The global need for clean water requires sustainable technology for purifying contaminated water. Highly efficient solar-driven photodegradation is a sustainable strategy for wastewater treatment. In this work, we demonstrate that the photodegradation efficiency of micropollutants in water can be improved by ∼2–24 times by leveraging polymeric microlenses (MLs). These microlenses (MLs) are fabricated from the in situ polymerization of surface nanodroplets. We found that photodegradation efficiency (η) in water correlates approximately linearly with the sum of the intensity from all focal points of MLs, although no difference in the photodegradation pathway is detected from the chemical analysis of the byproducts. With the same overall power over a given surface area, η is doubled by using ordered ML arrays, compared to heterogeneous MLs on an unpatterned substrate. A higher η from ML arrays may be attributed to a coupled effect from the focal points on the same plane that creates high local concentrations of active species to further speed up the rate of photodegradation. As a proof-of-concept for MLs-enhanced water treatment, MLs were formed on the inner wall of glass bottles that were used as containers for water to be treated. Three representative micropollutants (norfloxacin, sulfadiazine, and sulfamethoxazole) in the bottles functionalized by MLs were photodegraded by 30%–170% faster than in normal bottles. Our findings suggest that the MLs-enhanced photodegradation may lead to a highly efficient solar water purification approach without a large-sized solar collector. Such an approach may be particularly suitable for portable transparent bottles in remote regions.

This work demonstrates an original and ultrasensitive approach for surface‐enhanced Raman spectroscopy (SERS) detection based on evaporation of self‐lubricating drops containing silver supraparticles. The developed method detects an extremely low concentration of analyte that is enriched and concentrated on sensitive SERS sites of the compact supraparticles formed from drop evaporation. A low limit of detection of 10−16 m is achieved for a model hydrophobic compound rhodamine 6G (R6G). The quantitative analysis of R6G concentration is obtained from 10−5 to 10−11 m. In addition, for a model micro‐pollutant in water triclosan, the detection limit of 10−6 m is achieved by using microliter sample solutions. The intensity of SERS detection in this approach is robust to the dispersity of the nanoparticles in the drop but became stronger after a longer drying time. The ultrasensitive detection mechanism is the sequential process of concentration, extraction, and absorption of the analyte during evaporation of self‐lubrication drop and hot spot generation for intensification of SERS signals. This novel approach for sample preparation in ultrasensitive SERS detection can be applied to the detection of chemical and biological signatures in areas such as environment monitoring, food safety, and biomedical diagnostics.

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Sensing and detecting nitroaromatics (NAs) are essential for environmental, health, and safety reasons. Graphene quantum dots (GQDs) respond to the presence of NAs by a well-understood fluorescence quenching mechanism. However, despite the relative simplicity of fluorescence-based sensing, the limit of detection (LoD) can compare unfavorably with other methods. Here, we show that the LoD for sensors based on GQDs can be lowered by orders of magnitude using a droplet-based analyte partitioning effect. While previous efforts have attempted to improve the intrinsic GQD sensitivity via surface functionalization and size control, we show that a major improvement can be attained by changing from a bulk solution to droplet-based sensing of 2,4-dinitrotoluene and nitrobenzene. Moreover, the method is compatible with sensing from an aqueous solvent and has broader implications for many fluorescence-quenching-based sensing strategies that could benefit from partition-related enhancements.