气相色谱数据保留时间对齐的半监督聚类算法

IF 1.4 4区 工程技术 Q3 ENGINEERING, CHEMICAL Periodica Polytechnica Chemical Engineering Pub Date : 2022-02-10 DOI:10.3311/ppch.18834
Omar Péter Hamadi, T. Varga
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引用次数: 0

摘要

气相色谱法(GC)是分析含有大量组分的复杂混合物的有效工具。为了跟踪塑料废弃物热解等过程中的化学变化,通常会对不同的样品状态进行分析,但色谱图之间的保留时间漂移使得比较困难。本研究的目的是建立一种快速、简便的方法,利用易于获取的先验信息来消除色谱图之间的时间漂移。通过对实际废HDPE/PP/LDPE混合料粉碎后的热解产物(Mg/Y催化剂)进行GC色谱分析,验证了该方法的有效性。开发了一种改进的k-means算法来考虑样本(不同样本状态)之间的保留时间漂移。保留时间校准的结果是所有色谱图中每个峰的平均保留时间,这使得比较和进一步分析(如“指纹”)更容易或可能。
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Semi-supervised Clustering Algorithm for Retention Time Alignment of Gas Chromatographic Data
Gas chromatography (GC) is an effective tool for the analysis of complex mixtures with a huge number of components. To keep tracking the chemical changes during the processes like plastic waste pyrolysis usually different sample states are profiled, but retention time drifts between the chromatograms make the comparability difficult. The aim of this study is to develop a fast and simple method to eliminate the time drifts between the chromatograms using easily accessible priori information. The proposed method is tested on GC chromatograms obtained by analysis of pyrolysis product (Mg/Y catalyst) of shredded real waste HDPE/PP/LDPE mixture. A modified k-means algorithm was developed to account the retention time drifts between samples (different sample states). The outcome of the retention time alignment is an averaged retention time for each peak from all the chromatograms which makes the comparison and further analysis (such as "fingerprinting") easier or possible.
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来源期刊
CiteScore
3.10
自引率
7.70%
发文量
44
审稿时长
>12 weeks
期刊介绍: The main scope of the journal is to publish original research articles in the wide field of chemical engineering including environmental and bioengineering.
期刊最新文献
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