For the first time, ion mobility spectrometry coupled with rapid gas chromatography, using multicapillary columns, was applied for the development of a pattern of signs of life for the localization of entrapped victims after disaster events (e.g., earthquake, terroristic attack). During a simulation experiment with entrapped volunteers, 12 human metabolites could be detected in the air of the void with sufficient sensitivity to enable a valid decision on the presence of a living person. Using a basic normalized summation of the measured concentrations, all volunteers involved in the particular experiments could be recognized only few minutes after they entered the simulation void and after less than 3 min of analysis time. An additional independent validation experiment enabled the recognition of a person in a room of ∼25 m(3) after ∼30 min with sufficiently high sensitivity to detect even a person briefly leaving the room. Undoubtedly, additional work must be done on analysis time and weight of the equipment, as well as on validation during real disaster events. However, the enormous potential of the method as a significantly helpful tool for search-and-rescue operations, in addition to trained canines, could be demonstrated.
Ion Mobility Spectrometry is a powerful method for the rapid identification of gas-phase analytes and finds its usage in various fields including the sensitive analysis of extremely complex and humid mixtures such as human breath when additional pre-separation techniques are applied. The output data from an ion mobility spectrometer (IMS), equipped with a Multi-Capillary Column (MCC) for pre-separation, is a chromatogram of the signal intensity versus a particular retention time and a specific reduced ion mobility which are the characteristics of the detected analyte. Hence, it is important to have a database of analytes with both the values for comparison and identification of peaks in any IMS chromatogram. Commonly, such databases are collected by measurements of reference analytes. It is obvious that a prognosis of the values, without the time consuming and costly reference measurements, would be a considerable facilitation for a preliminary identification of unknowns and development of databases. In this study, a correlation between the reduced ion mobilities and the number of carbon atoms was found for secondary alcohols. The correlation was then used to predict the reduced ion mobilities of other analytes in the same homologous series. To verify the accuracy of the prognosis, the analytes were measured individually using a 63 Ni-MCC-IMS and compared to the predicted values. The results of the prognosis show an accuracy higher than 99.5%.
Over the years, ion mobility spectrometry has evolved into a powerful technique for rapid identification of analytes in very complex sample matrixes such as human breath. Every analyte detected has a characteristic ion mobility value (and a retention time when additional preseparation techniques are employed) which is used to identify the peaks in a spectrum either by comparison with reference analytes or by simultaneous mass spectrometric measurements. In this study, the mass-mobility correlations between compounds in three different homologous series are used to predict the mobilities of the other substances in the same series in a medium of synthetic air. The results show a very high accuracy (>99.5%) of the prognosis. The linear trend equations of ion mobilities, as a function of the number of carbon atoms, obtained from the different series were then generalized into one linear equation for the reduced ion mobility for the polar aliphatic compounds and is validated by comparing it with the traditional Mason-Schamp equation. To compare the empirical equation obtained from the prognosis and the Mason-Schamp equation, the collision integral term in the latter was split into two terms to linearize it. The resulting novel ion mobility equation could be the starting step to completely describe the relationship between ion collision integral and the ion mobility for polar aliphatic compounds. The splitting of the collision integral into two terms will also give new inputs to describe the various ion models and the different forces that act on the ions and the neutral gas molecules upon which the collision integral is dependent on. This prognosis method could, furthermore, be extended to all other classes of organic compounds and could serve as a useful tool for identification of unknowns in ion mobility spectra, thereby considerably reducing the time-consuming and costly reference measurements and other coupling techniques that are currently employed.
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