Electron Ionization Mass Spectra Research Articles

Evaluating the Accuracy of the QCEIMS Approach for Computational Prediction of Electron Ionization Mass Spectra of Purines and Pyrimidines.

Mass spectrometry is the most commonly used method for compound annotation in metabolomics. However, most mass spectra in untargeted assays cannot be annotated with specific compound structures because reference mass spectral libraries are far smaller than the complement of known molecules. Theoretically predicted mass spectra might be used as a substitute for experimental spectra especially for compounds that are not commercially available. For example, the Quantum Chemistry Electron Ionization Mass Spectra (QCEIMS) method can predict 70 eV electron ionization mass spectra from any given input molecular structure. In this work, we investigated the accuracy of QCEIMS predictions of electron ionization (EI) mass spectra for 80 purine and pyrimidine derivatives in comparison to experimental data in the NIST 17 database. Similarity scores between every pair of predicted and experimental spectra revealed that 45% of the compounds were found as the correct top hit when QCEIMS predicted spectra were matched against the NIST17 library of >267,000 EI spectra, and 74% of the compounds were found within the top 10 hits. We then investigated the impact of matching, missing, and additional fragment ions in predicted EI mass spectra versus ion abundances in MS similarity scores. We further include detailed studies of fragmentation pathways such as retro Diels–Alder reactions to predict neutral losses of (iso)cyanic acid, hydrogen cyanide, or cyanamide in the mass spectra of purines and pyrimidines. We describe how trends in prediction accuracy correlate with the chemistry of the input compounds to better understand how mechanisms of QCEIMS predictions could be improved in future developments. We conclude that QCEIMS is useful for generating large-scale predicted mass spectral libraries for identification of compounds that are absent from experimental libraries and that are not commercially available.

Quantum Chemical Prediction of Electron Ionization Mass Spectra of Trimethylsilylated Metabolites.

Chemical derivatization, especially silylation, is widely used in gas chromatography coupled to mass spectrometry (GC-MS). By introducing the trimethylsilyl (TMS) group to substitute active hydrogens in the molecule, thermostable volatile compounds are created that can be easily analyzed. While large GC-MS libraries are available, the number of spectra for TMS-derivatized compounds is comparatively small. In addition, many metabolites cannot be purchased to produce authentic library spectra. Therefore, computationally generated in silico mass spectral databases need to take TMS derivatizations into account for metabolomics. The quantum chemistry method QCEIMS is an automatic method to generate electron ionization (EI) mass spectra directly from compound structures. To evaluate the performance of the QCEIMS method for TMS-derivatized compounds, we chose 816 trimethylsilyl derivatives of organic acids, alcohols, amides, amines, and thiols to compare in silico-generated spectra against the experimental EI mass spectra from the NIST17 library. Overall, in silico spectra showed a weighted dot score similarity (1000 is maximum) of 635 compared to the NIST17 experimental spectra. Aromatic compounds yielded a better prediction accuracy with an average similarity score of 808, while oxygen-containing molecules showed lower accuracy with only an average score of 609. Such similarity scores are useful for annotation of small molecules in untargeted GC-MS-based metabolomics, suggesting that QCEIMS methods can be extended to compounds that are not present in experimental databases. Despite this overall success, 37% of all experimentally observed ions were not found in QCEIMS predictions. We investigated QCEIMS trajectories in detail and found missed fragmentations in specific rearrangement reactions. Such findings open the way forward for future improvements to the QCEIMS software.

