Suppr超能文献

电芬顿工艺降解对硝基苯酚:途径、动力学模型及中心复合设计优化。

p-Nitrophenol degradation by electro-Fenton process: Pathway, kinetic model and optimization using central composite design.

机构信息

Department of Chemical Engineering University of Vigo, Isaac Newton Building, Campus As Lagoas, Marcosende, 36310, Vigo, Spain.

Department of Chemical Engineering University of Vigo, Isaac Newton Building, Campus As Lagoas, Marcosende, 36310, Vigo, Spain.

出版信息

Chemosphere. 2017 Oct;185:726-736. doi: 10.1016/j.chemosphere.2017.07.067. Epub 2017 Jul 14.

Abstract

The chemical process scale-up, from lab studies to industrial production, is challenging and requires deep knowledge of the kinetic model and the reactions that take place in the system. This knowledge is also useful in order to be employed for the reactor design and the determination of the optimal operational conditions. In this study, a model substituted phenol such as p-nitrophenol was degraded by electro-Fenton process and the reaction products yielded along the treatment were recorded. The kinetic model was developed using Matlab software and was based on main reactions that occurred until total mineralization which allowed predicting the degradation pathway under this advanced oxidation process. The predicted concentration profiles of p-nitrophenol, their intermediates and by-products in electro-Fenton process were validated with experimental assays and the results were consistent. Finally, based on the developed kinetic model the degradation process was optimized using central composite design taking as key parameters the ferrous ion concentration and current density.

摘要

从实验室研究到工业生产的化学过程放大具有挑战性,需要深入了解动力学模型和系统中发生的反应。为了进行反应器设计和确定最佳操作条件,这些知识也很有用。在这项研究中,采用电芬顿工艺降解了一种替代苯酚的模型物质,如对硝基苯酚,并记录了处理过程中产生的反应产物。该动力学模型是使用 Matlab 软件开发的,基于主要反应,这些反应一直持续到完全矿化,这使得能够预测在这种高级氧化过程下的降解途径。电芬顿过程中对硝基苯酚、其中间产物和副产物的预测浓度分布与实验测定结果一致。最后,基于开发的动力学模型,采用中心复合设计,以亚铁离子浓度和电流密度为关键参数,对降解过程进行了优化。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验