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Traditional H2O2 cleavage mediated by macroscopic electron transfer (MET) not only has low utilization of H2O2, but also sacrifices the stability of catalysts. We present a non-redox hydroxyl-enriched spinel (CuFe2O4) catalyst with dual Lewis acid sites to realize the homolytic cleavage of H2O2. The results of systematic experiments, in situ characterizations, and theoretical calculations confirm that tetrahedral Cu sites with optimal Lewis acidity and strong electron delocalization can synergistically elongate the O-O bonds (1.47â Å â 1.87â Å) in collaboration with adjacent bridging hydroxyl (another Lewis acid site). As a result, the free energy of H2O2 homolytic cleavage is decreased (1.28â eV â 0.98â eV). H2O2 can be efficiently split into â OH induced by hydroxyl-enriched CuFe2O4 without MET, which greatly improves the catalyst stability and the H2O2 utilization (65.2 %, nearly 2 times than traditional catalysts). The system assembled with hydroxyl-enriched CuFe2O4 and H2O2 affords exceptional performance for organic pollutant elimination. The scale-up experiment using a continuous flow reactor realizes long-term stability (up to 600â mL), confirming the tremendous potential of hydroxyl-enriched CuFe2O4 for practical applications.
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The reducing gases produced and NO reduction by sewage sludge combustion were investigated in a self-made cement precalciner. The dual role of O2 concentration (0-5 vol%) in the production characteristics of reducing gases and the reduction efficiency of NO were evaluated experimentally. TG-FTIR analysis demonstrated that the key reducing gaseous species produced by sewage sludge combustion were HCN, NH3, CO, and CH4. And experiments demonstrated that O2 concentration had pronounced effects on NH3 distribution, the maximum production rate was obtained at an O2 concentration of 3 vol%. Meanwhile, the reducing gases NH3 and CO were the key species for NO reduction in the cement precalciner, and the reduction efficiency of NO, when reduced by NH3, increased with an increase in O2 concentration, while the reduction performance of NO by CO was limited by O2 concentration. Therefore, O2 concentration greatly influences NO reduction efficiency by sewage sludge combustion; the maximum NO reduction efficiency was 61.67% at an O2 concentration of 3 vol%. The difference in NO reduction by sewage sludge combustion under different O2 concentrations was primarily attributed to NH3 production rate and NO reduction by NH3 and CO, which is greatly affected by O2 concentration. Sewage sludge combustion can result in NO reduction in the cement kiln flue gas and resource utilisation of sewage sludge.
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Gases , Aguas del AlcantarilladoRESUMEN
The effects of ozone concentration, NaOH concentration, type and concentration of additives, initial pH, temperature, and NO and SO2 concentration on simultaneous removal of NO and SO2 were studied through ozone oxidation combined with wet absorption. Results indicated that ozone concentration and the type and concentration of additives had the most significant effect on NO removal. The optimal ozone concentration was 250 ppm (NO/NO2 = 1), and the best additive was KMnO4. The removal efficiency of NO x was as high as 97.86% when NO/NO2 = 1, and the concentration of KMnO4 was 0.025 mol/L. Considering economic and other factors, the KMnO4 concentration was selected to be 0.006 mol/L. At this time, the removal efficiencies of NO x and SO2 were 81.35 and 100%, respectively. This method has potential application prospects for simultaneous removal of SO2 and NO in the industrial flue gas.
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[This corrects the article DOI: 10.1039/C9RA04065J.].
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An experimental study on the effects of CO2 concentration on the release of reducing gases and the NO reduction efficiency by sludge reburning was carried out in a pilot scale cement precalciner. The results indicate that sludge reburning shows an ideal NO reduction activity. The best NO reduction efficiency of 54% is reached when the CO2 concentration is 25 vol%. Characteristic analysis of the sludge shows that the main types of reducing gases generated by sludge reburning are HCN, NH3, CO and CH4. Among them, CO2 concentration plays a crucial role in the release of HCN, CO and CH4. The mechanistic study indicates that NO reduction is dominated by homogeneous reduction during the sludge reburning process, in particular the reducing gases of CO and NH3 have significant influences on the NO reduction. Meanwhile, the effect of CO2 concentration on NO reduction is mainly due to the difference in CO release. The results of the present study not only provide insight into the mechanism of NO reduction by sludge reburning, but could also contribute to the development of NO X removal technology in the cement industry.
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Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.