Beyond the ground state: predicting electron ionization mass spectra using excited state molecular dynamics

Beyond the ground state: predicting electron ionization mass spectra using excited state molecular dynamics

Automated high confidence compound identification of electron ionization mass spectra for nontargeted analysis

Nontargeted analysis based on mass spectrometry is a rising practice in environmental monitoring for identifying contaminants of emerging concern. Nontargeted analysis performed using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC/TOF-MS) generates large numbers of possible analytes. Moreover, the default spectral library similarity score-based search algorithm used by LECO® ChromaTOF® does not ensure that high similarity scores result in correct library matches. Therefore, an additional manual screening is necessary, but leads to human errors especially when dealing with large amounts of data. To improve the speed and accuracy of the chemical identification, we developed CINeMA.py (Classification Is Never Manual Again). This programming suite automates GC×GC/TOF-MS data interpretation by determining the confidence of a match between the observed analyte mass spectrum and the LECO® ChromaTOF® software generated library hit from the NIST Electron Ionization Mass Spectral (NIST EI-MS) library. Our script allows the user to evaluate the confidence of the match using an algorithmic method that mimics the manual curation process and two different machine learning approaches (neural networks and random forest). The script allows the user to adjust various parameters (e.g., similarity threshold) and study their effects on prediction accuracy. To test CINeMA.py, we used data from two different environmental contaminant studies: an EPA study on household dust and a study on stormwater runoff. Using a reference set based on the analysis performed by highly trained users of the ChromaTOF and GC×GC/TOF-MS systems, the random forest model had the highest prediction accuracies of 86% and 83% on the EPA and Stormwater data sets, respectively. The algorithmic approach had the second-best prediction accuracy (82% and 79%), while the neural network accuracy had the lowest (63% and 67%). All the approaches required less than 1 min to classify 986 observed analytes, whereas manual data analysis required hours or days to complete. Our methods were also able to detect high confidence matches missed during the manual review. Overall, CINeMA.py provides users with a powerful suite of tools that should significantly speed-up data analysis while reducing the possibilities of manual errors and discrepancies among users, and can be applicable to other GC/EI-MS instrument based nontargeted analysis.

Cold Electron Ionization (EI) Is Not a Supplementary Ion Source to Standard EI. It is a Highly Superior Replacement Ion Source.

GC-MS usually employs a 70 eV electron ionization (EI) ion source, which provides mass spectra with detailed fragment ion information that are amenable for library search and identification with names and structures at the isomer level. However, conventional EI often suffers from low intensity or the absence of molecular ions, which reduces detection and identification capabilities in analyses. In an attempt to enhance the molecular ions, several softer ion sources are being used to supplement standard EI, including chemical ionization (CI), atmospheric pressure chemical ionization (APCI), field ionization (FI), photoionization (PI), and low electron energy EI. However, the most advantageous way to enhance molecular ions is to use cold EI, which employs 70 eV EI of cold molecules in supersonic molecular beams. Cold EI yields classical EI mass spectra with highly enhanced molecular ions, which still provides high detectability and library-searchable mass spectra. In this paper, we explain and discuss why cold EI is not a supplementary ion source to standard EI, but rather it is a highly superior replacement to standard EI. With cold EI, there is no need for standard EI or any other supplemental ion source. We describe 16 benefits and unique features of cold EI that not only yield better results for existing applications but also significantly extend the range of compounds and applications amenable for GC-MS analysis.

Proximity Effects in Mass Spectra of Benzanilides.

The analytical value of peaks arising by a proximity effect in the electron ionization mass spectra of benzanilides has been established by examining the spectra of numerous examples of general structure XC6H4NHCOC6H4Y. Significant [M-X]+ signals are observed only when X = Cl, Br, I or CH3O in the 2-position. The presence of strong [M-X]+ signals, but negligibly weak [M-Y]+ peaks, even when the C-Y bond would be expected to break more readily than the C-X bond, indicates that these diagnostically useful signals do not arise by simple cleavage. Similarly, the presence of an appreciable [M-Cl]+ signal, but no [M-Br]+ signal, in the spectra of representative examples of 4-Br-2ClC6H3NHCOC6H4Y, reveals that loss of a substituent from the 2-position occurs much more rapidly than fission of a weaker bond to a substituent in the 4-position. These trends are interpreted in terms of cyclization of the ionized 2-substituted benzanilide, followed by elimination of the substituent originally in the 2-position, to form a protonated 2-arylbenzoxazole.

