A Fast Mass Spectrum Screening Technique for Volatile Organic Compounds Based on Parallel Artificial Neural Networks

Autor:	Thomas G. Thomas, Dennis G. Smith
Rok vydání:	1998
Předmět:	chemistry.chemical_classification Chromatography Artificial neural network General Medicine BTEX Mass spectrometry Toluene Analytical Chemistry chemistry.chemical_compound chemistry Filter (video) Mass spectrum Volatile organic compound Gas chromatography
Zdroj:	Journal of Chromatographic Science. 36:237-246
ISSN:	1945-239X 0021-9665
DOI:	10.1093/chromsci/36.5.237
Popis:	A technique for screening mass spectra for the presence of volatile organic compounds (VOCs) is developed using probabilistic neural networks. A parallel neural network filter is designed to recognize benzene, toluene, ethyl benzene, and o-xylene in gas chromatography—mass spectrometry (GC–MS) chromatograms of VOC mixtures. The filter trained rapidly and was evaluated by analyzing a variety of VOC combinations. The performance of the network offers some significant advantages over the traditional GC–MS data processing techniques such as ion extraction and compound library searching. Advantages include speed, selectivity, and the ability to discriminate between overlapping compounds.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e16fef4a1e42ab8ccd28761346abc80c https://doi.org/10.1093/chromsci/36.5.237 Zobrazit plný text záznamu