We develop a closed-loop solution to design, to optimize and to expansively fabricate the desirable quasi-random nanostructures(QRNs). In contrast to the current non-deterministic manufacturing process that cannot be deployed in large dimensionality, we innovatively import binary quasi-random sequences to generate QRNs deterministically without the restriction of the pattern size. Note that all 2D quasi-random patterns such as particle and channel types can also be converted into binary sequences by digitizing their 2D pattern images. Moreover, to bridge the gap between the nanostructure spatial arrangement and its optical performance, the star discrepancy calculation is employed as a guidance to evaluate and to optimize these binary QNRs given that the nanostructures’ uniformity is a key factor for light trapping. Finally, these binary QRNs are generated in a “pit-and-land” morphology so that they can be facilely and directly fabricated via optical disk recording technology.
As the known of the Shockley-Queasier limit, over 90% of widely used silicon crystalline based solar cell only achieve 30% theoretical efficiency. To maximize the light-harvesting, the solar cell’s light-trapping structures must be broadband, omnidirectional, and polarization-insensitive. Quasi-random structures emerge as an ideal candidate since they combine the broadband wide-angle absorption enhancement and strong, customizable enhancement for desired wavelength windows. Herein, we demonstrated a kind of designed quasi-random structures, which were designed by topology optimization based on mathematical algorithms and directly fabricated the final products to achieve high efficiency. The best structure (Rudin-Shapiro) could reduce 11% on reflectance and improve 14% short circuit current which led 13% PCE improvement. Meanwhile, the results also exhibited ~10% efficiency improvement in a wide incident angle range (0-65 degree).
Organophosphates (OPs) are a class of pesticides and chemical warfare, several of which are highly toxic. Based on the newest report, there are nearly three million poisonings per year resulting in two hundred thousand deaths around the world. Inspired by the Liquid Crystals (LCs)’ extraordinary properties, we employed a customized LCs sensor to detect OPs with high sensitivity & selectivity, fast response time, and reusability. As proof of our research, four different measurements were operated in the experiments: sensitivity, response time, selectivity, and reusability. The results showed that the limit of detection (LOD) of our proposed sensing method can selectively detect OPs lower to the 10ppb concentration in 25 seconds in four different vapors (OPs, Steam, Ethyl alcohol, and Methylbenzene), which was far lower than the US EPA safety levels for OPs and also faster than the other competitors. Further, the sensor can be recovered by the nitrogen gas treatment in 30 seconds.
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