The analysis of impurities at a trace level in chemical products, nutrition additives, and drugs is highly important to guarantee safe products suitable for consumption. However, trace analysis in the presence of a dominating component can be a challenging task because of noncompatible linear detection ranges or strong signal overlap that suppresses the signal of interest. Here, we developed a technique for quantitative analysis using multiplexing gas chromatography (mpGC) for continuous and completely automated process trace analytics exemplified for the analysis of a CO stream in a production plant for detection of benzene, toluene, ethylbenzene, and the three structural isomers of xylene (BTEX) in the concentration range of 0-10 ppb. Additional minor components are methane and methanol with concentrations up to 100 ppm. The sample is injected up to 512 times according to a pseudorandom binary sequence (PRBS) with a mean frequency of 0.1 Hz into a gas chromatograph equipped with a flame ionization detector (FID). A superimposed chromatogram is recorded which is deconvoluted into an averaged chromatogram with Hadamard transformation. Novel algorithms to maintain the data acquisition rate of the detector by application of Hadamard transformation and to suppress correlation noise induced by components with much higher concentrations than the target substances are shown. Compared to conventional GC-FID, the signal-to-noise ratio has been increased by a factor of 10 with mpGC-FID. Correspondingly, the detection limits for BTEX in CO have been lowered from 10 to 1 ppb each. This has been achieved despite the presence of detectable components (methane and methanol) with a concentration about 1000 times higher than the target substances. The robustness and reliability of mpGC has been proven in a two-month field test in a chemical production plant.

Developing new catalysts is crucial for optimization of chemical processes. Thus, advanced analytical methods are required to determine the catalytic performance of new catalysts accurately. Usually, gas chromatographic methods are employed to analyze quantitatively the product distribution of volatile compounds generated by a specific catalyst. However, the characterization of rapidly changing catalysts, e.g., due to deactivation, still poses an analytical challenge because gas chromatographic methods are too slow for monitoring the change of the complex product spectra. Here, we developed a gas chromatographic technique based on the concept of multiplexing gas chromatography (mpGC) for fast and comprehensive analysis of the product stream from a catalytic testing unit. This technique is applied for the study of the catalytic reaction of methanol-to-olefins (MTO) conversion. For this method, the time distance between two measurements is chosen so that the chromatograms but not the peaks themselves are superimposed. In this way, stacked chromatograms are generated in which the components from successively injected samples elute baseline separated next to each other from the column. The peaks from different samples are interlaced, and for this reason, the method is referred to as time-division multiplexing gas chromatography (td-mpGC). The peaks are analyzed by direct peak integration not requiring a Hadamard transformation for deconvolution of the raw data as usual for many mpGC applications. Therefore, the sample can be injected equidistantly. The integrated peaks have to be allocated to the correct retention times. The time distance between two measurements for studying the reaction and regeneration cycles of MTO catalysts is 4.3 min and 38 s, respectively. Column switching techniques such as back-flush and heart-cut are introduced as general tools for multiplexing gas chromatography.

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