Characteristic structures of liquid crystal monomers in EI-MS analysis and the potential application in suspect screening

Liquid crystal monomers (LCMs) are of emerging concern due to their ubiquitous presence in indoor and outdoor environments and their potential negative impacts on human health and ecosystems. Suspect screening approaches have been developed to monitor thousands of LCMs that could enter the environment, but an updated suspect list of LCMs is difficult to maintain given the rapid development of material innovations. To facilitate suspect screening for LCMs, in-silico mass fragmentation model and quantitative structure-activity relationship (QSPR) models were applied to predict electron ionization (EI) mass spectra of LCMs. The in-silico model showed limited predictive power for EI mass spectra, while the QSPR models trained with 437 published mass spectra of LCMs achieved an acceptable absolute error of 12 percentage points in predicting the relative intensity of the molecular ion, but failed to predict the mass-to-charge ratio of the base peak. A total of 41 characteristic structures were identified from an updated suspect list of 1606 LCMs. Multi-phenyl groups form the rigid cores of 85% of LCMs and produce 154 characteristic peaks in EI mass spectra. Monitoring the characteristic structures and fragments of LCMs may help identify new LCMs with the same rigid cores as those in the suspect list.

A critical comparison of vacuum UV (VUV) spectrometer and electron ionization single quadrupole mass spectrometer detectors for the analysis of alkylbenzenes in gasoline by gas chromatography: Experimental and statistical aspects

Recent advances in benchtop vacuum ultraviolet (VUV) spectrometers have yielded effective universal detectors for gas chromatography (GC). The ability of these detectors to acquire absorbance spectra from 125 nm to 430 nm poses an alternative to the gold standard of mass spectrometry (MS) as a sensitive and selective GC detector. The applications of GC/VUV extend into many areas. Featured here is the potential application of GC/VUV to the analysis of ignitable liquids, which may be found on debris from suspected arson fires. A particular compound class of interest is the alkylbenzenes, as they are a significant component in fuels such as gasoline, petroleum distillates, and aromatic solvents such as degreasers and cleaning solvents. To measure the sensitivity, selectivity and specificity of GC-VUV and GC-MS for alkylbenzenes we employed both library search methods and chemometric analysis using discriminant analysis. The GC-VUV detector was found to have superior specificity to the GC-MS detector in full scan mode. The GC-VUV detector was able to identify all alkylbenzenes correctly, including the correct identification of all structural isomers. LODs for both GC-VUV and GC-MS were found to be picograms on column.

Combining linear retention index and electron ionization mass spectrometry for a reliable identification in nano liquid chromatography

The present research is focused on the object to improve identification capability in liquid chromatography (LC), by creating a system as similar as possible to gas chromatography (GC), where the combination/complementarity of Linear Retention Index (LRI) and Electron Ionization Mass Spectrometry (EI-MS) data makes the identification process easy, automatic and reliable. Conversely, in LC the untargeted characterization of real-world samples is still a challenge, due to the not repeatable and poorly informative nature of typical atmospheric pressure ionization mass spectrometry, normally hyphenated to LC. In the last decades the miniaturization of LC instrumentation together with the considerable progresses in MS vacuum pump capability has made the LC-EI-MS hyphenation more feasible. In the present work, a prototypal nanoLC-EI-MS system was used for the determination of typically LC-amenable compunds, such as coumarins, furocoumarins and polymethoxyflavones in citrus essential oils. All the compounds provided high quality EI-MS spectra, evaluated by the comparison with thousands of spectra present in commercial EI-MS libraries. Spectral similarities major than 80% were achieved. Furthermore, an LRI system, based on the use of an alkyl aryl ketone homologue reference series, was proposed as additional filter to achieve a univocal identification. Then, a novel dual-filter LRI/EI-MS library was built and resulted very helpful in the case of isomeric compounds characterized by identical EI-MS spectrum, but different retention behaviour. The very low inter-day variability attained for each LRI value, together with the satisfactory chromatographic resolution of the developed method, led to a 100% reliability of the identification process based on LRI.

Mass Spectral Library Quality Assurance by Inter-Library Comparison

A method to discover and correct errors in mass spectral libraries is described. Comparing across a set of highly curated reference libraries compounds that have the same chemical structure quickly identifies entries that are outliers. In cases where three or more entries for the same compound are compared, the outlier as determined by visual inspection was almost always found to contain the error. These errors were either in the spectrum itself or in the chemical descriptors that accompanied it. The method is demonstrated on finding errors in compounds of forensic interest in the NIST/EPA/NIH Mass Spectral Library. The target list of compounds checked was the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) mass spectral library. Some examples of errors found are described. A checklist of errors that curators should look for when performing inter-library comparisons is provided. Graphical Abstract ᅟ.