Correlation analysis of modern analytical data - a chemometric dissection of spectral and chromatographic variables

The Standard Practices for Infrared Multivariate Quantitative Analysis (ASTM E1655) provide a guide for determining physicochemical properties of materials using multivariate calibration techniques applied to chemical sources that have high multicollinearity and correlated information. Partial least squares (PLS) is the most widely used multivariate regression method due to its excellent prediction capabilities and easy optimization. Initially applied to chromatographic data, PLS has also shown great results in near-infrared (NIR) and mid-infrared (MIR) spectroscopies. However, complex chemical matrices with low correlation may not be efficiently modeled using PLS or other multivariate analyses limited by grouping similar information (such as latent variables or principal components). Therefore, this study aims to evaluate the multicollinearity of different analytical techniques, such as high-temperature gas chromatography (HTGC), NIR, MIR, hydrogen nuclear magnetic resonance (1H NMR), carbon-13 nuclear magnetic resonance (13C NMR), and Fourier transform ion cyclotron resonance mass spectrometry coupled to the electrospray source in positive and negative ionization modes (ESI(±)FT-ICR). Descriptive statistics (coefficient of determination, R2) and principal component analysis (PCA) were used to identify the distribution of correlated information. Results showed that NIR and MIR spectroscopies exhibited a higher percentage of correlated variables, while 13C NMR and ESI(±)FT-ICR MS had more discrete profiles. Therefore, PLS development may be more effectively applied to NIR, MIR, and 1H NMR data, while 13C NMR and mass spectra may require other algorithms or variable selection methods in combination with PLS.

Characterization of Compositional Variability in Petroleum Substances

In the process of registration of substances of Unknown or Variable Composition, Complex Reaction Products or Biological Materials (UVCBs), information sufficient to enable substance identification must be provided. Substance identification for UVCBs formed through petroleum refining is particularly challenging due to their chemical complexity, as well as variability in refining process conditions and composition of the feedstocks. This study aimed to characterize compositional variability of petroleum UVCBs both within and across product categories. We utilized ion mobility spectrometry (IMS)-MS as a technique to evaluate detailed chemical composition of independent production cycle-derived samples of 6 petroleum products from 3 manufacturing categories (heavy aromatic, hydrotreated light paraffinic, and hydrotreated heavy paraffinic). Atmospheric pressure photoionization and drift tube IMS-MS were used to identify structurally related compounds and quantified between- and within-product variability. In addition, we determined both individual molecules and hydrocarbon blocks that were most variable in samples from different production cycles. We found that detailed chemical compositional data on petroleum UVCBs obtained from IMS-MS can provide the information necessary for hazard and risk characterization in terms of quantifying the variability of the products in a manufacturing category, as well as in subsequent production cycles of the same product.

Compositional Analysis of High-TAN Sudanese Crude Oil Using High-Resolution Mass Spectrometry and Study of the Effect of Temperature and Catalyst on Acidic Composition

Sudanese Fula crude oil, from the western region, is considered highly viscous and acidic and contains high amounts of heteroatoms (N and O) but a low sulfur content. This work presents an original and comprehensive analysis of its molecular composition in addition to an investigation of the effect of temperature and catalyst on the treatment of the acid fraction. The analysis was performed using a high-resolution Fourier transform mass spectrometer and Orbitrap-Elite with different ionization methods. The results reveal that the Fula crude oil contains a high abundance of nitrogen composition homologue classes N[H], NO₂[H], and NO[H]. Their hydrocarbon composition includes low to high aromatic hydrocarbons. The number of oxygen classes varies from acids containing monocarboxylic acids of O₂ to acids of multiple carboxylic and phenolic group (C _x H _y O₃ to C _x H _y O₁₅) classes, which indicate a high content of acidic moiety of 0.765%. In addition to oxygen classes, the acidic fraction that is present as a NO _x series indicates the presence of carboxylic carbazole acidic fraction. Low-temperature crude oil treatment at 200 °C decreases the intensity of acids. No significant reduction to low masses was observed; however, there was a clear reduction to high masses. At a high temperature of 350 °C, the carboxylic acid intensity increases (O₂ classes), and thus, heating crude oil to 350 °C is unfavorable as it increases the amount of monocarboxylic acids, which are primarily responsible for corrosion in refinery units. Predicted TAN values of residual samples show a reduction in TAN of 62% using thermal treatment at 200 °C, whereas there is an increase in TAN of 5% at 350 °C. A great reduction in acidity results from catalytic treatment with a transition metal catalyst of cobalt and iridium complex. A reduction in all acidic oils is observed; however, the greater reduction is found in mono- and dicarboxylic acids. Catalytic treatment is shown to result in an 85% reduction in predicted TAN values.

