Packed modulation loops to reduce band broadening in two-dimensional liquid chromatography

Modulation interfaces employing sample loops are applied in many hyphenated separations such as two-dimensional liquid chromatography (2D-LC). When the first-dimension effluent in 2D-LC is eluted from the modulation loop, dispersion effects occur due to differences in the laminar flow velocity of the filling and emptying flow. These effects were recently studied by Moussa et al. whom recommended the use of coiled loops to promote radial diffusion and reduce this effect. In the 1980s, Coq et al. investigated the use of packed loops, which also promote radial diffusion, in large volume injection 1D-LC. Unfortunately, this concept was never investigated in the context of 2D-LC modulation. Our work evaluates use of packed loops in 2D-LC modulation and compares them to unpacked coiled and uncoiled modulation loops. The effect of the solvents, loop volume, differences in filling and emptying rates, and loop elution direction on the elution profile was investigated. Statistical moments were used as a pragmatic tool to quantify elution profile characteristics. Decreased dispersion was observed in all cases for the packed loops compared to unpacked loops and unpacked coiled loops. In particular for larger loop volumes the dispersion was reduced significantly. Furthermore, countercurrent elution resulted in narrower elution profiles in all cases compared to concurrent elution. We found that packed modulation loops are of high interested when analytes are not refocussed in the second-dimension separation (e.g. for size-exclusion chromatography). Moreover, our work suggests that the use of packed loops may aid in prevention of loop overfilling.</p

Development of a chemometric approach to improve the accuracy of copolymer sequence information obtained from pyrolysis gas-chromatography mass-spectrometry data

Number-average copolymer sequence length information can be obtained by pyrolysis-gas chromatography (Py-GC) by comparing the ratios of formed oligomers (i.e. dimers and trimers). The formation constants of the oligomers and their detection efficiency are not constant for all fragments, however. This can lead to unrepresentative peak ratios in the chromatogram. In these cases, calibration with an external method (e.g. NMR) is required. In this work, we introduce an algorithm that improves the copolymer sequence accuracy yielded from chromatograms with unrepresentative peak areas. The algorithm even functions in cases where oligomer data is missing as the rate of formation of certain oligomers is too low to detect them. One Py-GC measurement and one NMR measurement are required to train the developed algorithm for the determination of average monomer reactivity ratios and relative pyrolysis constants. Afterwards, Py-GC measurements of copolymers containing the same monomers, albeit with different compositions, can be corrected using the previously estimated constants. The algorithm was tested on various styrene-acrylate copolymers, yielding more accurate sequence information, even when limited oligomer information was available.</p

Automated Feature Mining for Two-Dimensional Liquid Chromatography Applied to Polymers Enabled by Mass Remainder Analysis

A fast algorithm for automated feature mining of synthetic (industrial) homopolymers or perfectly alternating copolymers was developed. Comprehensive two-dimensional liquid chromatography-mass spectrometry data (LC × LC-MS) was utilized, undergoing four distinct parts within the algorithm. Initially, the data is reduced by selecting regions of interest within the data. Then, all regions of interest are clustered on the time and mass-to-charge domain to obtain isotopic distributions. Afterward, single-value clusters and background signals are removed from the data structure. In the second part of the algorithm, the isotopic distributions are employed to define the charge state of the polymeric units and the charge-state reduced masses of the units are calculated. In the third part, the mass of the repeating unit (i.e., the monomer) is automatically selected by comparing all mass differences within the data structure. Using the mass of the repeating unit, mass remainder analysis can be performed on the data. This results in groups sharing the same end-group compositions. Lastly, combining information from the clustering step in the first part and the mass remainder analysis results in the creation of compositional series, which are mapped on the chromatogram. Series with similar chromatographic behavior are separated in the mass-remainder domain, whereas series with an overlapping mass remainder are separated in the chromatographic domain. These series were extracted within a calculation time of 3 min. The false positives were then assessed within a reasonable time. The algorithm is verified with LC × LC-MS data of an industrial hexahydrophthalic anhydride-derivatized propylene glycol-terephthalic acid copolyester. Afterward, a chemical structure proposal has been made for each compositional series found within the data

Characterization and comparison of smokeless powders by on-line two-dimensional liquid chromatography

Smokeless powders (SPs) are one of the most commonly used propellants for ammunition but can also be abused as energetic material in improvised explosive devices (IEDs) such as pipe bombs. After a shooting or explosion, unburnt or partially burnt particulates may be observed which can be used for forensic investigation. SPs comprise mainly nitrocellulose (NC) and additives. Therefore, the characterization of both NC and the additives is of significant forensic importance. Typically, the identification, classification, and chemical profiling of smokeless powders are based exclusively on the analysis of the additives. In this study, information regarding the NC base component was combined with the chemical analysis of the additives using two-dimensional liquid chromatography (2D-LC). The system combines size-exclusion chromatography (SEC) and reversed-phase liquid chromatography (RPLC) in an on-line heart-cut 2D-LC configuration. In the first dimension, the NC is characterized by its molecular-weight distribution (MWD) while being separated from the additives. The additives are then transferred to the second-dimension separation using a novel analyte-transfer system. In the second dimension, the additives are separated to obtain a detailed profile of the low-molecular-mass compounds in the SP. With this approach, the MWD of the NC and the composition of the additives in SP have been obtained within an hour. A discrimination power of 90.53% was obtained when studying exclusively the NC MWD, and 99.47% for the additive profile. This novel combination enables detailed forensic comparison of intact SPs. Additionally, no extensive sample preparation is required, making the developed method less labor intensive