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Characterizing the Dynamic Behavior of Nano-TiO2 Agglomerates in Suspensions by Photocorrelation Spectroscopy

Published

Author(s)

I-Hsiang Tseng, Stephanie S. Watson, Li Piin Sung

Abstract

Metal oxide nanoparticles are small but easily form agglomerates in suspension, depending on the strength of particle-particle and particle-media interactions. To understand the agglomeration behavior of nanoparticles in media and relate to it to product performance testing, measurement methods are desired to characterize highly scattering metal oxide nanoparticle suspensions without dilution. In this paper, we describe the advantages of using photocorrelation spectroscopy (PCS) in a backscattering detection configuration to carry out a realistic agglomerate size measurement in multiple scattering media found in most metal oxide nanoparticle suspensions. The dynamic behavior of nano-titanium dioxide (TiO2) particles in buffer solutions of different chemical composition and pH values was investigated as a sample system using PCS. The resulting autocorrelation functions (AF) at different time intervals, particle concentrations, and pH values were measured at several detection angles. The AF exhibits a multi-mode relaxation time feature and the calculated hydrodynamic diameters strongly depended on media composition and detection angle. This result indicates that the size and dispersion of nano-TiO2 agglomerates are significantly affected by solution media. A measurement protocol for determining size and dispersion of metal oxide particles in media is proposed and related to a performance test found in industry.
Citation
Journal of Nanoparticle Research

Keywords

photocorrelation spectroscopy, nanoparticle, agglomerate, non-ergodic, TiO2

Citation

Tseng, I. , Watson, S. and Sung, L. (2009), Characterizing the Dynamic Behavior of Nano-TiO2 Agglomerates in Suspensions by Photocorrelation Spectroscopy, Journal of Nanoparticle Research, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=902458 (Accessed April 19, 2024)
Created April 21, 2009, Updated October 12, 2021