Molecular structure, spectroscopy and photochemistry of alprazolam

In this article, a comprehensive study of the molecular structure, spectroscopy, and photochemistry of alprazolam (Xanax®; 8-chloro-1-methyl-6-phenyl-4H-[1,2,4]triazolo[4,3-a][1,4]benzodiazepine) is reported. The structure of the isolated molecule of the compound was investigated using density functional theory (DFT), revealing that the molecule exists in a single conformer, which is associated with 12 equivalent-by-symmetry minima. The molecules of the compound were trapped from the gas phase into a low temperature (10 K) argon matrix, and the infrared (IR) spectrum of the matrix-isolated monomers was obtained and assigned. The matrix-isolated molecules were then subjected to in situ ultraviolet (UV) irradiation. It was concluded that alprazolam is photostable under these experimental conditions, contrarily to what is known to happen for the compound in solution or in solid state in the presence of excipients used in the pharmaceutical formulations. An explanation for the photostability of the matrix-isolated compound is provided, based on rapid recombinations of the biradical formed from the UV-induced diazepine ring cleavage or the chlorine atom and the complementary radical resulting from the scissoring of the C–Cl bond, which are favored by the cage confinement of the matrix-isolated molecules. The major fragmentation channels of the alprazolam molecule upon electron bombardment (70 eV) were determined by analysis of its electron ionization mass spectrum, which reveals that the major primary fragmentation processes lead to formation of cyanobenzene, N2, HCl (Cl2), and benzene.The compound was also investigated in solution by multinuclear (1H, 13C and 15N) nuclear magnetic resonance (NMR) and ultraviolet (UV) spectroscopies, and in crystalline phase (P-1 polymorph) through IR and Raman spectroscopies. In addition, the structure of the crystal, previously reported in the literature [M. R. Caira, B. Easter, S. Honiball, A. Horne and L. R. Nassimbeni, Structure and Thermal Stability of Alprazolam and Selected Solvates, J. Pharm. Sci., 1995, 84, 1379–1384], was revisited in order to evaluate the relative importance of the different types of intermolecular interactions, using Hirshfeld surface analysis, the CE-B3LYP energy decomposition model, and the harmonic oscillator model of aromaticity (HOMA) index. Finally, the enthalpy of sublimation of the crystal was estimated from the CE-B3LYP calculated lattice energy.

Identify low mass volatile organic compounds from cometary ice analogs using gas chromatography coupled to an Orbitrap mass spectrometer associated to electron and chemical ionizations

Analysis of organic matter extracted from meteorites showed that solar system objects present an important molecular diversity. To improve our understanding of such organic matter, new analytical technologies must be developed. The present study displays the first experiments using a GC-FT-Orbitrap-MS to decipher the molecular diversity observed in experiments simulating the evolution of cometary ices. The proposed analytical strategy focuses on the analysis of 110 volatile organic compounds (VOC) with mainly 1 to 6 carbon atoms generated in such cometary ice analogs. Electron ionization (EI) and chemical ionization (CI) modes with methane (CH4) or ammonia (NH3) were optimized and compared. Those developments maximized the intensity of molecular, protonated or deprotonated ions, and improved high-resolution molecular formula unambiguous identification: EI mode is too energetic to provides there detection, while it is not the case in CI mode. Particularly, NH3 as a reagent gas improves amine identification in positive mode (PCI), and esters, alcohols, carbonyls, amides, carboxylic acids and nitriles in negative mode (NCI). The combination of both EI and CI mass spectrum analysis improves molecular identification, thanks to the detection of molecular, deprotonated or protonated ion of highest intensity and fragment formula assignments. The EI and NCI NH3 combination allows formula assignments up to 94% of our database with limit of detection up to 7 ppm. This procedure has been validated for untargeted GC-FT-Orbitrap-MS analysis of VOC coming from the processing of cometary ice analogs.

From QCEIMS to QCxMS: A Tool to Routinely Calculate CID Mass Spectra Using Molecular Dynamics.

