在照片-芬顿过程中使用Arduino自组自动系统进行自动H2O2监控
Kevin U Antela1, Davide Palma2, Angel Morales-Rubio3
1Department of Chemistry, University of Turin, Via P. Giuria 5, Torino, 10125, Italy; Department of Analytical Chemistry, University of Valencia, Dr. Moliner 50, 46100, Burjassot, València, Spain.
Talanta
|May 6, 2024
概括
一个使用Arduino的自动化系统监测了在Photo-Fenton咖啡因降解过程中的过氧化 (H2O2) 消耗. 与手工方法相比,这种绿色化学方法提供了更高的精度和更少的浪费.
科学领域:
- 环境化学环境化学
- 分析化学 分析化学
- 绿色化学 绿色化学
背景情况:
- 光芬顿降解是一种有效的去除咖啡因等有机污染物的方法.
- 持续监测过氧化 (H2O2) 对于优化光-芬顿过程至关重要.
- 手动H2O2监测可能是劳动密集型的,并使操作人员面临危险.
研究的目的:
- 开发和评估一个低成本的,基于Arduino的自动化系统来监测H2O2消耗.
- 为了比较自动化系统的分析性能与传统的UV-Vis光谱光度计.
- 使用自动监测系统优化咖啡因的光芬顿降解.
主要方法:
- 一个Arduino自组装的自动系统被用于通过色度反应连续监测H2O2.
- 高性能液态色谱 (HPLC) 用于样本分析.
- 实验设计 (DoE) 用于优化照片-芬顿参数 (H2O2度,铁度,咖啡因度).
主要成果:
- 与手动UV-Vis光谱相比,自动化系统表现出较高的分析性能,检测 (LOD) 和量化 (LOQ) 极限较低.
- 自动系统的LOD:0.032 mM,LOQ:0.106 mM与UV-Vis.的LOD:0.064 mM,LOQ:0.213 mM相比,自动系统的LOD为0.032 mM,LOQ为0.106 mM.
- 通过调查关键的操作参数来实现光-芬顿处理的优化.
结论:
- 基于Arduino的自动化系统提供了一个具有成本效益,精确和高效的解决方案,用于监测H2O2在光-芬顿降解中的降解.
- 该系统通过减少工作量,试剂消耗和浪费,与绿色分析化学原则保持一致.
- 自动化通过最大限度地减少操作员干预和暴露于紫外线辐射来提高安全性.
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