Online Continuous Trace Process Analytics Using Multiplexing Gas Chromatography

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 CO2 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 CO2 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.