Hypothesis: Polyoxometalates (POMs) are metal oxygen clusters with a range of interesting magnetic and catalytic properties. POMs with attached hydrocarbon chains show amphiphilic behaviour so we hypothesised that mixtures of a nonionic surfactant and anionic surfactants with a polyoxometalate cluster as headgroup would form mixed micelles, giving control of the POM density in the micelle, and which would differ in size and shape from micelles formed by the individual surfactants. Due to the high charge and large size of the POM, we suggested that these would be nonideal mixtures due to the complex interactions between the two types of surfactants. The nonideality and the micellar composition may be quantified using regular solution theory. With supplementary information provided by small-angle neutron scattering (SANS), an understanding of this unusual binary surfactant system can be established.
Experiments: A systematic study was performed on mixed surfactant systems containing polyoxometalate-headed amphiphiles (K[PWOOSi(CH)], abbreviated as PW-2C, where n = 12, 14 or 16) and hexaethylene glycol monododecyl ether (CEO). Critical micelle concentrations (CMCs) of these mixtures were measured and used to calculate the interaction parameters based on regular solution theory, enabling prediction of micellar composition. Predictions were compared to micelle structures obtained from SANS. A phase diagram was also established.
Findings: The CMCs of these mixtures suggest unusual unfavourable interactions between the two species, despite formation of mixed micelles. Micellar compositions obtained from SANS concurred with those calculated using the averaged interaction parameters for PW-2C/CEO (n = 12 and 14). We attribute the unfavourable interactions to a combination of different phenomena: counterion-mediated interactions between PW units and the unfolding of the ethylene oxide headgroups of the nonionic surfactant, yet micelles still form in these systems due to the hydrophobic interactions between surfactant tails.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.jcis.2020.06.007 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!