Total sulfur determination in residues of crude oil distillation using FT-IR/ATR and variable selection methods

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.

Thermal Oxidative Stability of Biodiesel/Petrodiesel Blends by Pressurized Differential Scanning Calorimetry and Its Calculated Cetane Index

Diesel fuel mixtures with high concentrations of biodiesel have been investigated to analyze the technical feasibility of their use in diesel cycle engines regarding thermal and oxidative properties. The results of combined techniques of oxidative stability, high Pressurized Differential Scanning Calorimetry (P-DSC), Calculated Cetane Index (CCI), and calorific power were used to verify the effect of the thermal-oxidative stability as a function of the percentage of biodiesel in the mixtures. The obtained results evidenced that the thermal and oxidative stability decreased with the addition of biodiesel from 50 to 5% v/v. Low stability fuels require rapid use as the oxidation compounds degrade the product and impair vehicle performance, as well as lead to corrosion and clogging problems in various mechanical systems.

Rapid fingerprinting technology of heavy oil spill by mid-infrared spectroscopy

With the increase of unconventional oil production and transportation, the detection methods of light crude oil have been challenged. Mid-Infrared spectroscopy can reflect the functional group of the oil related samples, which has strong absorption signals with distinguishable peaks featured as a fast, economy, and robust technique. Nevertheless, the previous study and application of oil relevant samples, such as petroleum chemical industry online monitoring, are mainly based on Near-infrared spectroscopy. Recently, the rapid development of the spectral instrument manufacturing and the data analysis methods provides a more comprehensive technical support for the rapid and accurate identification of marine oil spill by Mid-infrared spectroscopy. In this paper, 10 crude oil samples were selected for infrared spectroscopy detection, and the results were analysed and compared with those of gas chromatography flame ionization detection method. The character information of the IR spectra and GC/FID chromatograms were extracted and classified both by principal component analysis and partial least squares regression. Under the condition of small sample size, the recognition accuracy was up to 100%. The results show that the mid-infrared method combined with chemometrics can be expected to achieve rapid, accurate and economical identification of heavy oil species.

Determination of halogens and sulfur in honey: a green analytical method using a single analysis

The halogen determination is important in view of their biological and environmental roles, but their determination has still been considered a challenge, especially at low concentrations. Therefore, a method for honey decomposition using microwave-induced combustion (MIC) combined with ion chromatography and conductimetric detection (for Cl, F, and S determination) or mass detection (for Br and I determination) (IC-CD-MS) is proposed. Trueness was evaluated by adding reference materials (RMs) or a standard solution in the sample. By using 50 mmol L^-1 NH₄OH as the absorbing solution, recoveries for all analytes were between 94 and 103%, in both tests. Moreover, no statistical difference (t test, confidence level of 95%) was observed for the results obtained by IC in comparison with those obtained by inductively coupled plasma optical emission spectroscopy (Cl and S) and by inductively coupled plasma mass spectrometry (Br and I). Finally, the proposed method was applied to 19 honey samples from different origins. The concentrations ranged from < 0.45 to 2.39 mg kg^-1 (Br), 21.8 to 671 mg kg^-1 (Cl), and 11 to 154 mg kg^-1 (S), while the F and I concentrations were below that their quantification limits (LOQs) in all analyzed samples. The LOQs for Br, Cl, F, I, and S were 0.45, 21, 3.7, 0.077, and 8.7 mg kg^-1, respectively. The MIC method provided a compatible solution to IC for the halogen and S determination in honey by a single analysis. Graphical abstract.

Whole Cell Actinobacteria as Biocatalysts

Production of fuels, therapeutic drugs, chemicals, and biomaterials using sustainable biological processes have received renewed attention due to increasing environmental concerns. Despite having high industrial output, most of the current chemical processes are associated with environmentally undesirable by-products which escalate the cost of downstream processing. Compared to chemical processes, whole cell biocatalysts offer several advantages including high selectivity, catalytic efficiency, milder operational conditions and low impact on the environment, making this approach the current choice for synthesis and manufacturing of different industrial products. In this review, we present the application of whole cell actinobacteria for the synthesis of biologically active compounds, biofuel production and conversion of harmful compounds to less toxic by-products. Actinobacteria alone are responsible for the production of nearly half of the documented biologically active metabolites and many enzymes; with the involvement of various species of whole cell actinobacteria such as Rhodococcus, Streptomyces, Nocardia and Corynebacterium for the production of useful industrial commodities.

