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Photocatalytic degradation of antibiotics by molecular assembly porous carbon nitride: Activity studies and artificial neural networks modeling

机译:分子组装多孔碳氮化物的光催化降解抗生素:活性研究和人工神经网络建模

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摘要

As a emerging photocatalyst, polymeric carbon nitride has attracted much attention. However, the activity of bulk carbon nitride is low. In this study, the porous carbon nitride (P-UCN) was synthesized by thermal calcination of urea and 2,5-dibromopyrazine. The optical absorption range and the separation efficiency of photogenerated electrons-holes of P-UCN were improved. The photocatalytic activity of P-UCN was studied by sulfadiazine (SD) degradation under 12-channel visible light reaction system. The effect of catalyst amount, initial concentration of SD were studied. In addition, the artificial neural network model was utilized to predict SD removal rate of porous carbon nitride (P-UCN).
机译:作为一种新兴光催化剂,聚合物碳氮化物引起了很多关注。 然而,散装碳氮化物的活性低。 在该研究中,通过尿素热煅烧和2,5-二溴吡嗪的热煅烧合成多孔碳氮化物(P-UCN)。 改善了P-UCN的光生电子孔的光学吸收范围和分离效率。 通过12通道可见光反应系统下磺胺嗪(SD)降解P-UCN的光催化活性。 研究了催化剂量,初始浓度SD的效果。 另外,利用人工神经网络模型来预测多孔碳氮化(P-UCN)的SD去除速率。

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