Electron Ionization Mass Research Articles

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.

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.

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.

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.

A novel approach to the analysis of spin-trapped free radicals using dimethyl sulfoxide and gas chromatography – mass spectrometry (GC-MS) with both solvent extraction and headspace solid phase microextraction (HS-SPME)

In this study, we have utilized a novel strategy based upon the use of dimethyl sulfoxide (DMSO) and gas chromatography-mass spectrometry (GC-MS) for the detection and identification of spin-trapped free radicals. Hydroxymethyl ( . CH2OH) radicals, generated by Fenton-type chemistry, have been trapped by N-tert-butyl-α-phenylnitrone (PBN) or one of its derivatives in the presence of DMSO to form a 1,3-diadduct [PBN-(CH2OH)(CH3)], which may be detected directly in the reaction mixture following chloroform extraction or in the reaction vial headspace by sampling with SPME. Separation and identification have been carried out by capillary gas chromatography coupled to electron-ionization mass spectrometry (EI-MS). The results demonstrate that using DMSO aids GC-MS analysis of spin-trapped free radicals via the formation of radical-methyl di-adducts that are sufficiently volatile to be sampled both in the headspace or by an extracting solvent without the need for a derivatization step using silylating agents.

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.

Compound identification via deep classification model for electron-ionization mass spectrometry

Compound identification in electron-ionization mass spectrometry (EI-MS) is usually achieved by matching the query mass spectrum to the well-collected reference spectral library. Although various similarity methods have been developed in recent years, it is still difficult to distinguish some similar mass spectra, especially for isomers. In this work, a deep learning based on classification model is proposed to improve the final compound identification. The replicate library of NIST05 is used as query data and main library is used as reference database. Through a simple library searching algorithm, a data set consisting of paired similar mass spectra is created. Based on the data set, two optimal deep classification models (model-1 and model-2) are trained to determine whether the query and candidate spectrum are same compound. To validate the proposed method, a series experiments are conducted by using the created classification model to aid random projection for compound identification. The experimental results show that the model-1 and model-2’s identification accuracy of Rank 1 are increased by 1.5% and 7.7% respectively. Contrasting three state-of-are similarity measure, the proposed classification model achieves the best identification performance.

Predicting Total Electron-Ionization Cross Sections and GC-MS Calibration Factors Using Machine Learning.

Concentrations in GC-MS using electron-ionization mass spectrometry can be determined without pure calibration standards through prediction of relative total-ionization cross sections. An atom- and group-based artificial neural network (FF-NN-AG) model is created to generate EI cross sections and calibrations for organic compounds. This model is easy to implement and is more accurate than the widely used atom-additivity-based correlation of Fitch and Sauter (Anal. Chem. 1983). Ninety-two new measurements of experimental EI cross sections (70-75 eV) are joined with different interlaboratory datasets, creating a 396-compound cross-section database, the largest to date. The FF-NN-AG model uses 16 atom-type descriptors, 79 structural-group descriptors, and one hidden layer of 10 nodes, trained 500 times. In each cycle, 96% of the compounds in this database are freshly chosen at random, and then the model is tested with the remaining 4%. The resulting r2 is 0.992 versus 0.904 for the Fitch and Sauter correlation, root mean square deviation is 2.8 versus 9.2, and maximum relative error is 0.30 versus 0.73. As an example of the model's use, a list of cross sections is generated for various sugars and anhydrosugars.

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.

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.

Polycyclic aromatic hydrocarbons (PAHs) and oxy- and nitro-PAHs in ambient air of the Arctic town Longyearbyen, Svalbard

