Novel method for chlorine determination in biofuel lipid feedstock by coupling a total sample introduction system (hTISIS) to an inductively coupled plasma tandem mass spectrometry (ICP-MS/MS).

BACKGROUND: Chlorine concentrations above 1 mg kg-1 in lipid feedstocks for biofuel production can generate corrosion issues in the different refining units as well as catalyst deactivation by clogging or fouling. To reach accurate analyses by inductively coupled plasma (ICP) techniques at low concentration levels, dilution in organic solvents rises as a simpler and more straightforward sample preparation methodology than conventional sample decomposition procedures (e.g., microwave-assisted acid digestion). However, matrix effects and the impact of the Cl chemical form on the signal must be overcome to obtain accurate results. RESULTS: In this work, the high temperature torch integrated sample introduction system (hTISIS) operated at 350 °C is coupled to an inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) for the determination of Cl in lipid biofuel feedstock samples diluted in xylene and these results are compared with those reported by a conventional sample introduction system. Under optimal conditions of the hTISIS-ICP-MS/MS configuration, matrix effects are efficiently overcome (recovery values ranged from 101 to 104%) as well as the effect of the Cl chemical form on the signal for 6 organochloride compounds. Thus, an external calibration approach can be set to carry out the quantification of this element in real samples. The method is successfully validated, obtaining a good agreement in the Cl concentration reported in a standard reference material (SRM NIST 1634c) and also by comparing the concentration results obtained by external calibration and standard addition approaches in two biofuel feedstock samples. SIGNIFICANCE AND NOVELTY: The hTISIS coupled to an ICP-MS/MS system is used for the first time to overcome not only matrix effects but also the impact of the Cl chemical form in biofuel feedstock samples. This novel method, with a limit of quantification (LOQ) of 7.1 µg kg-1, give access to an accurate Cl determination in all kind of lipid feedstocks for clean fuel production.

Development of heart-cutting multidimensional gas chromatography coupled to time of flight mass spectrometry for silicon speciation at trace levels in gasoline samples.

To improve the understanding of hydrotreatment (HDT) catalyst poisoning by silicon species, these molecules must be characterized in petroleum products using powerful analytical systems. Heart-cutting gas chromatography coupled to time of flight mass spectrometry (GC-GC/TOFMS) method equipped with a Deans switch (DS) system was developed for the direct characterization of target silicon compounds at trace level (µg kg(-1)) in gasoline samples. This method was performed to identify silicon compounds never characterized before. After the selection of the second dimension column using GC-GC-FID, GC-GC/TOFMS was performed. The calibration curves obtained by the GC-GC/TOFMS method were linear up to 1,000 µg kg(-1). Limits of detection (LOD) were ranging from 5 to 33 µg kg(-1) in spiked gasoline. The method provided sufficient selectivity and sensitivity to characterize known silicon compounds thanks to their specific ions and their retention times. The analysis of a naphtha sample by GC-GC/TOFMS has shown the presence of cyclic siloxanes (D(n)) as major compounds of PDMS thermal degradation with the occurrence of linear siloxanes, especially hexamethyldisiloxane (L(2)), which was never characterized in petroleum products but already known as severe poison for catalyst.

Combining Fourier transform-ion cyclotron resonance/mass spectrometry analysis and Kendrick plots for silicon speciation and molecular characterization in petroleum products at trace levels.

A new method combining FT-ICR/MS analysis and Kendrick plots for the characterization of silicon species at trace levels in light petroleum products is presented. The method provides efficient instrumental detection limits ranging from 80 ng/kg to 5 µg/kg and reliable mass accuracy lower than 0.50 ppm for model silicon molecules in spiked gasoline. More than 3000 peaks could be detected in the m/z 50-500 range depending on the nature of the gasoline sample analyzed. An in-house software program was used to calculate Kendrick plots. Then, an algorithm searched, selected, and represented silicon species classes (O(2)Si, O(3)Si, and O(4)Si classes) in Kendrick plots by incorporating model molecules' information (i.e., exact mass and intensity). This procedure allowed the complete characterization of more than 50 new silicon species with different degrees of unsaturation in petroleum products.

Silicon speciation by gas chromatography coupled to mass spectrometry in gasolines.

A method for the speciation of silicon compounds in petroleum products was developed using gas chromatography coupled to mass spectrometry (GC-MS). Prior to analysis, several precautions about storage and conservation were applied for all samples. In spiked gasoline samples, limits of detection between 24 and 69 µg kg(-1) for cyclic siloxanes (D(4)-D(6)) and between 1 and 7 µg kg(-1) for other species were obtained. In this study, cyclic siloxanes (D(n)) and one ethoxysilane were quantified for the first time in petroleum products by a specific method based on response factor calculation to an internal standard. This method was applied to four samples of naphthas and gasolines obtained from a steam cracking process. Cyclic siloxanes were predominant in four investigated samples with concentrations ranging between 101 and 2204 µg kg(-1). Cyclic siloxane content decreased with an increase in their degree of polymerization. During a steam cracking process, silicon concentrations determined by GC-MS SIM (single ion monitoring) significantly increase. This trend was confirmed by ICP-OES (inductively coupled plasma optical emission spectroscopy) measurements but a difference on the total silicon content was observed, certainly highlighting the presence of unknown silicon species. GC-MS SIM method gives access to the chemical nature of the silicon species, which is crucial for the understanding of hydrotreatment catalyst poisoning in the oil and gas industry.