A switchable cross-species liquid-repellent surface is developed that can rapidly switch between two distinct liquid-repellent modes: i) the superhydrophobic mode, modeled after lotus leaves, and ii) the slippery mode, modeled after the pitcher-plant peristome. Adaptive liquid repellency and programmable fog harvesting are demonstrated as application examples for the new switchable surface.

This article presents a facile approach to centimeter-scale colloidal photonic crystals (PCs) with narrow stopbands assembled on low-adhesive superhydrophobic substrates. The full-width-at-half-maxima of the stopbands are just 12 nm. The narrow stopbands of colloidal PCs are ascribed to the combined effects of perfectly ordered assembly structure, large-scale crack elimination, decreased void fraction, and sufficient thickness of the colloidal PCs. These properties result from a self-assembly process on a low-adhesive superhydrophobic substrate. Latex suspension on this substrate displays a receding three-phase contact line during evaporation, which releases tensile stress induced by latex shrinkage and results in complete elimination of cracks in the colloidal PCs. Furthermore, the simultaneous assembly of latex particles on the outermost layer of a spread liquid film contributes to the perfectly ordered assembly structure. This facile fabrication of centimeter-scale colloidal PCs with narrow stopbands will offer significant insights into the design and creation of novel optical devices.

A critical requirement for the successful recognition of multiple analytes is the acquisition of abundant sensing information. However, for this to be achieved requires massive chemical sensors or multiplex materials, which complicates the multianalysis. Thus, there is a need to develop a strategy for the facile and efficient recognition of multiple analytes. Herein, we explore the angle-dependent structural colors of photonic crystals to provide abundant optical information, thereby generating a rainbow-color chip to realize the convenient recognition of multiple analytes. By simply using a multiangle analysis method, the monophotonic crystal matrix chip can differentially enhance fluorescence signals over broad spectral ranges, thereby resulting in abundant sensing information for highly efficient multiple analysis. Twelve saccharides with similar structures, as well as saccharides in different concentrations and mixtures, were successfully discriminated.