Portable combination of Fourier transform infrared spectroscopy and differential mobility spectrometry for advanced vapor phase analysis

Abstract

Designing mobile devices for the analysis of complex sample mixtures containing a variety of analytes at different concentrations across a large dynamic range remains a challenging task in many analytical scenarios. To meet this challenge, a compact hybrid analytical platform has been developed combining Fourier transform infrared spectroscopy based on substrate-integrated hollow waveguides (iHWG-FTIR) with gas chromatography coupled differential mobility spectrometry (GC-DMS). Due to the complementarity of these techniques regarding analyte type and concentration, their combination provides a promising tool for the detection of complex samples containing a broad range of molecules at different concentrations. To date, the combination of infrared spectroscopy and ion mobility techniques remains expensive and bound to a laboratory utilizing e.g. IMS as prefilter or IR as ionization source. In the present study, a cost-efficient and portable solution has been developed and characterized representing the first truly hyphenated IR-DMS system. As a model analyte mixture, 5 ppm isopropylmercaptan (IPM) in methane (CH4) were diluted, and the concentration-dependent DMS signal of IPM along with the concentration-dependent IR signal of CH4 were recorded for all three hybrid IR-DMS systems. While guiding the sample through the iHWG-FTIR or the GC-DMS first did not affect the obtained signals, optimizing the IR data acquisition parameters did benefit the analytical results.

Conflict of interest statement

Conflicts of interest

There are no conflicts to declare.

Figures

Fig. 1

A gaseous sample mixture of low concentrated isopropylmercaptan (ppb range) and highly concentrated methane (% range) was analyzed via the hybrid analytical setup interfacing GC-DMS and iHWG-FTIR taking advantage of the orthogonality of the two methods

Fig. 2

Hybrid GC-DMS and iHWG-FTIR setups and respective model DMS and IR spectra. For clarity, „iHWG-FTIR” was simplified to „IR”. Numbers along the flow path are listed as mL/min. In the IR(300)-GC-DMS setup, a different sample flow in the IR (300 mL/min instead of 60 mL/min) as well as different IR settings (resolution, number of averaged IR scans; symbolized by green star) were applied in order to maximize the IR signal. A detailed view of the interior of the IR and GC-DMS setups can be found in the supporting information

Fig. 3

IR peak at 3016 cm−1and 4.3 % CH4. The peak recorded with IR(300)-GC-DMS setup (green) shows rotational fine structure and higher signal intensities due to the higher resolution of 2 cm−1. The peaks recorded with the IR(60)-GC-DMS and GC-DMS-IR(60) setup overlap each other and therefore cannot be clearly distinguished from one another here.

Fig. 4

DMS spectrum of 217 ppb IPM. Tentative peak assignment comprises the IPM monomer (+1.3 V CV, 479 s RT) and the IPM dimer (+3.8 V CV, 479 s RT) peak. As expected, the RIP intensity (along −23.5 V CV) is decreased while IPM is present within the DMS sensing region

Fig. 5

Results of the concentration dependent iHWG-FTIR measurements are shown: averaged peak areas fitted with a Box-Lucas function (all R2 > 0.99). 1σ error bars are plotted, yet hardly visible due to their small size

Figure 6.

Results of the concentration dependent GC-DMS measurements are shown: averaged DMS peak volumes linearly fitted (all R2 > 0.94). 1σ error bars are displayed