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Stabilization of TiO2 Nanoparticles in Complex Medium through a pH Adjustment Protocol
Link to Journal Abstract
Preparing TiO2 nanoparticle (NP) suspensions displaying well-defined and reproducible dispersion state is a key feature to perform relevant toxicity experiments for environmental, animal, or human concerns. Relying on the evolution of surface charge with pH, and interactions between nanoparticles in their medium, we developed an optimized dispersion protocol involving a pH adjustment before addition of bovine serum albumin (BSA). It yielded highly dispersed and stable concentrated stock suspensions of TiO2 NP at pH 7. It was designed for four kinds of manufactured TiO2 nanomaterials and can be extended to a wide range of TiO2 NP. The suspensions studied here were characterized by small-angle X-ray scattering (SAXS), using a model quantitatively describing fractal aggregates. Results were correlated with dynamic light scattering (DLS) measurements. Moreover, the stability in a typical biological medium was assessed by diluting stock suspensions in Luria–Bertani (LB) medium. It resulted in highly dispersed and stable working suspensions. No sedimentation, followed by in situ DLS, was observed over 17 h for both the concentrated stock suspensions prepared according to the pH adjusted-BSA protocol and their dilution into LB medium.
In this study, the authors developed an optimized dispersion protocol involving a pH adjustment before addition of bovine serum albumin (BSA) in order to prepare TiO2 nanoparticle (NP) suspensions displaying well-defined and reproducible dispersion state, which is a key feature to perform relevant toxicity experiments for environmental, animal, or human concerns.
Peer Reviewed Journal Article
Exposure Or Hazard Target
Method Of Study
Material Analysis and Applications
Risk Exposure Group
Environmental Science & Technology, 2013, 47(2): 1057-1064
Environmental Science & Technology
Guiot C, Spalla O
Last updated on January 25, 2013
This work is supported in part by the Nanoscale Science and Engineering Initiative of the National Science Foundation
under NSF Award Number EEC-0118007.
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