Dissimilarity analysis and automatic identification of monomethylalkanes from gas chromatography mass spectrometry
Liangxiao Zhang1, Yizeng Liang
1College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, China.
Abstract:
Monomethylalkanes are common but important components in many naturally occurring and synthetic organic materials. Generally, this kind of compounds is routinely analyzed by gas chromatography mass spectrometry (GC-MS) and identified by the retention pattern or similarity matching to the reference mass spectral library. However, these identification approaches rely on the limited standard database or costly standard compounds. When unknown monomethylalkane is absent from the reference library, these approaches might be less useful. In this study, based on the fragmentation rules and empirical observation, many interesting mass spectral characteristics of monomethylalkanes were discovered and employed to infer the number of carbon atoms and methylated position. Combined with the retention pattern, a protocol was described for the identification of monomethylalkane analyzed by GC-MS. After tested by simulated data and GC-MS data of the gasoline sample, it was demonstrated that the developing approach could automatically and correctly identify monomethylalkanes in complicated GC-MS data.
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