Effects of Chlorine Addition on Nitrogen Oxide Reduction and Mercury Oxidation over Selective Catalytic Reduction Catalysts.

The effect of chlorine on mercury oxidation and nitrogen oxides (NO x ) reduction over selective catalytic reduction (SCR) catalysts was investigated in this study. Commercial SCR catalysts achieved a high Hg0 oxidation efficiency when Cl2 was sprayed into the flue gas. Results indicated that an appropriate concentration of Cl2 was found to promote NO x reduction and Hg0 oxidation significantly. An optimal concentration of Cl2 (25 ppm) was found to significantly promote NO x reduction and Hg0 oxidation. Moreover, we studied the effects of Cl2 on NO x reduction and Hg0 oxidation over SCR catalysts under different concentrations of SO2. The SO2 poisoning effect was decreased by Cl2 when the SO2 concentration was low (below 1500 ppm). However, sulfate gradually covered the catalyst surface over time during the reaction, which limited the impact of Cl2. Finally, different sulfur-poisoned catalysts were examined in the presence of Cl2. The NO x reduction and Hg0 oxidation performances of sulfate-poisoned catalysts improved when Cl2 was added to the flue gas. Mechanisms for NO x reduction and Hg0 oxidation over fresh catalysts and sulfate-poisoned catalysts in the presence of Cl2 were proposed in this study. The mechanism of Cl2-influenced NO x reduction was similar to that for the NH3-SCR process. With Cl2 in the flue gas, the number of Brønsted active sites increased, which improved catalytic activity. Furthermore, Cl2 reoxidized V4+-OH to V5+=O and caused the NH3-SCR process to operate continuously. The Langmuir-Hinshelwood mechanism was followed for Hg0 oxidation by SCR catalysts when Cl2 was in the flue gas. Cl2 increased the number of Lewis active sites, and catalytic activity increased. Hg0 adsorbed on the surface of the catalysts and was then oxidized to HgCl2. Adding Cl2 to the flue gas increased the strength and number of acid sites on sulfate-poisoned catalysts.

Computational Model Development of Drug-Target Interaction Prediction: A Review.

In the medical field, drug-target interactions are very important for the diagnosis and treatment of diseases, they also can help researchers predict the link between biomolecules in the biological field, such as drug-protein and protein-target correlations. Therefore, the drug-target research is a very popular study in both the biological and medical fields. However, due to the limitations of manual experiments in the laboratory, computational prediction methods for drug-target relationships are increasingly favored by researchers. In this review, we summarize several computational prediction models of the drug-target connections during the past two years, and briefly introduce their advantages and shortcomings. Finally, several further interesting research directions of drug-target interactions are listed.