Modeling the Interfacial Energy of Surfactant-Free Amphiphilic Janus Nanoparticles from Phase Inversion in Pickering Emulsions.
Dalin WuBernard P BinksAndrei HonciucPublished in: Langmuir : the ACS journal of surfaces and colloids (2017)
Determining the interfacial energy of nanoparticles is very challenging via traditional methods that first require measuring the contact angle of several liquids of a sessile drop on pellets or capillary rise in powder beds. In this work, we propose an alternative way to model the interfacial energy of nanoparticles directly from emulsion phase inversion data in Pickering emulsions. This could establish itself as a universal and facile way to determine the polarity of nanoparticles relative to a series of standard particles without the need to measure contact angles. Pickering emulsions of several oils in water were generated with a series of snowman-like Janus nanoparticles (JNPs), whose polarity gradually increased with the size of the more polar lobe. Depending on the oil to water ratio and the JNPs lobe size, oil-in-water (o/w) or water-in-oil (w/o) Pickering emulsions were obtained and the affinity of the JNPs to either water or oil can be inferred from the evolution of the emulsion phase inversion curves with these parameters. We further demonstrate that by adopting a simple model for the work of adhesion of JNPs with the water and oil phases, one can quantitatively calculate the relative interfacial energy change of the JNPs with the liquid. In addition, a knowledge of the interfacial energy of nanoparticles is useful for employing these in suspension polymerization to create surface nanostructured materials. The o/w and w/o Pickering emulsions obtained from monomers, such as styrene, could be polymerized, resulting in colloidosomes or hollow-like materials. The hollow materials exhibited a rather high volume storage capacity for the aqueous phase for extended periods of time, which could be released upon microwaving, making them ideal for use in long-term storage applications of various water-soluble actives.
Keyphrases
- ionic liquid
- molecular dynamics simulations
- fatty acid
- water soluble
- walled carbon nanotubes
- perovskite solar cells
- escherichia coli
- magnetic resonance imaging
- electronic health record
- pseudomonas aeruginosa
- metal organic framework
- machine learning
- deep learning
- high resolution
- data analysis
- capillary electrophoresis