通过与FeNC合的等离子体进行周期性激活以去除污染物:机器学习辅助催化剂优化和电子穿机制
Wenxuan Jiang1, Yawen Wang1, Chendong Puyang1
1College of Ecology and the Environment, Nanjing Forestry University, Nanjing 210037 China.
Journal of colloid and interface science
|January 29, 2025
概括
这项研究引入了一种新的水处理方法,使用介电屏障放电 (DBD) 血与铁基催化剂 (FeNC) 激活周期物 (PI) 进行高效的新兴污染物去除. 该系统实现了硫法迪亚100%的降解,证明了净化水的有希望的解决方案.
科学领域:
- 环境化学环境化学
- 材料科学 材料科学 材料科学
- 化学工程是化学工程的重要组成部分.
背景情况:
- 新兴污染物 (ECs) 由于其持久性和毒性,在水处理中存在重大挑战.
- 传统的水处理方法与ECs的复杂性作斗争.
- 先进的氧化工艺 (AOP) 提供了EC降解的潜力,但往往需要优化.
研究的目的:
- 开发和评估一种新的水处理系统,将介电屏障放电 (DBD) 等离子体,铁基催化剂 (FeNC) 和周期物 (PI) 结合起来,以有效地去除EC.
- 使用机器学习 (ML) 优化FeNC催化剂,以提高性能.
- 阐明硫黄 (SDZ) 的降解机制,并评估该系统在真实水样中的有效性.
主要方法:
- 介电屏障放电 (DBD) 等离子体与FeNC激活周期电 (PI) 相结合.
- 机器学习 (ML) 用于优化催化剂合成参数 (化温度和添加).
- 用于催化剂分析的高级表征技术 (XRD,Raman,XPS) 和密度函数理论 (DFT).
- 使用硫黄 (SDZ) 作为EC模型的降解实验,监测去除效率和反应动力学.
- 识别活性氧物种 (ROS) 和降解途径.
主要成果:
- 优化的FeNC催化剂在575°C以17%的N添加合成,表现出卓越的性能.
- 在12分钟内,DBD/FeNC/PI系统实现了100%的SDZ退化,显著优于单独的DBD和DBD/PI.
- 鉴定和DFT分析证实了优化催化剂的增强电子穿和PI激活能力.
- 包括单一氧 (1O2),基基 (•OH) 和超氧化基 (O2−•) 在内的反应性物种被确定为降解的关键贡献者.
- 主要降解途径涉及通过OH攻击和电子转移解离胺环.
- 中间产品的毒性低于母SDZ的毒性.
- 该系统在实际的水样中证明了高的SDZ清除效率,以及与其他EC相比的有效性.
结论:
- DBD/FeNC/PI系统代表了一种高效和有前途的新兴污染物清除AOP.
- FeNC催化剂在激活PI和促进电子转移方面发挥着至关重要的作用,增强了污染物降解.
- 优化的催化剂和过程显示出在水处理中实际应用的巨大潜力,为复杂污染物提供可持续的解决方案.
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