期刊
ANALYTICA CHIMICA ACTA
卷 433, 期 1, 页码 53-70出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/S0003-2670(00)01391-X
关键词
mobility spectra; fragment ion; neural networks; atmospheric pressure chemical ionization; ion mobility spectrometry; spectral library
Mobility spectra for organic compounds at temperatures of similar to 50 degreesC and 175-250 degreesC were categorized by chemical class using back-propagation neural networks with the successful classification even of chemicals not familiar to the networks. Network performance suggested that chemical class information in spectra at similar to 50 degreesC differed from that in spectra at high temperatures, prompting a detailed analysis of regions where chemical class information was located. These regions, or drift times in the mobility spectra, were identified at each temperature using a method of incrementally removing portions of spectra so that the value or structural content of the subtracted region could be seen in comparisons of network performance. At high temperatures (175-250 degreesC), chemical class information was contained in fragment ions located in a narrow region of the spectra with reduced mobilities of 3.06-2.11 cm(2) V-1 s(-1) corresponding to the drift times near and encompassing the reactant ions peaks. In contrast, spectra at low temperature (similar to 50 degreesC) were classified through fragment ions that resided in a broad region of drift time between protonated water clusters and product cluster peaks. This corresponded to reduced mobilities of 1.8-1.2 cm(2) V-1 s(-1). These findings suggest that fragmentation in ion mobility spectrometry and other atmospheric pressure chemical ionization based methods, with moisture <1 ppm, may be more common than previously understood. Class specific fragmentation reactions for ions at low temperature have never been described in LMS and became evident only when mobility spectra were formatted with a logarithmic axis for ion intensity. <(c)> 2001 Elsevier Science B.V. All rights reserved.
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