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Mingxia Yu,Huosheng Li,Keke Li,Yuting Li,Fengli Liu,Gaosheng Zhang,Tangfu Xiao,Ping Zhang,Hongguo Zhang,Jianyou Long 한국섬유공학회 2022 Fibers and polymers Vol.23 No.2
Decolorization and organic degradation of wastewater containing multiple dyes are still challenging inwastewater treatment. Magnetic biochar coupled with advanced oxidation is a potential solution to this issue. In this study,a series of magnetite-based biochar composites (Fe3O4@C) was prepared and compared for the removal of mixed dyes,including methyl orange (MO), rhodamine B (RhB), methylene blue (MB), and an organic macromolecule, humic acid(HA). The pyrolysis of watermelon rinds followed by precipitation of Fe3O4 onto the biochar was selected as the optimummethod to prepare an adsorbent and catalyst to couple binary oxidants (hypochlorite and persulfate) for color and totalorganic carbon removal. Persulfate was prone to degrade HA and MB, while hypochlorite was inclined to oxidize MO andRhB. Fe3O4@C exhibited better dye removal performance in coupling with binary oxidants than with a single oxidant. Formixed dye solutions with an initial concentration of 50 mg/l for each dye, the highest TOC (57.24±3.17 %) and the colorremoval efficiencies (94.13±1.68 %) for the mixed dye solution were achieved at a sorbent dosage of 1 g/l and an oxidantdosage of 5 mmol/l for both hypochlorite and persulfate. Multiple free radicals, including hydroxyl radicals, sulfateradicals, and hypochlorite-induced radicals, play critical roles in the degradation of mixed dyes and color removal. Theregeneratibility and reutilization of the magnetic Fe3O4@C composite were effective and stable. The results obtained inthis study show that the combined Fe3O4@C and binary oxidants technique is promising for the treatment of multi-dyewastewater.
Zhaoyang Qu,Wanxin Wang,Nan Qu,Yuqing Liu,Hongbo Lv,Kewei Hu,Jianyou Yu,Manyang Gao,Jiajun Song 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.6
Due to unfortunate mistake the grant numbers have been omitted in the acknowledgments section: This work is supported by the National Natural Science Foundation of China (No. 51437003), Jilin Province Science and Technology Development Plan Project of China (20160623004TC, 20180201092GX), Jilin Science and Technology Innovation Development Plan Project of China (201830817).
Zhaoyang Qu,Wanxin Wang,Nan Qu,Yuqing Liu,Hongbo Lv,Kewei Hu,Jianyou Yu,Manyang Gao,Jiajun Song 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.4
In order to improve the accuracy of forecasts of the electricity sales of power sales companies, a depth forecast model of electricity sales based on the characteristics of the power market is proposed. First, based on survival analysis, the calculation method of the user churn rate in the electricity market is given, and the number of users at a certain moment in the future is predicted. Then, users’ electricity consumption that calculated by the deep belief network and the predicted quantity of users are combined to design a forecast model of electricity sales. Finally, the model is solved utilizing the weighting algorithm of adaptive inertia. The analysis of the example shows that the proposed method achieves a signifi cant improvement in the accuracy of power sales forecasting.