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In comparison with the poor stability, high cost, and difficult preparation of conventional natural enzymes, nanozymes have the obvious advantages of excellent stability, high catalytic activity, multifunctionality, and large-scale preparation. Herein, a series of Fe3O4 NPs-based magnetic composite with dual enzyme-like activities (peroxidase and oxidase) were successfully synthesized by the microwave-assisted method. Among them, the Fe3O4/Ag Au nanocomposite showed the highest peroxidase-like activity due to the synergistic catalytic effect of Ag and Au bimetallic modifications. Enzyme kinetic studies revealed good kinetic parameters of the Fe3O4/Ag Au nanocomposite for peroxidase, and it also exhibited a higher affinity for TMB compared to natural horseradish peroxidase. In addition, a method for effective dye degradation and selective detection of glutathione was constructed based on its peroxidase-like activity. Importantly, the remarkable magnetic separation property and the outstanding stability proved the extensive application prospects of the nanozymes in the remediation of water pollution and some biomarker-specific detection. [ABSTRACT FROM AUTHOR]

Cobalt coordinated covalent organic frameworks have attracted increasing interest in the field of CO2 photoreduction to CO, owing to their high electron affinity and predesigned structures. However, achieving high conversion efficiency is challenging since most Co related coordination environments facilitate fast recombination of photogenerated electron-hole pairs. Here, we design two kinds of Co-COF catalysts with oxygen coordinated Co atoms and find that after tuning of coordination environment, the reported Co framework catalyst with Co-O4 sites exhibits a high CO production rate of 18000 µmol g−1 h−1 with selectivity as high as 95.7% under visible light irradiation. From in/ex-situ spectral characterizations and theoretical calculations, it is revealed that the predesigned Co-O4 sites significantly facilitate the carrier migration in framework matrixes and inhibit the recombination of photogenerated electron-hole pairs in the photocatalytic process. This work opens a way for the design of high-performance catalysts for CO2 photoreduction. A class of inexpensive aminoanthraquinone organic dyes are shown to facilitate visible-light-driven CO2 reduction. Overall reaction efficiencies were found to be optimal when both electron donating and accepting groups were on a single dye molecule. [ABSTRACT FROM AUTHOR]

In e-learning, the increasing number of learning resources makes it difficult for learners to find suitable learning resources. In addition, learners may have different preferences and cognitive abilities for learning resources, where differences in learners' cognitive abilities will lead to different importance of learning resources. Therefore, recommending personalized learning paths for learners has become a research hotspot. Considering learners' preferences and the importance of learning resources, this paper proposes a learning path recommendation algorithm based on knowledge graph. We construct a multi-dimensional courses knowledge graph in computer field (MCCKG), and then propose a method based on graph convolutional network for modeling high-order correlations on the knowledge graph to more accurately capture learners' preferences. Furthermore, the importance of learning resources is calculated by using the characteristics of learning resources in the MCCKG and learners' characteristics. Finally, by weighting the two factors of learners' preferences and the importance of learning resources, we recommend the optimal learning path for learners. Our method is evaluated from the aspects of learner's satisfaction, algorithm effectiveness, etc. The experimental results show that the method proposed in this paper can recommend a personalized learning path to satisfy the needs of learners, thus reducing the workload of manually planning learning paths. [ABSTRACT FROM AUTHOR]