures characterized in the literature by 29Si NMR and ESI-MS. Using our static protocol based on density functional theory (DFT), we analyzed the influence of structural features, particularly the presence of 3- and 4-membered rings, as well as the deprotonation state on the position of the main Raman bands. Moreover, we experimentally measured the Raman spectra of several silicate solutions presenting different polymerization degrees. By combining our experimental and theoretical results we constrain the families of silica species most compatible with the experimental spectra. Our findings reveal a strong correlation between vibrational localization and spectral position, where 3-membered rings in the structures shift Raman bands to higher frequencies, while 4-membered rings and further condensation lead to lower wavenumbers. The effect of acidity and deprotonation on the Raman spectra is also analyzed. We identify the 920 cm-1 band as a spectroscopic marker of the doubly deprotonated monomer (H2SiO42-), relevant for silica speciation in high-pH solutions. The resulting spectral database provides a practical reference for experimental Raman studies and an interpretative framework that surpasses existing approaches in capturing vibrational complexity, based on the study of the rings in the backbone of the structure.
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