Efficient fabrication of tilt micro/nanopillars on polypropylene surface with robust superhydrophobicity for directional water droplet rebound.

The directional rebound and transport of water droplets plays an important role in microfluidic devices, anti-fogging, and water harvesting. Herein, an extrusion compression molding and directional stretch demolding method was used to prepare a polypropylene (PP) surface with tilt micro/nanopillars with a contact angle of 157 ± 3°. The rolling angle is the highest (9 ± 4°) when the direction of rotation is opposite the tilt direction of the micro/nanopillars, showing excellent water repellency and anisotropy of the surface. Compared with the position of the first collision of the water droplet, the position of the second collision shifted ∼1.5 mm along the tilt direction of the micro/nanopillars, driven by the surface tension component during the collision. The directional rebound behavior is controlled by the droplet energy and the tilt angle. The micro/nanopillars demonstrate excellent self-cleaning property and mechanical durability, which shows the possibility of their practical engineering applications.

Discrimination of Chinese teas with different fermentation degrees by stepwise linear discriminant analysis (S-LDA) of the chemical compounds.

This study aimed to construct objective and accurate analytical models of tea categories based on their polyphenols and caffeine. A total of 522 tea samples of 4 commonly consumed teas with different fermentation degrees (green tea, white tea, oolong tea, and black tea) were analyzed by high-performance liquid chromatography (HPLC) coupled with spectrophotometry, utilizing ISO 14502, as analytical tools. The content of polyphenols and caffeine varied significantly according to differently fermented teas, indicating that these active constituents may discriminate fermentation degrees effectively. By principal component analysis (PCA) and stepwise linear discriminant analysis (S-LDA), the vast majority of tea samples could be successfully differentiated according to their chemical markers. This study yielded three discriminant functions with the capacity to simultaneously discriminate the four tea categories with a 97.8% correct rate. In classification of oolong and other teas, there were one discriminant function and two equations with best discriminant capacity. Furthermore, the classification of different degrees of fermentation of oolong and external validation achieved the desired results. It is suggested that polyphenols and caffeine are the distinct variables to establish internationally recognized models of teas.