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This study addresses the critical challenge of integrating sustainable financial management within the framework of green economic growth in China from 1990 to 2022, underscored by rapid industrialization and environmental concerns. The primary aim is to analyze how big data technology innovations have facilitated sustainable financial practices that align with green economic objectives. The objectives include assessing the impact of these technologies on environmental sustainability, financial inclusion, and economic resilience. Using China as a case study, the research employs a longitudinal analysis to trace the evolution and integration of sustainable financial management and green economic growth, underpinned by technological advancements. Results indicate that big data technology has significantly enhanced the capacity for real-time analysis, risk assessment, and decision-making in financial institutions, leading to improved environmental and economic outcomes. Policy implications suggest that the government should foster an innovation-friendly environment that encourages the development and adoption of big data technologies, to further integrate sustainable financial management within the green growth agenda.

For studying the effect of nitriding treatment on the microstructure and wear properties of HVOF sprayed Al1-xCoCrFeNiTix(x＝0，0.125，0.250) high-entropy alloy coatings，the HVOF technology was employed to prepare Al1-xCoCrFeNiTix(x＝0，0.125，0.250) highentropy alloy coating on 35CrMo steel substrate，which were further nitrided.The effects of nitriding treatment on the microstructure and wear properties of Al1-xCoCrFeNiTix(x＝0，0.125，0.250) high-entropy alloy coating prepared by HVOF were studied via characterization methods such as SEM，XRD，3D white light interferometer and EDS.Results showed that the high-entropy alloy coating of Al1-xCoCrFeNiTix(x＝0，0.125，0.250) after nitriding treatment had a dense microstructure with a typical thermal spray coating-like structure.The coating thickness was about 300～350 μm，the nitriding layer thickness was about 10 μm，and the nitriding layer phase structure was FCC phase and AlN，CrN and other nitriding phases.Meanwhile，the microhardness of the nitriding layer was 981 HV2N(x＝0)，1 090 HV2N(x＝0.125) and 1 194 HV2N(x＝0.250)，respectively，which was significantly improved compared with the microhardness of 479 HV2N(x＝0)，506 HV2N(x＝0.125) and 548 HV2N(x＝0.250) of the unnitrided high-entropy alloy coating.With the increase of Ti content，the wear resistance of the nitriding layer increased，and Al0.750CoCrFeNiTi0.250nitriding layer possessed the best wear resistance [(2.17×10-6mm3/(N·m)].Besides，the wear failure mechanism of Al1-xCoCrFeNiTix(x＝0，0.125，0.250) nitriding layer was mainly abrasive wear，oxidation wear and adhesive wear.

With the rapid development of education informatization and intelligence, personalized teaching and course recommendations have gradually become an important research direction in the field of education technology. A knowledge graph, as a structured knowledge representation and organization, provides rich semantic information and a relationship network for teaching course recommendations. Based on this research background, this paper focuses on the research of knowledge graph multivariate environment-aware recommendation algorithms for teaching courses. The article firstly constructs the ontology of course resources, researches and analyzes the methods and steps of acquiring and processing data in order to build the knowledge graph, and then constructs the framework of the recommendation model combining multivariate perception in order to further analyze and explore the user’s course-aware representation learning and the user’s course-aware embedded learning. Embedded Learning, and finally, the teaching course of a school as an empirical study, it is shown that the performance of Ripple_mlp+ and Ripple_mlp in this article are higher than the benchmark algorithms through the experimental class and the control class of the pre and post-test scores have been sorted out and counted. The experimental students’ scores are steadily increasing, and the overall scores are better than the control class. In the experimental class, the significance value is 0.013, indicating that there is a significant difference between the midterm and final grades of the experimental class. Through the paired samples t-test on the midterm and final grades of the experimental class, after analyzing and comparing the midterm and final grades of students at different levels, it can be concluded that the t-value of the superior students is −3.326. The value of significance is 0.049, indicating that there is a significant difference between the midterm and final grades of the exceptional students. The T-value for intermediate students is −0.134, and the value of significance is 0.045, which indicates that there is a significant difference in the midterm final grades of intermediate students. The T-value of −1.623 and the value of significance is 0.534 for advanced students indicates that the difference in midterm final grades of advanced students is not significant.

As simple and ubiquitous redox-active organic molecules, quinones participate in diverse electron transfer processes in chemistry and biological systems for energy transformation and signal transduction. We introduce here a practical exercise to study the redox potentials of benzoquinone and its two derivatives by combining the electrochemistry method with quantum chemistry computation. The practical reduction potentials of three quinones were measured by cyclic voltammetry experiment. Quantum chemistry computation, on the other hand, provided theoretical Gibbs free energy change and reduction potentials of the three quinones, which were found to be in line with the experimental results. Detailed thermodynamic energy analysis based on the computation results revealed that the reduction Gibbs free energy changes of the three quinones were mainly contributed from the electronic energies change of the molecules, while thermal energy and entropy played a relatively minor role. The energy levels of the lowest unoccupied molecular orbital (LUMO) of the three quinones, which were modulated by substituent groups and conjugation structures, were further identified as the main origin of the reduction potential. This experiment provides practical and theoretical training on the fundamental ideas involved in major courses like thermodynamics, quantum chemistry, electrochemistry, and organic chemistry, and promotes students to find the tie between macroscopic redox properties of chemicals and their microscopic molecular structures, a key topic in chemistry education.