Mass spectrometry (MS) is a powerful tool in chemical research and substance identification. For the computational modeling of electron ionization MS, we have developed the quantum-chemical electron ionization mass spectra (QCEIMS) program. Here, we present an extension of QCEIMS to calculate collision-induced dissociation (CID) spectra. The more general applicability is accounted for by the new name QCxMS, where "x" refers to EI or CID. To this end, fragmentation and rearrangement reactions are computed "on-the-fly" in Born-Oppenheimer molecular dynamics (MD) simulations with the semiempirical GFN2-xTB Hamiltonian, which provides an efficient quantum mechanical description of all elements up to Z = 86 (Rn). Through the explicit modeling of multicollision processes between precursor ions and neutral gas atoms as well as temperature-induced decomposition reactions, QCxMS provides detailed insight into the collision kinetics and fragmentation pathways. In combination with the CREST program to determine the preferential protonation sites, QCxMS becomes the first standalone MD-based program that can predict mass spectra based solely on molecular structures as input. We demonstrate this for six organic molecules with masses ranging from 159 to 296 Da, for which QCxMS yields CID spectra in reasonable agreement with experiments.

Predicting the Mass Spectra of Environmental Pollutants Using Computational Chemistry: A Case Study and Critical Evaluation.

Organic pollutants can be identified by comparing their electron ionization (EI) mass spectra with those in libraries or obtained from authentic standards. Nevertheless, libraries are incomplete; standards may be unavailable or too costly, or their synthesis may be too time-consuming. This study evaluates the performance of quantum chemical electron ionization mass spectrometry (QCEIMS) vis-à-vis competitive fragmentation modeling (CFM) for suspect screening and unknown identification. EI mass spectra of 35 compounds, including halogenated organics, organophosphorus flame retardants (OPFRs), and disinfection byproducts were computed. Computational results were compared with EI mass spectra compiled in the NIST Library as well as collision-induced dissociation (CID) mass spectra obtained from radical cations M•+ generated by charge-exchange atmospheric pressure chemical ionization (APCI). The results indicate that QCEIMS performs equivalently or better than CFM. Average match factors between computed and experimental (NIST) EI mass spectra were 656 vs 503 for the halogenated organics, and on average, QCEIMS predicted 55% of the products generated by CID vs 17% predicted by CFM. QCEIMS predicted 37% of the OPFR CID products whereas CFM predicted 29%. QCEIMS performed comparably to a commercial combinatorial fragmentation method for suspect screening of a dust sample, identifying 19/20 targets. Examples of unknown pollutants, whose reference spectra were unavailable at the time of discovery, are also presented. The computational results suggest that QCEIMS can help guide the analyst in obtaining authentic standards and raise the possibility that, with advances in computing, an unknown may eventually be confirmed in hours as opposed to the days or months required to obtain authentic standards.

Calibration-Curve-Locking Database for Semi-Quantitative Metabolomics by Gas Chromatography/Mass Spectrometry.

Calibration-Curve-Locking Databases (CCLDs) have been constructed for automatic compound search and semi-quantitative screening by gas chromatography/mass spectrometry (GC/MS) in several fields. CCLD felicitates the semi-quantification of target compounds without calibration curve preparation because it contains the retention time (RT), calibration curves, and electron ionization (EI) mass spectra, which are obtained under stable apparatus conditions. Despite its usefulness, there is no CCLD for metabolomics. Herein, we developed a novel CCLD and semi-quantification framework for GC/MS-based metabolomics. All analytes were subjected to GC/MS after derivatization under stable apparatus conditions using (1) target tuning, (2) RT locking technique, and (3) automatic derivatization and injection by a robotic platform. The RTs and EI mass spectra were obtained from an existing authorized database. A quantifier ion and one or two qualifier ions were selected for each target metabolite. The calibration curves were obtained as plots of the peak area ratio of the target compounds to an internal standard versus the target compound concentration. These data were registered in a database as a novel CCLD. We examined the applicability of CCLD for analyzing human plasma, resulting in time-saving and labor-saving semi-qualitative screening without the need for standard substances.