Abstract. Polycyclic aromatic hydrocarbons (PAHs) are not declining in Arctic air despite reductions in their global emissions. In Svalbard, the Longyearbyen coal-fired power plant is considered to be one of the major local sources of PAHs. Power plant stack emissions and ambient air samples, collected simultaneously at 1 km (UNIS) and 6 km (Adventdalen) transect distance, were analysed (gaseous and particulate phases separately) for 22 nitro-PAHs, 8 oxy-PAHs, and 16 parent PAHs by gas chromatography in combination with single quadrupole electron capture negative ionization mass spectrometry (GC-ECNI-MS) and gas chromatography in combination with triple quadrupole electron ionization mass spectrometry (GC-EI-MS/MS). Results confirm low levels of PAH emissions (∑16 PAHs =1.5 µg kg−1 coal) from the power plant. Phenanthrene, 9,10-anthraquinone, 9-fluorenone, fluorene, fluoranthene, and pyrene accounted for 85 % of the plant emission (not including naphthalene). A dilution effect was observed for the transect ambient air samples: 1.26±0.16 and 0.63±0.14 ng m−3 were the sum of all 47 PAH derivatives for UNIS and Adventdalen, respectively. The PAH profile was homogeneous for these recipient stations with phenanthrene and 9-fluorenone being most abundant. Multivariate statistical analysis confirmed coal combustion and vehicle and marine traffic as the predominant sources of PAHs. Secondary atmospheric formation of 9-nitroanthracene and 2+3-nitrofluoranthene was evaluated and concluded. PAHs partitioning between gaseous and particulate phases showed a strong dependence on ambient temperatures and humidity. The present study contributes important data which can be utilized to eliminate uncertainties in model predictions that aim to assess the extent and impacts of Arctic atmospheric contaminants.

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.

Analysis of impurities in pharmaceuticals by LC-MS with cold electron ionization.

Pharmaceuticals require careful and precise determination of their impurities that might harm the user upon consumption. Although today, the most common technique for impurities identification is liquid chromatography-mass spectrometry (LC-MS/MS), it has several downsides due to the nature of the ionization method. Also, the analyses in many cases are targeted thus despite being present, some of the compounds will not be revealed. In this paper, we propose and show a new method for untargeted analysis and identification of impurities in active pharmaceutical ingredients (APIs). The instrument used for these analyses is a novel electron ionization (EI) LC-MS with supersonic molecular beams (SMB). The EI-LC-MS-SMB was implemented for analyses of several drug samples spiked with an impurity. The instrument provides EI mass spectra with enhanced molecular ions, named Cold EI, which increases the identification probabilities when the compound is identified with the aid of an EI library like National Institute of Standards and Technology (NIST). We analyzed ibuprofen and its impurities, and both the API and the expected impurity were identified with names and structures by the NIST library. Moreover, other unexpected impurities were found and identified proving the ability of the EI-LC-MS-SMB system for truly untargeted analysis. The results show a broad dynamic range of four orders of magnitude at the same run with a signal-to-noise ratio of over 10 000 for the API and almost uniform response.

Discrimination of seized drug positional isomers based on statistical comparison of electron-ionization mass spectra

Positional isomers of novel psychoactive substances (NPS) present challenges in seized drug identification given the high degree of similarity in the resulting electron-ionization (EI) mass spectra. In this work, a previously developed method, which is based on the unequal variance t-test, is applied to statistically compare mass spectra with a specific focus on distinction of positional isomers. Two sets of positional isomers were statistically compared: ortho-, meta-, and para-isomers of ethylmethcathinone (EMC) and ortho-, meta-, and para-isomers of fluoromethamphetamine (FMA). Spectra were also subjected to principal components analysis (PCA) to identify ions contributing to the variance in each data set.For both the EMCs and FMAs, spectra of corresponding isomers were statistically associated at the 99.9% confidence level. Random-match probabilities for associations, which estimate the probability that the mass spectral fragmentation pattern occurs by random chance alone, ranged from 6.5 × 10−35– 5.9 × 10−27. For the EMC isomers, discrimination of the ortho-, meta-, and para-isomers was achieved at the 99.9% confidence level, with up to 16 ions responsible for discrimination. For the FMA isomers, discrimination of isomers was also achieved, albeit at the 99% confidence level due to the higher degree of spectral similarity among these isomers. For FMA comparisons, up to 10 discriminating ions were identified, with the lower number of ions a result of the higher spectral similarity. For both sets of isomers, there was correspondence in the discriminating ions identified by the statistical comparison method and by PCA.

Better screening of non-target pollutants in complex samples using advanced chromatographic and mass spectrometric techniques

The number of priority and emerging contaminants nowadays exceeds several thousands. As a consequence, it is a daunting task to monitor thousands of compounds using classical gas chromatography–mass spectrometry (GC–MS). Preliminary non-targeted screening is thus usually performed to identify the most relevant contaminants. Here we analyzed complex environmental samples of snow, rain water and cloud water from the Arctic, France, Chile, and Russia by two-dimensional gas chromatography (GC × GC) with ionization methods including electron ionization (EI), positive chemical ionization (PCI), and electron capture negative ionization (ECNI) modes, combined with high-resolution mass spectrometry. This approach combines the separation capacity of GC × GC, detailed EI mass spectral libraries, the softness of PCI, and the selectivity of ECNI. Switching between ionization modes without any hardware change allowed to increase the information capacity and reliability of analysis. The structural elucidation becomes easier and more reliable due to the detection of molecular ions in PCI and ECNI modes with corresponding extensive fragmentation in EI, while the ECNI mode improves about 100 times the detection limits for environmentally relevant halogenated and nitro compounds. Overall, a notable enhancement of the analytical capabilities for both targeted and non-targeted purposes is achieved.

