کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1197146 | 964638 | 2010 | 8 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: 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 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](/preview/png/1197146.png)
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.The 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.
Journal: Journal of Analytical and Applied Pyrolysis - Volume 87, Issue 1, January 2010, Pages 85–92