This paper presents a unique synergistic behavior between a graphene oxide (GO) and graphene nanoplatelet (GnP) composite in an aqueous medium. The results showed that GO stabilized GnP colloid near its isoelectric point and prevented rapid agglomeration and sedimentation. It was considered that a rarely encountered charge-dependent electrostatic interaction between the highly charged GO and weakly charged GnP particles kept GnP suspended at its rapid coagulation and phase separation pH. Sedimentation and transmission electron microscope (TEM) micrograph images revealed the evidence of highly stable colloidal mixtures while zeta potential measurement provided semi-quantitative explanation on the mechanism of stabilization. GnP suspension was confirmed via UV-vis spectral data while contact angle measurement elucidated the close resemblance to an aqueous solution indicating the ability of GO to mediate the flocculation prone GnP colloids. About a tenfold increase in viscosity was recorded at a low shear rate in comparison to an individual GO solution due to a strong interaction manifested between participating colloids. An optimum level of mixing ratio between the two constituents was also obtained. These new findings related to an interaction between charge-based graphitic carbon materials would open new avenues for further exploration on the enhancement of both GO and GnP functionalities particularly in mechanical and electrical domains.

Lipid nanocarrier displays the advantages over conventional drug carriers as they are formulated with biodegradable and non-irritant lipids. However, the main drawbacks are the agglomeration of lipid particles, instability over storage, low drug loading, and the burst release of active ingredients. In this study, we investigated the effects of various polysorbate nonionic surfactants namely Tween 20, 40, 60, or 80 on the nanostructured lipid carrier (NLC). NLC incorporated with polysorbate nonionic surfactant was prepared by using high-pressure homogenization technique. The average size was reduced to 139.9 ± 15.8 nm in the presence of Tween 80 and remained stable in nano-size even incubated for 28 days. Encapsulation of l-ascorbic acid or Gold Tri.E 30 showed a high encapsulation efficiency of more than 75%, where the highest was Gold Tri.E in the presence of Tween 60 at 99.7%. In vitro release study showed that the release of both l-ascorbic acid and Gold Tri.E was significantly reduced in NLC with Tween as compared to bare active ingredients and NLC without Tween. In conclusion, the incorporation of Tween successfully produced a lipid nanocarrier that has the potential to be developed as a carrier of various active ingredients such as nutrients, extracts, and drugs.

The purpose of this study was to optimize the parameters involved in the production of water-soluble phytosterol microemulsions for use in the food industry. In this study, response surface methodology (RSM) was employed to model and optimize four of the processing parameters, namely, the number of cycles of high-pressure homogenization (1−9 cycles), the pressure used for high-pressure homogenization (100−500 bar), the evaporation temperature (30−70 °C), and the concentration ratio of microemulsions (1−5). All responses—particle size (PS), polydispersity index (PDI), and percent ethanol residual (%ER)—were well fit by a reduced cubic model obtained by multiple regression after manual elimination. The coefficient of determination (R²) and absolute average deviation (AAD) value for PS, PDI, and %ER were 0.9628 and 0.5398%, 0.9953 and 0.7077%, and 0.9989 and 1.0457%, respectively. The optimized processing parameters were 4.88 (approximately 5) homogenization cycles, homogenization pressure of 400 bar, evaporation temperature of 44.5 °C, and concentration ratio of microemulsions of 2.34 cycles (approximately 2 cycles) of high-pressure homogenization. The corresponding responses for the optimized preparation condition were a minimal particle size of 328 nm, minimal polydispersity index of 0.159, and <0.1% of ethanol residual. The chi-square test verified the model, whereby the experimental values of PS, PDI, and %ER agreed with the predicted values at a 0.05 level of significance.