Mass Spectra of New Heterocycles: XXI. Study of Alkyl [(5-Amino-1H-pyrrol-2-yl)sulfanyl]acetates by Electron and Chemical Ionization Mass Spectrometry

The fragmentation of previously inaccessible alkyl [(5-amino-1H-pyrrol-2-yl)sulfanyl]acetates under electron (70 eV) and chemical (reactant gas methane) ionization conditions was studied for the first time. Under electron ionization, all the studied compounds form a molecular ion (Irel 7–100%), the main primary fragmentation pathway of which is associated with the C–S bond cleavage in the sulfanyl group and elimination of the ester fragment (R4OCOCH2) in the form of a radical. The chemical ionization of alkyl [(5-amino-1H-pyrrol-2-yl)sulfanyl]acetates is characterized by protonation, recharging, and electrophilic addition. The base peak belongs to an [M + H]+ ion. Chemical ionization is accompanied by the elimination of an R4OCOCH2 radical from the M+• and [M + Et]+ ions and an R4OCOCHS molecule from the M+• and [M + H]+ ions.

Features of the Identification of Trialkyl Phosphites in Reaction Mixtures and Their Characterization by Gas Chromatography–Mass Spectrometry

The interaction of aliphatic alcohols ROH with phosphorus trichloride in the absence of bases leads to the formation of exclusively dialkyl phosphonates (RO)2PHO. To obtain trialkyl phosphites (RO)3P, insufficiently described to date, the pH of the reaction mixtures was adjusted by adding N,N-dimethylaniline (pKa 5.1 ± 0.1). The identification of trialkyl phosphites directly in reaction mixtures without preparative isolation implies a joint consideration of their mass spectra and gas chromatographic retention indices, provided that all other components of such mixtures are identified. The need to comply with this condition has led to the identification of several homologues of a previously uncharacterized series of 2-alkoxy-1,3,2-dioxaphospholanes, formed from a random admixture of ethylene glycol. The use of such combined mass spectrometric parameters as homologous increments of retention indices helps to distinguish trialkyl phosphites from isobaric dialkyl phosphonates; the compounds of both series belong to the homologous group of y = 12, y ≡ M(mod14). Despite the absence of molecular ion signals in the electron ionization (EI) mass spectra, the molecular weights of trialkyl phosphites can be estimated. In addition, a comparison of the homologous increments of retention indices shows that, compared with dialkyl phosphonates, trialkyl phosphites are significantly less polar.

Comparative gas chromatographic/mass spectrometric characterization of di- and trialkyl phosphites.

Homologous series of alkyl esters of phosphorus-containing acids, namely, dialkyl phosphonates (synonym: dialkyl phosphites) and trialkyl phosphites, were characterized by electron ionization (EI) mass spectra and gas chromatographic retention indices (GC RI) on semi-standard non-polar stationary phases. It is confirmed that GC/MS characterization of any sets of homologues should not be restricted to independent registration of these analytical parameters. Their joint processing in the form of so-called homologous increments of GC RIs means, firstly, a novel way of evaluating the chromatographic polarity of analytes and, secondly, a new algorithm for the prediction of their molecular weights if no peaks of molecular ions are registered in the mass spectra. A standard GC/MS technique, including determination of GC RIs on semi-standard nonpolar stationary phases in temperature-programmed regime and electron ionization (EI) mass spectra was used. A total of 31 dialkyl phosphonate homologues and 37 trialkyl phosphite homologues were characterized by EI mass spectra and GC RIs for the first time. Joint processing of these analytical parameters allows the calculation of so-called homologous increments of GC RIs, which are useful parameters for evaluating the chromatographic polarity of analytes and predicting their molecular weights. GC/MS characterization of any sets of homologues should not be restricted to independent registration of the mass spectra and chromatographic retention parameters. Their joint processing in the form of so-called homologous increments of GC retention indices means, firstly, a novel way of evaluating the chromatographic polarity of analytes and, secondly, a new algorithm for predicting their molecular weights.