Improving the Catalytic Power of the DszD Enzyme for the Biodesulfurization of Crude Oil and Derivatives

The enhancement of the catalytic power of enzymes is a subject of enormous interest both for science and for industry. The latter, in particular, due to the vast applications enzymes can have in industrial processes, for instance in the desulfurization of crude oil, which is mandatory by law in many developed countries and is currently performed using costly chemical processes. In this work we sought to enhance the turnover rate of DszD from Rhodococcus erythropolis, a NADH-FMN oxidoreductase responsible for supplying FMNH₂ to DszA and DszC in the biodesulfurization process of crude oil, the 4S pathway. For this purpose, we replaced the wild type spectator residue of the rate limiting step of the reduction of FMN to FMNH₂ , a process catalysed by DszD and known to play an important role in the reaction energy profile. As replacements, we used all the naturally occurring amino acids, one at a time, using computational methodologies, and repeated the above-mentioned reaction with each mutant. To calculate the different free energy profiles, one for each mutated model, we applied quantum mechanics/molecular mechanics (QM/MM) methods within an ONIOM scheme. The free energy barriers obtained varied between 15.1 and 29.9 kcal mol^-1 . Multiple factors contributed to the different ΔG values. The most relevant were electrostatic interactions and the induction of a favourable alignment between substrate and cofactor. These results confirm the great potential that chirurgic mutations have for increasing the catalytic power of DszD in relation to the wild type (wt) enzyme.

On-line monitoring of extraction process of Flos Lonicerae Japonicae using near infrared spectroscopy combined with synergy interval PLS and genetic algorithm

There is a growing need for the effective on-line process monitoring during the manufacture of traditional Chinese medicine to ensure quality consistency. In this study, the potential of near infrared (NIR) spectroscopy technique to monitor the extraction process of Flos Lonicerae Japonicae was investigated. A new algorithm of synergy interval PLS with genetic algorithm (Si-GA-PLS) was proposed for modeling. Four different PLS models, namely Full-PLS, Si-PLS, GA-PLS, and Si-GA-PLS, were established, and their performances in predicting two quality parameters (viz. total acid and soluble solid contents) were compared. In conclusion, Si-GA-PLS model got the best results due to the combination of superiority of Si-PLS and GA. For Si-GA-PLS, the determination coefficient (R_p²) and root-mean-square error for the prediction set (RMSEP) were 0.9561 and 147.6544μg/ml for total acid, 0.9062 and 0.1078% for soluble solid contents, correspondingly. The overall results demonstrated that the NIR spectroscopy technique combined with Si-GA-PLS calibration is a reliable and non-destructive alternative method for on-line monitoring of the extraction process of TCM on the production scale.

Determination of propranolol hydrochloride in pharmaceutical preparations using near infrared spectrometry with fiber optic probe and multivariate calibration methods

A method for determination of propranolol hydrochloride in pharmaceutical preparation using near infrared spectrometry with fiber optic probe (FTNIR/PROBE) and combined with chemometric methods was developed. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). The treatments based on the mean centered data and multiplicative scatter correction (MSC) were selected for models construction. A root mean square error of prediction (RMSEP) of 8.2 mg g(-1) was achieved using siPLS (s2i20PLS) algorithm with spectra divided into 20 intervals and combination of 2 intervals (8501 to 8801 and 5201 to 5501 cm(-1)). Results obtained by the proposed method were compared with those using the pharmacopoeia reference method and significant difference was not observed. Therefore, proposed method allowed a fast, precise, and accurate determination of propranolol hydrochloride in pharmaceutical preparations. Furthermore, it is possible to carry out on-line analysis of this active principle in pharmaceutical formulations with use of fiber optic probe.