Heterojunctioned ZnO/Bi₂S₃ nanocomposites were prepared via a facile solvothermal method. The obtained photocatalysts were characterized by X-ray powder diffraction (XRD), Scanning electron microscopy (SEM), High resolution transmission electron microscopy (HRTEM), X-ray photoelectron spectroscopy (XPS), UV-Vis diffuse reflectance spectroscopy (DRS), and Photoelectrochemical and Photoluminescence spectroscopy (PL), respectively. The results showed that ZnO/Bi₂S₃ composites exhibited the sandwiched-like structure, where ZnO nanoparticles were randomly embedded between Bi₂S₃ nanoflakes. The performance of photocatalytic Cr(VI) reduction under visible light indicated that ZnO/Bi₂S₃ composites exhibited high-efficiency photocatalytic activity in comparison with either Bi₂S₃ or ZnO. The 5%-ZnO/Bi₂S₃ photocatalyst removed 96% of Cr(VI) within 120 min at 20 mg/L initial concentration of Cr(VI). The enhanced performance of ZnO/Bi₂S₃ photocatalysts could be ascribed to the increased light harvesting and the effective separation and transfer of the photogenerated charge carriers across the heterojunction interface of the ZnO/Bi₂S₃ composite. This work could pave the way for the design of new hetero-structured materials and has great potential in environmental remediation.

Nickel-doped titanium dioxide (NIT) with different nickel contents (0.1–1.0 wt%) was prepared via the sol–gel method, combined with mechanical ball milling. X-ray diffraction (XRD), scanning electron microscopy (SEM), and UV–Vis diffuse reflectance spectroscopy (DRS) were employed to characterize the crystalline structure, morphological characteristics, and optical properties of the samples. The photocatalytic activity was evaluated through the photocatalytic degradation of methylene blue (MB) under visible light and nitric oxide (NO) under simulated sunlight. The XRD results show that all the catalysts retain the anatase phase, confirming that nickel doping does not alter the crystalline structure of TiO₂. NIT catalysts exhibited a plate-like morphology due to the ball milling treatment of the precursors. The DRS analysis revealed that nickel modification induced a redshift in the absorption edge of TiO₂ and enhanced the visible-light absorption. The photocatalytic tests demonstrated that 0.5 wt% NIT and 0.7 wt% NIT exhibited the highest photocatalytic activity for MB degradation, achieving degradation rates of 93.1% and 91.4% after 60 min, respectively. Moreover, 0.7 wt% NIT showed the optimal NO conversion efficiency of 45.4% after 30 min. The improved photocatalytic performance of the sample is attributed to enhanced visible-light absorption, reduced charge recombination, and a high specific surface area. This study provides a facile strategy for synthesizing Ni-doped TiO₂ nanoplates based on the sol–gel method, which is scalable in regard to the industrial production of efficient photocatalysts.

Teachers and students are the two basic elements in educational activities. Students are educated but are not exactly passive recipients of education. With subjective initiative, all educational impacts must be through the initiative of students to achieve the desired effect. Therefore, all activities of education must start from mobilizing students’ initiative and motivation so that they have sufficient motivation to learn actively and well. The effective analysis of employment data, at the statistical level of data analysis, is a favorable basis to support the influence of teachers on students. However, most of the previous methods are C4.5 algorithms, decision tree generation algorithms based on rough sets, etc., which are commonly used for employment data analysis. None of them can sufficiently deal with the problem of different decision accuracy requirements and noise adaptability. In this paper, we analyze the employment data of a university in 2012 as an example and compare the analysis results with those of the C4.5 algorithm and decision tree generation algorithm based on a rough set. The results show that the decision tree algorithm based on the multiscale rough set model generates a simple decision tree structure. In addition, our methods do not have indistinguishable datasets and are fast in terms of computing. This study provides an effective guide to the relevance of teachers’ cognitive abilities and teaching motivations for students’ employment.

In order to prepare alkyl-functionalized reduced graphene oxide more simply, economically and environmentally, we adopt a two-step method of first reduction and then surface grafting. Graphite oxide (GtO) is first exfoliated to thermally-reduced graphene oxide (TRGO) and then, in a heat-induced solid-state reaction, converted to lauryl-functionalized TRGO (LTRGO). During the second step, lauryl radicals generated from the decomposition of lauroyl peroxide (LPO) open the epoxide rings on TRGO, covalently grafting the alkyl chains. The average water contact angle of LTRGO is 135.5°, and it disperses stably in base oil without surfactants or other additives. Four-ball test results show when the dosage of LTRGO is 75 mg/L, the average friction coefficient and wear scar diameter of the Formosa Plastics base oil (100 N) are decreased by 20.8% and 15.4%, respectively. The morphology and element analysis after ball-on-disk friction tests showed that the stable LTRGO physical friction adsorption film and metal oxide friction chemical reaction film could be formed between the friction pairs, thus reducing the friction wear.