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一种新型顶空 O 浓度测量传感器在小瓶中的开发。

The Development of a Novel Headspace O Concentration Measurement Sensor for Vials.

机构信息

School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

出版信息

Sensors (Basel). 2023 Feb 22;23(5):2438. doi: 10.3390/s23052438.

Abstract

In the process of manufacture and transportation, vials are prone to breakage and cracks. Oxygen (O) in the air entering vials can lead to the deterioration of medicine and a reduction in pesticide effects, threatening the life of patients. Therefore, accurate measurement of the headspace O concentration for vials is crucial to ensure pharmaceutical quality. In this invited paper, a novel headspace oxygen concentration measurement (HOCM) sensor for vials was developed based on tunable diode laser absorption spectroscopy (TDLAS). First, a long-optical-path multi-pass cell was designed by optimizing the original system. Moreover, vials with different O concentrations (0%, 5%, 10%, 15%, 20%, and 25%) were measured with this optimized system in order to study the relationship between the leakage coefficient and O concentration; the root mean square error of the fitting was 0.13. Moreover, the measurement accuracy indicates that the novel HOCM sensor achieved an average percentage error of 1.9%. Sealed vials with different leakage holes (4, 6, 8, and 10 mm) were prepared to investigate the variation in the headspace O concentration with time. The results show that the novel HOCM sensor is non-invasive and has a fast response and high accuracy, with prospects in applications for online quality supervision and management of production lines.

摘要

在制造和运输过程中,小瓶容易破裂和出现裂缝。进入小瓶的空气中的氧气(O)会导致药物变质和降低农药效果,威胁患者的生命。因此,准确测量小瓶的顶空 O 浓度对于确保药物质量至关重要。在这篇特邀论文中,开发了一种基于可调谐二极管激光吸收光谱(TDLAS)的新型小瓶顶空氧气浓度测量(HOCM)传感器。首先,通过优化原始系统设计了一个长光程多通池。此外,使用该优化系统测量了具有不同 O 浓度(0%、5%、10%、15%、20%和 25%)的小瓶,以研究泄漏系数与 O 浓度之间的关系;拟合的均方根误差为 0.13。此外,测量精度表明,新型 HOCM 传感器的平均百分比误差为 1.9%。制备了具有不同泄漏孔(4、6、8 和 10mm)的密封小瓶,以研究顶空 O 浓度随时间的变化。结果表明,新型 HOCM 传感器是非侵入式的,具有快速响应和高精度,有望在线应用于生产线的质量监督和管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2ce/10007330/36ca8d7a3b4b/sensors-23-02438-g001.jpg

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