3 years ago

Tuning Mobility Separation Factors of Chemical Warfare Agent Degradation Products via Selective Ion-Neutral Clustering

Tuning Mobility Separation Factors of Chemical Warfare Agent Degradation Products via Selective Ion-Neutral Clustering
Brian H. Clowers, Pearl Kwantwi-Barima, Christopher J. Hogan, Hui Ouyang
Combining experimental data with computational modeling, we illustrate the capacity of selective gas-phase interactions using neutral gas vapors to yield an additional dimension of gas-phase ion mobility separation. Not only are the mobility shifts as a function of neutral gas vapor concentration reproducible, but also the selective alteration of mobility separation factors is closely linked to existing chemical functional groups. Such information may prove advantageous in elucidating chemical class and resolving interferences. Using a set of chemical warfare agent simulants with nominally the same reduced mobility values as a test case, we illustrate the ability of the drift-gas doping approach to achieve separation of these analytes. In nitrogen, protonated forms of dimethyl methyl phosphonate (DMMP) and methyl phosphonic acid (MPA) exhibit the reduced mobility values of 1.99 ± 0.01 cm2 V–1s–1 at 175 °C. However, when the counter current drift gas of the system is doped with 2-propanol at 20 μL/h, full baseline resolution of the two species is possible. By varying the concentration of the neutral modifier, the separation factor of the respective clusters can be adjusted. For the two species examined and at a 2-propanol flow rate of 160 μL/h, MPA demonstrated the greatest shift in mobility (1.58 cm2V–1s–1) compared the DMMP monomer (1.63 cm2V–1s–1). Meanwhile, the DMMP dimer experienced no change in mobility (1.45 cm2V–1s–1). The enhancement of separation factors appears to be brought about by the differential clustering of neutral modifiers onto different ions and can be explained by a model which considers the transient binding of a single 2-propanol molecule during mobility measurements. Furthermore, the application of the binding models not only provides a thermodynamic foundation for the results obtained but also creates a predictive tool toward a quantitative approach.

Publisher URL: http://dx.doi.org/10.1021/acs.analchem.7b03518

DOI: 10.1021/acs.analchem.7b03518

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