Principles of Controlling the Correctness of Gas-Chromatographic Retention Indices of Previously Uncharacterized Analytes (Based on an Example of 2-Aryl-1,3-Dioxolanes and 2-Aryl-1,3-Dioxanes)

The series of the interaction products of substituted benzaldehydes XC6H4CHO with several aliphatic diols (ethanediol, 1,2-propanediol, 1,3-propanediol, 1,3-butanediol, and racemic 2,3-butanediol) were characterized for the first time by analytical parameters required for their chromatography–mass spectrometric identification: electron ionization mass spectra and gas-chromatographic retention indices (RIs) on a standard nonpolar polydimethylsiloxane stationary phase. It was found that it is expedient to combine this characterization of new compounds with controlling the correctness of the RIs by checking their correlations with data for one or several series of simpler and, therefore, characterized in more detail structural analogs. The proposed algorithm made it possible not only to confirm the correctness of all of the newly determined retention indices but also to reveal an erroneous reference value of the retention index of 4-ethoxyphenol. An appropriate selection of structural analogs provides an opportunity to use this method for controlling the retention indices of compounds in whose molecules steric interactions of structural fragments are manifested.

Reduction Reactions in the Ion Source in Electron Ionization Mass Spectrometry

Theoretically, electron ionization mass spectra should contain exclusively peaks of ions due to the monomolecular fragmentation of molecular ions. However, spectra of aromatic compounds with halogen atoms and nitro groups contain ion peaks with the composition not consistent with this postulate. Based on a detailed study of such ions by high-resolution mass spectrometry, we showed that their formation is associated with the reduction of the initial molecules at the metal walls of the ion source before their ionization. As a result, products of the reduction reaction of the corresponding composition are ionized. Nitro compounds are reduced to the corresponding amines, while halogenated compounds lose the halogen atom, turning into unsubstituted substrates. Water molecules on the metal surface of the ion source act as reduction agents. This process does not depend on the geometry of the source and proceeds in any mass spectrometer.

A Comparison of the Limits of Detection for a Number of Surrogates of Organophosphorus Toxic Agents and Methylphosphonic Acid Silyl Derivatives and its O-Alkyl Esters by Gas Chromatography/Mass Spectrometry with Various Ionization Methods and a Flameless Thermionic Ionization Detector

Electron ionization (EI) and chemical ionization (CI) mass spectra of methylphosphonic acid phosphates and phosphonates (surrogates of respective chemical war agents) and silyl derivatives and its O-alkyl esters (markers of hydrolysis products of chemical war agents) were investigated and respective limits of detection were determined by GC/MS (EI) and GC/MS (CI) in a single ion monitoring mode. Atmospheric pressure photo- and photochemical ionization (APPI/APPCI) mass spectra of the same compounds were investigated by GC/MS (APPI/APPCI) and conditions providing the registration of mass spectra consisting of only one peak, corresponding to the M+ or [M + H]+ ion, were chosen and the limits of detection in the single ion monitoring mode were determined. In addition, the limits of detection for all of the studied compounds by GC with a flameless thermionic detector (FTID) were determined. The limits of detection for phosphates and phosphonates by GC/MS (EI) (MS/MS), GC/MS (CI), GC/MS (APPI), and GC/MS (APPCI) and in the single ion monitoring mode were 0.2–1.0 pg, 1.0–6.0 pg, 10–30 pg, and 0.1–0.3 pg, respectively. For methylphosphonic acid silyl derivatives and its O-alkyl esters, the respective limits of detection were 0.2–4.0 pg, 1.0–5.0 pg, 10–25 pg, and 1.0–3.0 pg. The limits of detection for all the studied compounds by GC with FTID were 0.3–0.4 pg. This means that the rapid screening of the samples to be investigated should be based on the last named method and GC/MS must be used only for the selected samples.