Naphthenic Acids: Formation, Role in Emulsion Stability, and Recent Advances in Mass Spectrometry-Based Analytical Methods

Naphthenic acids (NAs) are compounds naturally present in most petroleum sources comprised of complex mixtures with a highly variable composition depending on their origin. Their occurrence in crude oil can cause severe corrosion problems and catalysts deactivation, decreasing oil quality and consequently impacting its productivity and economic value. NAs structures also allow them to behave as surfactants, causing the formation and stabilization of emulsions. In face of the ongoing challenge of treatment of water-in-oil (W/O) or oil-in-water (O/W) emulsions in the oil and gas industry, it is important to understand how NAs act in emulsified systems and which acids are present in the interface. Considering that, this review describes the properties of NAs, their role in the formation and stability of oil emulsions, and the modern analytical methods used for the qualitative analysis of such acids.

Comprehensive Lists of Internal Calibrants for Ultrahigh-Resolution Mass Spectrometry Analysis of Crude Oil and Natural Organic Matter and Their Preparation Recipes

In this work, comprehensive lists of internal calibrants for accurate mass determination of molecules in crude oils, natural organic matter, and soil as well as their preparation recipes are presented. The lists include various sets of chemicals for positive- and negative-ion mode electrospray ionization, atmospheric pressure chemical ionization, atmospheric pressure photoionization, and laser desorption ionization. The chemicals were chosen based on their solvent compatibility, ionization efficiency, and accessibility. The sample preparation process was optimized for each ionization method and type of sample. The lists include detailed information on preparation solvent, concentrations, and mixing ratios of sample and calibrants. Internal calibration using the information in the lists results in successful calibration, and all the data presented in this study show root-mean-square errors between the theoretical and obtained m/z numbers of less than 0.4 ppm. The information presented in this study provides an important guideline for researchers working on complex mixtures with ultrahigh-resolution mass spectrometry.

Estimating the intermediate precision in petroleum analysis by (±)electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry

RATIONALE

Electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS) is an important analytical technique used for the elucidation of crude oil polar compounds at the molecular level, providing thousands of heteroatom compounds in a single analysis. Due to the high resolution, the complexity of data produced, and steps involved in spectra acquisition and processing, it is necessary to estimate its intermediate precision.

METHODS

Intermediate precision was estimated for positive- and negative-ion ionization modes (ESI(±)) using Composer® software for two Brazilian crude oil samples. The analytical parameters evaluated were the class distribution histogram, the double bond equivalent (DBE) distribution, and the DBE versus carbon number. The statistical parameters used to study the intermediate precision were calculated from the average, standard deviation, confidence interval (significance level at 5%), coefficient of variation (CV), intermediate precision limit (ISO 5725), and principal component analysis (PCA).

RESULTS

Two crude oil samples (A and B) were analyzed, in triplicate, for seven consecutive days by ESI(±) FT-ICR MS. The assigned class limit by ESI(+) for crude oil A was 0.42% (O₂ S[H] class) and for crude oil B was 0.04% (N₂ O₂ S[H] class). The assigned DBE intensity limits for the two crude oils were 0.04% for ESI(+) and 0.013% for ESI(-). The PCA for ESI(-) and ESI(+) modes presented better precision for crude oils B and A, respectively.

CONCLUSIONS

The most abundant classes and DBE of the majority class (i.e., with the highest intensity) are the parameters produced from the Composer® software that had the highest precision and can be used to estimate crude oil properties. The DBE values presented lower intermediate precision limit values (0.04%) than the assigned class values (0.4%). According to CV and PCA, ESI(+) was more precise for crude oil A (83% precision) and ESI(-) for crude oil B (84% precision).

Specification of the nitrogen functional group in a hydrotreated petroleum molecule using hydrogen/deuterium exchange electrospray ionization high-resolution mass spectrometry

Hydrotreatment is extensively used for the production of clean fuel. Attaining an understanding of the structural conversion of the nitrogen species during hydrotreatment is very challenging due to the compositional complexity and the absence of a proper characterization method. In the presented work, we coupled hydrogen/deuterium exchange (HDX) with positive-ion electrospray ionization high-resolution mass spectrometry ((+) ESI HR MS) to investigate the difference between the composition of the nitrogen-containing species and the functional groups before and after hydrotreatment. The solvent and additive were optimized for HDX (+) ESI HRMS through systematic evaluations on model nitrogen-containing compounds. We found that adding deuterated water (D₂O) and deuterated formic acid (DCOOD) significantly increased the degree of HDX and thus facilitated the identification of nitrogen functional groups. After application to the hydrotreated petroleum samples, the compositional variation of intermediate amine compounds during the heavy petroleum hydrotreatment process was clearly revealed.

