Fully automated spectrophotometric procedure for simultaneous determination of calcium and magnesium in biodiesel

Three-component deep eutectic solvent-based microextraction approach for biodiesel quality control: Determination of water and metals

Biodiesel is an important alternative fuel produced by blending biofuels with petroleum diesel. Biofuel production is usually carried out by catalytic interesterification of animal fats or vegetable oils, followed by the removal of by-products and catalysts through washing with water. Residual amounts of water and catalysts can accelerate fuel biodegradation and contribute to the corrosion of metal surfaces. Considering the need to control the quality of biodiesel fuel, a simple and environmentally friendly analytical approach was first developed for the determination of water and metals (sodium, potassium, magnesium, calcium as catalysts, and iron, copper, tin, zinc, lead as feedstock elements) using a deep eutectic solvent. The technique involved microextraction of analytes from biodiesel into a new three-component deep eutectic solvent (choline chloride, lactic acid, and cobalt chloride) using a laboratory vortex, followed by impregnating the filter paper with the obtained extract to determine the analytes. The colorimetric determination of water is based on a change in the color of the deep eutectic solvent, which goes from blue to pink due to the formation of cobalt aqua complexes. The detection of water on the filter paper was carried out using a conventional scanner. The content of metals on the filter paper was determined by X-ray fluorescence spectrometry. Under optimal conditions, the detection limit was 100 mg kg-1 for water and 0.03-3 mg kg-1 for metals. The technique enabled multicomponent analysis to be carried out without the use of dangerous Karl Fischer reagents (for water determination) and microwave mineralization of samples (for elemental analysis). The enrichment factor ranged from 290 to 330, and the RSD was less than 15%.

Spectroscopy approach to methanol detection in waste fat methyl esters

Second-generation biodiesel manufactured from waste cooking oils (WCO) and inedible animal fats (AF) are one of the alternatives to the first generation (1G) vegetable oil-based biodiesel. In this study, a quality control method is proposed to evaluate methanol content in waste fat methyl esters and is based on near infrared spectroscopy (NIR) combined with multivariate analysis. More specifically, calibration models are constructed using partial least squares regression (PLS) for the prediction of methanol content in rapeseed oil methyl ester (ROME), waste cooking oil methyl ester (WCOME), chicken fat methyl ester (CFME) and pork fat methyl ester (PFME) by Vis-NIR spectrometer. The calibration models are based on the absorbance spectra and computed data from five wavelength regions of 400-2170 nm, 780-2170 nm, 1400-2170 nm, 1400-1600 nm and 1970-2170 nm. For the cases with the highest prediction ability obtained in this study, the coefficient of determination of the model's goodness-of-fit for methanol concentrations range 0-5% (v/v) was R² > 0.990, and for concentrations 0-1% (v/v) was R² > 0.994, indicating the spectroscopic approach effectiveness in methanol content detection relevant to the biofuel quality assessment. A pseudo-univariate limits of detection (LOD_pu) and quantification (LOQ_pu) as well as ratio of performance to deviation (RPD) were used to confirm the validity and to evaluate the practical applicability of developed models. In addition, the obtained results indicate the possibility of developing a transmission sensor for online monitoring of the production process and the quality of biofuel.

Simultaneously detection of calcium and magnesium in various samples by calmagite and chemometrics data processing

The current study describes results of the application of radial basis function-partial least squares (RBF-PLS), partial robust M-regression (PRM), singular value decomposition (SVD), evolving factor analysis (EFA), multivariate curve resolution with alternating least squares (MCR-ALS) and rank annihilation factor analysis (RAFA) methods for the purposes of simultaneous determination of trace amounts calcium (Ca(2+)) and magnesium (Mg(2+)) and exploratory analysis based on their colored complexes formation with 1-(1-hydroxy-4-methyl-2-phenylazo)-2-naphthol-4-sulfonic acid (calmagite) as chromomeric reagent. The complex formation Ca(2+) and Mg(2+) with calmagite was investigated under pH10.20. The performance of RBF-PLS model in detection of minerals was compared with PRM as a linear model. The pure concentration and spectral profiles were obtained using MCR-ALS. EFA and SVD were used to distinguish the number species. The stability constants of the complexes were derived using RAFA. Finally, RBF-PLS was utilized for simultaneous determination of minerals in pharmaceutical formulation and various vegetable samples.

Recent advances in flow injection analysis

A dynamic development of methodologies of analytical flow injection measurements during four decades since their invention has reinforced the solid position of flow analysis in the arsenal of techniques and instrumentation of contemporary chemical analysis.