Lei Da-Peng, Huang Jian-Hua
Department of Chemistry, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Wenzhou Quality and Technology Testing Research Institute, Wenzhou 325007, China.
Nanomaterials (Basel). 2024 Mar 12;14(6):508. doi: 10.3390/nano14060508.
Employing an automated monitoring system (AMS) for data acquisition offers benefits, such as reducing the workload, in the kinetic study of suspended photocatalytic batch reactions. However, the current methods in this field tend to narrowly focus on the substrate and often overlook the optical characteristics of both the mixture and solid particles. To address this limitation, in this study, we propose a novel AMS based on online circulatory spectrophotometry (OCS) and incorporate debubbling, aeration, and segmented flow (DAS), named DAS-OCS-AMS. Initially, a debubbler is introduced to mitigate the issue of signal noise caused by bubbles (SNB). Subsequently, an aerated and segmented device is developed to address the issue of particle deposition on the inner wall of the pipeline (PDP) and on the windows of the flow cell (PDW). The proposed DAS-OCS-AMS is applied to monitor the kinetics of the photocatalytic degradation of Acid Orange Ⅱ by TiO (P25), and its results are compared with those obtained using the traditional OCS-AMS. The comparative analysis indicates that the proposed DAS-OCS-AMS effectively mitigates the influence of SNB, PDP, and PDW, yielding precise results both for the mixture and solid particles. The DAS-OCS-AMS provides a highly flexible universal framework for online circulatory automated monitoring and a robust hardware foundation for subsequent data processing research.
在悬浮光催化间歇反应的动力学研究中，采用自动监测系统（AMS）进行数据采集具有诸多益处，比如可减轻工作量。然而，该领域目前的方法往往过于狭隘地聚焦于底物，常常忽略混合物和固体颗粒的光学特性。为解决这一局限性，在本研究中，我们提出了一种基于在线循环分光光度法（OCS）并结合除泡、曝气和分段流动（DAS）的新型AMS，命名为DAS-OCS-AMS。首先，引入一个除泡器以减轻气泡引起的信号噪声问题（SNB）。随后，开发了一种曝气分段装置来解决颗粒在管道内壁（PDP）和流通池窗口（PDW）上沉积的问题。所提出的DAS-OCS-AMS被应用于监测TiO₂（P25）光催化降解酸性橙Ⅱ的动力学过程，并将其结果与使用传统OCS-AMS获得的结果进行比较。对比分析表明，所提出的DAS-OCS-AMS有效减轻了SNB、PDP和PDW的影响，对混合物和固体颗粒均产生了精确的结果。DAS-OCS-AMS为在线循环自动监测提供了一个高度灵活的通用框架，并为后续数据处理研究奠定了坚实的硬件基础。
