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使用3D打印柱和MiCS-6814传感器优化低成本气体分析以检测挥发性化合物

Optimizing Low-Cost Gas Analysis with a 3D Printed Column and MiCS-6814 Sensor for Volatile Compound Detection.

作者信息

Skowronkova Nela, Adamek Martin, Zvonkova Magdalena, Matyas Jiri, Adamkova Anna, Dlabaja Stepan, Buran Martin, Sevcikova Veronika, Mlcek Jiri, Volek Zdenek, Cernekova Martina

机构信息

Department of Food Analysis and Chemistry, Faculty of Technology, Tomas Bata University in Zlin, Vavreckova 5669, 760 01 Zlin, Czech Republic.

Department of Automation and Control Engineering, Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, 760 05 Zlin, Czech Republic.

出版信息

Sensors (Basel). 2024 Oct 13;24(20):6594. doi: 10.3390/s24206594.

Abstract

This paper explores an application of 3D printing technology on the food industry. Since its inception in the 1980s, 3D printing has experienced a huge rise in popularity. This study uses cost-effective, flexible, and sustainable components that enable specific features of certain gas chromatography. This study aims to optimize the process of gas detection using a 3D printed separation column and the MiCS-6814 sensor. The principle of the entire device is based on the idea of utilizing a simple capillary chromatographic column manufactured by 3D printing for the separation of samples into components prior to their measurement using inexpensive chemiresistive sensors. An optimization of a system with a 3D printed PLA block containing a capillary, a mixing chamber, and a measuring chamber with a MiCS-6814 sensor was performed. The optimization distributed the sensor output signal in the time domain so that it was possible to distinguish the peak for the two most common alcohols, ethanol and methanol. The paper further describes some optimization types and their possibilities.

摘要

本文探讨了3D打印技术在食品工业中的应用。自20世纪80年代问世以来,3D打印的受欢迎程度大幅提升。本研究使用了具有成本效益、灵活性和可持续性的组件,这些组件实现了某些气相色谱的特定功能。本研究旨在使用3D打印的分离柱和MiCS-6814传感器优化气体检测过程。整个装置的原理基于这样一种理念:利用通过3D打印制造的简单毛细管色谱柱,在使用廉价的化学电阻传感器进行测量之前,将样品分离成各个组分。对一个包含毛细管、混合室和带有MiCS-6814传感器的测量室的3D打印聚乳酸(PLA)模块系统进行了优化。该优化在时域中分布了传感器输出信号,从而能够区分两种最常见的醇类(乙醇和甲醇)的峰值。本文进一步描述了一些优化类型及其可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8479/11511080/eb953734bc23/sensors-24-06594-g001.jpg

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