Janus droplet microreactors for preparing polyaniline/AgCl nanocomposites.

We report a novel method to conduct heterogeneous reactions using aqueous-ionic liquid Janus microdroplets as a series of isolated bi-phasic microreactors where AgCl@polyaniline core-shell nanoparticles are successfully synthesized accompanied by polyaniline nano-needles, and enhanced visualization of reaction progression through the color changes in Janus droplets is achieved.

Study of molecular interaction and texture characteristics of hydrocolloid-mixed alginate microspheres: As a shell to encapsulate multiphase oil cores.

This work investigates the molecular interaction of hydrocolloids (xanthan gum (XG), hydroxyethyl cellulose (HEC), carbomer (CBM) and hymagic™-4D (HA)) with sodium alginate (SA) in microspheres in detail. The molecular interaction of hydrocolloids with SA are demonstrated by the rheological property analysis of the mixed solutions as well as the morphology structure and texture characteristics studies of the microspheres. It is found that the hydrocolloids (XG, HEC and CBM) with branches or capable to coil are able to form complex networks with SA through molecular interactions which hinders the free diffusion of calcium ions and changes the texture characteristics of microspheres. In addition, the mixed solutions (SA-XG and SA-HEC) with complex networks and do not have a chelating effect on calcium ions are used to form the shell of the microcapsules through droplet microfluidic technology, and stable with soft microcapsules encapsulating multiphase oil cores have been successfully prepared. At the same time, the textural properties of microcapsules are quantized, which are related to human sensory properties. The developed stable and soft microcapsules which have the properties of sensory comfort are expected to be applied in the personal care industry and a variety of fields.

The relationship between air quality and MODIS aerosol optical depth in major cities of the Yangtze River Delta.

The AOD derived from the MODIS deep blue(DB) algorithm and AQI were used to investigate the correlation between AOD and AQI in seven major cities of Yangtze River Delta (YRD) from January to December 2019. The accuracy of MODIS AOD was validated by AERONET. Moreover, the AOD and AQI were studied to explore the annual and seasonal distribution characteristics, and the correlation analysis was carried out using five regression models. It was found: Ⅰ) There was a significant correlation between AOD and AERONET data (R2 ˃ 0.80, RMSE = 0.106, and MAE = 0.089). Ⅱ) The highest AQI was observed in winter (83), followed by spring (76), autumn (74), and summer (72). Ⅲ) The monthly average AOD showed noticeable seasonal variations, which reached the highest in summer (0.91) and the lowest in winter (0.69), followed by spring and autumn. Ⅳ) Among the five models, the cubic model obtained the best results with R2 ˃ 0.55. In the sub-seasonal regression model, the cubic model outperformed other models in spring (R2 ˃ 0.57), summer (R2 ˃ 0.76) and autumn (R2 ˃ 0.38). However, in winter the composite model outperformed others (R2 ˃ 0.68). Ⅴ) Considering annual data, the AOD can predict over 70% of the variations in AQI (0.41＜R2 ＜0.81). These results demonstrate the feasibility of AOD derived from the MODIS DB algorithm in AQI prediction. The method used in this study can be applied as an aid for air pollution control programs in different regions.