Publication Type Journal Article
Title Application of Turbiscan in the homoaggregation and heteroaggregation of copper nanoparticles
Authors Xuejiao Qi Ya nan Dong Hongtao Wang Chen Wang Fengting Li Ryan Holt Paul Cooke Miguel Brown
Groups G1 G3
Journal COLLOIDS AND SURFACES A-PHYSICOCHEMICAL AND ENGINEERING ASPECTS
Year 2017
Month December
Volume 535
Number
Pages 96-104
Abstract With the development of industries, copper nanoparticles (Cu NPs) have been abundantly discharged into natural water and may threaten the safety of aquatic environments. The stability (such as homoaggregation and heteroaggregation) of Cu NPs in aqueous phase may affect their toxicity. Turbiscan, including three kinds of data processing methods (transmitted intensity (T), variation of average transmitted intensity (Delta T) and Turbiscan stability index (TSI), were used to investigate the homoaggregation and heteroaggregation of Cu NPs with humic acid (HA) and kaolin in aqueous phase. T and TSI were used to analyze Cu NPs-kaolin and Cu NPs-HA-kaolin systems, respectively, whereas T and Delta T were used to analyze Cu NPs and Cu NPs-HA systems. Results showed that the stability of the system is influenced by the dissolution and sedimentation of Cu NPs, and the aggregation and sedimentation of Cu NPs, HA and kaolin. When pH is 4, the dissolution of Cu NPs is the main factor affecting the system stability. Kaolin may reduce the stability of system by sedimentation or impeding the dissolution of Cu NPs. When pH is 8, the aggregation and sedimentation of Cu NPs mainly affect the system stability. Kaolin renders the system unstable by promoting the aggregation of Cu NPs. In addition, HA improves the stability of the system by inhibiting the aggregation of Cu NPs and kaolin when pH = 4 and 8. Ionic strength reduces the stability of system by condensing electric double layer. Therefore, Turbiscan can be used to study both homoaggregation and heteroaggregation in a relatively long period (12 h), and three kinds of data processing methods can be applied based on the properties of the samples.
DOI http://dx.doi.org/10.1016/j.colsurfa.2017.09.015
ISBN
Publisher
Book Title
ISSN 0927-7757
EISSN 1873-4359
Conference Name
Bibtex ID ISI:000413629000013
Observations
Back to Publications List