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首页> 外文期刊>Journal of Analytical & Applied Pyrolysis >Efficient analysis of Py-GC/MS data by a large scale automatic database approach: An illustration of white pitch identification in pulp and paper industry
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Efficient analysis of Py-GC/MS data by a large scale automatic database approach: An illustration of white pitch identification in pulp and paper industry

机译：大型自动数据库方法对Py-GC / MS数据进行高效分析：纸浆和造纸工业中白色沥青识别的图示

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摘要

Hyphenated techniques like Py-GC/MS (pyrolysis-gas chromatography/mass spectrometry) result often in complex chromatograms containing a high information density. Extracting meaningful information is difficult and time consuming. Especially with automatic sampling, data evaluation becomes a major bottleneck. An effective approach to automate the characterization of chromatograms is presented. The database approach consists basically of three steps: measuring reference substances to generate a database, measuring unknown or difficult samples and using the database for the identification of these samples.rnThe compiled database contains a collection of mass spectra of pyrolysis products with data such as retention index and additional information from which reference substances the pyrolysis products may derive. The developed database approach has been tested on designed mixtures of compounds forming "white pitch". "White pitch" is a typical type of deposit found in paper production processes deriving from chemicals used in coating processes.
机译：像Py-GC / MS（热解气相色谱/质谱）这样的联用技术通常会导致包含高信息密度的复杂色谱图。提取有意义的信息既困难又耗时。特别是在自动采样的情况下，数据评估成为主要瓶颈。提出了一种自动进行色谱图表征的有效方法。数据库方法主要包括三个步骤：测量参考物质以生成数据库，测量未知或困难的样品，并使用该数据库识别这些样品。rn编译后的数据库包含热解产物的质谱集合，以及诸如保留的数据指数和热分解产物可能来自的参考物质的其他信息。已开发的数据库方法已在形成“白色沥青”的化合物的设计混合物中经过测试。 “白沥青”是在纸张生产过程中发现的一种典型类型的沉积物，其源于涂布过程中使用的化学品。

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