DropMS: Petroleomics Data Treatment Based in Web Server for High-Resolution Mass Spectrometry

We have built an online tool with a user-friendly and browser-based interface to facilitate the processing of high resolution and precision oil mass spectrometry data. DropMS does not require software installations. Mass spectra are sent and processed by the server using various algorithms reported in the literature, such as S/N ratio filters, recalibrations, chemical formula assimilations, and data visualization using graphs and diagrams popularly known in mass spectrometry as Van Krevelen and Kendrick diagrams and DBE vs C#. To validate the algorithms used and the processing results, the same mass spectrum of a typical Brazilian oil sample was analyzed by ESI(+)-FT-ICR/MS and processed using Sierra Analytics DropMS and Composer to obtain good agreement between the heteroatomic classes found and the number of compounds assigned. The MS has chemical information spread over the entire spectrum. The PLS multivariate regression has the main objective of decomposing the most important information into latent variables in order to quantify the most evaluated properties. Finally, 12 processed petroleum FT-ICR MS spectra were used for a partial least-squares regression with seven latent variables for R² = 0.971 and RMSEC of 0.997 for API density property with a reference value range of 21-42.

Comparing Crude Oils with Different API Gravities on a Molecular Level Using Mass Spectrometric Analysis. Part 1: Whole Crude Oil

Different ionization techniques based on different principles have been applied for the direct mass spectrometric (MS) analysis of crude oils providing composition profiles. Such profiles have been used to infer a number of crude oil properties. We have tested the ability of two major atmospheric pressure ionization techniques, electrospray ionization (ESI(±)) and atmospheric pressure photoionization (APPI(+)), in conjunction with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The ultrahigh resolution and accuracy measurements of FT-ICR MS allow for the correlation of mass spectrometric (MS) data with crude oil American Petroleum Institute (API) gravities, which is a major quality parameter used to guide crude oil refining, and represents a value of the density of a crude oil. The double bond equivalent (DBE) distribution as a function of the classes of constituents, as well as the carbon numbers as measured by the carbon number distributions, were examined to correlate the API gravities of heavy, medium, and light crude oils with molecular FT-ICR MS data. An aromaticity tendency was found to directly correlate the FT-ICR MS data with API gravities, regardless of the ionization technique used. This means that an analysis on the molecular level can explain the differences between a heavy and a light crude oil on the basis of the aromaticity of the compounds in different classes. This tendency of FT-ICR MS with all three techniques, namely, ESI(+), ESI(−), and APPI(+), indicates that the molecular composition of the constituents of crude oils is directly associated with API gravity.

Evaluation of Thin-Layer Chromatography-Laser Desorption Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometric Imaging for Visualization of Crude Oil Interactions

A light oil was separated into four chromatographic fractions that serve as proxy for SARA fractions. The fractions were (semi)quantified on a rod by TLC-flame ionization detection and characterized on a plate with laser desorption ionization-mass spectrometry imaging (TLC-LDI-MS). Comparisons of (semi)quantitative TLC-FID and qualitative TLC-LDI-MS results showed that LDI-MS was most sensitive for detection of molecules in the polar P1 fraction, and, to some extent, for the aromatics fraction, while no signal was observed for the most polar P2 and saturates fractions. Based on these results, limits of the compositional space, as observed by the laser ionization technique, were evaluated. The molecular speciation between and within the spots of the aromatics and the P1 fractions were analyzed and interpreted in terms of oil-SiO₂ versus oil-solvent interactions, as a function of molecular characteristics such as DBE, aromaticity (H/C ratio), heteroatom content, degree of alkylation, and shielding of heteroatoms. In addition, the high oil loading resulted in an interesting bifurcation of the aromatics spot, which implies that oil-oil interactions can be enforced and studied in the TLC model system.

Multiparticle Simulations of Quadrupolar Ion Detection in an Ion Cyclotron Resonance Cell with Four Narrow Aperture Detection Electrodes

The current paradigm in FT-ICR cell design is to approximate the ideal three-dimensional quadratic trapping potential as closely as possible to maintain ion cloud spatial coherence and achieve long transients, either with hyperbolically shaped electrodes, shimming electrodes, or by dynamic harmonization. In sharp contrast, the FT-ICR analyzer cell with four narrow aperture detection electrodes (NADEL) introduces significant anharmonic terms to the trapping potential. This analyzer cell is capable of quadrupolar detection by which one can measure a signal that is close to the unperturbed cyclotron frequency. This is far less sensitive to trapping potential and space charge shifts than the reduced cyclotron frequency measured in conventional ICR cells. The quadrupolar mode of ion detection in NADEL cells has been examined previously by SIMION simulations of ion clouds with up to 500 ions per simulation. Here, the behavior of the NADEL analyzer cell is examined through particle-in-cell (PIC) simulations, which allows us to examine the behavior of large populations (tens of thousands) of ions with space charge considerations, and to calculate the induced charge on the NADEL detection electrodes, and thus the transient signal. PIC simulations confirm a unique spatial distribution of the ions, with a coherent motion that results in long transient signals. Dependence of the ion cloud and image current signal on cell design, ion energy, and magnetron radius are examined. Coalescence effects are compared with those found in a dynamically harmonized cell. The insensitivity of the measured cyclotron frequency to space-charge is demonstrated both with simulations and experimentally. Graphical Abstract ᅟ.