Facile construction of Z-scheme AgCl/Bi3TaO7 photocatalysts for effective removal of tetracycline under visible-light irradiation.

A string of AgCl/Bi3TaO7 two-component composite was synthesized by hydrothermal and deposition-precipitation process initially. The photocatalytic activities of mixed-phase AgCl/Bi3TaO7 were evaluated toward the decomposition of tetracycline (TC). Among these as-prepared materials, AgCl/Bi3TaO7 nanocomposites when the molar ratio of baked materials between AgCl and Bi3TaO7 was 1:5 presented the optimal photocatalytic quantum efficiency for TC dissociation (86.82%) with visible-light exposure, which was 1.69 and 2.38 folders higher than that of single Bi3TaO7 and AgCl, respectively. What is more, it illustrated that the photo-generated carriers were markedly isolated on account of the formation of heterojunction confirmed by EIS analysis. Meanwhile, radical trapping experiments implied that the photo-induced holes (h+), hydroxyl radical (·OH), and superoxide radical (·O2-) were the major active species. The escalated photocatalytic activity could be ascribed to the unique construction of Z-scheme AgCl/Bi3TaO7 heterojunction, which could expedite charge separation and transmission, cement light absorption capability and retain the strong redox ability of photo-generated electrons and holes. Our finding suggests that AgCl/Bi3TaO7 nanocomposites possess great potential for photocatalytic oxidation of residual TC in the wastewater effluents and the reported strategy can contribute to the development of novel high-performance photocatalyst.

Accumulative Quantization for Approximate Nearest Neighbor Search.

To further improve the approximate nearest neighbor (ANN) search performance, an accumulative quantization (AQ) is proposed and applied to effective ANN search. It approximates a vector with the accumulation of several centroids, each of which is selected from a different codebook. To provide accurate approximation for an input vector, an iterative optimization is designed when training codebooks for improving their approximation power. Besides, another optimization is introduced into offline vector quantization procedure for the purpose of minimizing overall quantization errors. A hypersphere-based filtration mechanism is designed when performing AQ-based exhaustive ANN search to reduce the number of candidates put into sorting, thus yielding better search time efficiency. For a query vector, a self-centered hypersphere is constructed, so that those vectors not lying in the hypersphere are filtered out. Experimental results on public datasets demonstrate that hypersphere-based filtration can improve ANN search time efficiency with no weakening of search accuracy; besides, the proposed AQ is superior to the state of the art on ANN search accuracy.