Predicting in silico electron ionization mass spectra using quantum chemistry

Compound identification by mass spectrometry needs reference mass spectra. While there are over 102 million compounds in PubChem, less than 300,000 curated electron ionization (EI) mass spectra are available from NIST or MoNA mass spectral databases. Here, we test quantum chemistry methods (QCEIMS) to generate in silico EI mass spectra (MS) by combining molecular dynamics (MD) with statistical methods. To test the accuracy of predictions, in silico mass spectra of 451 small molecules were generated and compared to experimental spectra from the NIST 17 mass spectral library. The compounds covered 43 chemical classes, ranging up to 358 Da. Organic oxygen compounds had a lower matching accuracy, while computation time exponentially increased with molecular size. The parameter space was probed to increase prediction accuracy including initial temperatures, the number of MD trajectories and impact excess energy (IEE). Conformational flexibility was not correlated to the accuracy of predictions. Overall, QCEIMS can predict 70 eV electron ionization spectra of chemicals from first principles. Improved methods to calculate potential energy surfaces (PES) are still needed before QCEIMS mass spectra of novel molecules can be generated at large scale.

Detection and identification of ethanal-derived spin-trapped free radicals using headspace thermal desorption gas chromatography-mass spectrometry (TD-GC-MS)

In this study, we demonstrate a novel approach to the detection and identification of the products of spin-trapped free radicals. Hydroxyl free radicals were generated by Fenton-based chemistry in the presence of ethanal and the spin-trapping agent N-tert-butyl-α-phenylnitrone (PBN). The resulting volatile compounds present in the reaction vial headspace were collected using thermal desorption (TD) and analysed by gas chromatography-mass spectrometry (GC-MS). Eleven compounds were detected in the headspace, and their identification was aided by using either a fluorinated or deuterated analogue of PBN as an alternative spin trap and/or deuterated ethanal (CD3CHO) as the secondary source of free radicals. The electron-ionisation (EI) mass spectra clearly demonstrate the “capture” of methyl radicals; two of the compounds detected were identified as containing one methyl group derived from ethanal, and four were shown to contain two methyl groups. This study demonstrates that sampling the reaction headspace using TD-GC-MS is a viable method for analysing products of free radical trapping, and potentially may be applied to a wide range of free radical systems.

Specific Features of the Gas Chromatography–Mass Spectrometry Identification of Monoalkyl Phthalates

A similarity of electron ionization mass spectra of various alkyl esters of benzene-1,2-dicarboxylic (phthalic) acid places special demands on the reliability of the identification of monoalkyl phthalates, often recognized as dialkyl phthalates and vice versa. An original mass spectrometric criterion is proposed for the group identification of monoalkyl phthalates (assignment to a subgroup of homologues), which assumes the calculation of the total relative intensity of ion peaks at m/z > 170. In the mass spectra of monoalkyl esters, this value does not exceed 1%, whereas for dialkyl ethers, it varies from 1 to 172%. Within the set subgroups of isomers, it becomes effective to use the homologous increments of the retention indices, iRI = RI – 100x, where x = int (M/14), to refine the identification results. Using predefined iRI values and the ratio М ≈ 0.14(RI – iRI) + y, we can estimate the molecular weights of compounds in the mass spectra of which the molecular ion signals are not detected or are of low intensity (including monoalkyl phthalates). In addition, iRI values are in many cases informative for estimating the number of branches of the sp3 carbon skeleton of molecules (Z) based on regression relations of the form of iRI = aZ + b. The examination of homologous increments of the retention indices of dialkyl phthalates revealed an anomalous dependence of their values on the number of carbon atoms in the alkyl fragments of the molecules: from +125 (СН3) to –33 (С10Н21). In the subgroup of monoalkyl phthalates, such anomalies were not observed.

A comparison of electron ionization mass spectra obtained at 70 eV, low electron energies, and with cold EI and their NIST library identification probabilities

