Xuanbo Gao

A simple model for separation prediction of comprehensive two-dimensional gas chromatography and its applications in petroleum analysis

A model has been developed to predict and optimize Comprehensive two-dimensional gas chromatography (GC × GC) separation by simulating GC × GC chromatograms and quantitatively evaluating the separation orthogonality. A custom standard mixture and a light crude oil were used to validate the prediction by the model. It showed that the practical separation was in good agreement with the prediction. With this method, the separation optimization of individual peaks becomes more easy and efficient. Using the optimized separation conditions from the model, some crude oil samples were characterized in detail by GC × GC coupled to time-of-flight mass spectrometry (TOFMS). It showed that the components in the crude oil were separated well under nearly orthogonal conditions and almost spread throughout the whole region of the 2D-plane. Compared with non-orthogonal GC × GC and 1DGC, many new compounds were separated and identified from the co-eluting peaks, some of which are potential biomarkers of petroleum and probably indicate important geochemical information for petroleum exploration. Based on the GC × GC orthogonal separation, some classic geochemical parameters were calculated according to the peak area ratios of individual biomarkers, and compared with results from traditional GC/MS. Basically, more accurate parameters were obtained in orthogonal GC × GC, but good separation of biomarkers in GC/MS could result in close agreement of both methods. Furthermore, owing to the excellent separation of GC × GC in orthogonal conditions, some time-consuming steps of sample preparation proposed in ASTM test methods were simplified greatly by using a homemade device, which can decrease the loss of some components or avoid changing the ratio of compounds during sample preparation.

Determination of diamondoids in crude oils using gas purge microsyringe extraction with comprehensive two dimensional gas chromatography-time-of-flight mass spectrometry.

Based on a homemade device, gas purge microsyringe extraction (GP-MSE) of crude oil samples was developed for the first time. As a simple, fast, low-cost, sensitive and solvent-saving technique, GP-MSE provides some outstanding advantages over the widely used sample preparation methods for crude oils such as column chromatography (ASTM D2549). Several parameters affecting extraction efficiency were optimized, including extraction temperature, extraction time, extraction solvent, condensing temperature and purge gas flow rate. With the optimized GP-MSE conditions, several real crude oil samples were extracted, and trace diamondoids were determined using comprehensive two dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS). In total, more than 100 diamondoids were detected and 27 marker compounds were identified and quantified accurately. The limits of detection (LODs, S/N=3) were less than 0.08μg/L for all diamondoids. The relative standard deviation (RSD) was below 8%, ranging from 1.1 to 7.6%. The linearity of the developed method was in the range of 0.5-100.0μg/L with correlation coefficients (R2) more than 0.996. The recoveries obtained at spiking 50μg/L were between 81 and 108% for diamondoids in crude oil samples. The developed method can also be extended to the analysis of other components in crude oils and other complex matrices.

Preparation of Multiwalled Carbon Nanotubes/Hydroxyl-Terminated Silicone Oil Fiber and Its Application to Analysis of Crude Oils

A simple and efficient method to analyze the volatile and semivolatile organic compounds in crude oils has been developed based on direct immersion solid-phase microextraction coupled to comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (DI-SPME-GC × GC/TOFMS). A novel fiber, multiwalled carbon nanotubes/hydroxyl-terminated silicone oil (MWNTs-TSO-OH), was prepared by sol-gel technology. Using standard solutions, the extraction conditions were optimized such as extraction mode, extraction temperature, extraction time, and salts effect. With the optimized conditions, a real crude oil sample was extracted and then analyzed in detail. It shows that the proposed method is very effective in simultaneously analyzing the normal and branched alkanes, cycloalkanes, aromatic hydrocarbons, and biomarkers of crude oil such as steranes and terpanes. Furthermore, the method showed good linearity (r > 0.999), precision (RSD < 8%), and detection limits ranging from 0.2 to 1.6 ng/L.