Electron ionization (EI) mass spectra of 46 compounds from several different compound classes were measured. Their molecular ion abundances were compared as obtained with 70-eV EI, with low eV EI (such as 14 eV), and with EI mass spectra of vibrationally cold molecules in supersonic molecular beams (Cold EI). We further compared these mass spectra in their National Institute of Standards and Technology (NIST) library identification probabilities. We found that Low eV EI is not a soft ionization method, and it has little or no influence on the molecular ion relative abundances for large molecules and those with weak or no molecular ions. Low eV EI for compounds with abundant or dominant molecular ions in their 70 eV mass spectra results in the reduction of low mass fragment ions abundances thereby reducing their NIST library identification probabilities thus rarely justifies its use in real-world applications. Cold EI significantly enhances the relative abundance of the molecular ions particularly for large compounds; yet, it retains the low mass fragment ions; hence, Cold EI mass spectra can be effectively identified by the NIST library. Different standard EI ion sources provide different 70 eV EI mass spectra. Among the Agilent technologies ion sources, the "Extractor" exhibits relatively abundant molecular ions compared with the "Inert" ion source, while the "High efficiency source" (HES) provides mass spectra with depleted molecular ions compared with the "Inert" ion source or NIST library mass spectra. These conclusions are demonstrated and supported by experimental data in nine figures and two tables.

Analytical profile of N-ethyl-N-cyclopropyl lysergamide (ECPLA), an isomer of lysergic acid 2,4-dimethylazetidide (LSZ).

Recent investigations have shown that N-ethyl-N-cyclopropyl lysergamide (ECPLA) produces LSD-like behavioral effects in mice, which suggests that it may act as a hallucinogen in humans. Although the use of ECPLA as a recreational drug has been limited, key analytical data that can be used to detect ECPLA are required for future forensic and clinical investigations. ECPLA is an isomer of (2′S,4′S)-lysergic acid 2,4-dimethylazetidide (LSZ), a lysergamide that emerged as a recreational drug in 2013. Several analytical approaches were examined, including single- and tandem mass spectrometry platforms at low and high resolution, gas- and liquid chromatography (GC, LC), nuclear magnetic resonance spectroscopy (NMR), and GC condensed-phase infrared spectroscopy (GC-sIR). ECPLA and LSZ could be differentiated by NMR, GC-sIR, GC, and LC-based methods. The electron ionization mass spectra of ECPLA and LSZ contained ion clusters typically observed with related lysergamides such as m/z 150–155, m/z 177–182, m/z 191–197, m/z 205–208, and m/z 219–224. One of the significant differences in abundance related to these clusters included ions at m/z 196 and m/z 207/208. The base peaks were detected at m/z 221 in both cases followed by the retro-Diels-Alder fragment at m/z 292. Minor but noticeable differences between the two isomers could also be seen in the relative abundance of m/z 98 and m/z 41. Electrospray ionization mass spectra included lysergamide-related ions at m/z 281, 251, 223, 208, 197, 180, and 140. LSZ (but not ECPLA) showed product ions at m/z 267 and m/z 98 under the conditions used.

Integrated qualitative analysis of polymer sample by pyrolysis-gas chromatography combined with high-resolution mass spectrometry: Using accurate mass measurement results from both electron ionization and soft ionization.

Gas chromatography/mass spectrometry (GC/MS) is a powerful analytical tool used to separate and then identify volatile compounds through library database searches. However, as not all compounds are registered in these databases, it is not uncommon to detect unregistered components. Therefore, new analytical techniques were developed that utilize methods of identification beyond database searches alone. Acquire data by using electron ionization (EI) and soft ionization (SI) with high-resolution mass spectrometry (HRMS). Use the EI mass spectra to library search for matches. Use the SI mass spectra for accurate mass analysis of the EI molecular ions. Conduct an isotope pattern analysis of the molecular ion to refine the possible candidate compositions. Use these compositions as a constraint for the accurate mass analysis of the EI fragment ions. If a given molecular ion formula is not correct, the EI fragment ions will not show good matches. Finally, all analytical results are integrated into a color-coded qualitative analysis report. The capabilities of this new integrated analytical method were assessed for a polymer resin sample that was measured by using pyrolysis-gas chromatography/high resolution time-of-flight mass spectrometry. A total of 161 compounds were detected in the total ion current chromatogram, and 154 of these compounds were identified as having only one chemical formula candidate with this new integrated qualitative analysis method. This new integrated qualitative analysis method gives analytical results independent of library search results. It can be applied to a variety of SI methods including chemical ionization, photoionization, field ionization, and low-energy EI.