Component data of oil sample treated by microwave and/or nano catalyst

Published: 20-11-2020| Version 1 | DOI: 10.17632/8sydnkkgtb.1
Contributor:
Li Hanyong

Description

Firstly, 10% to 50% water content was selected for the experimental study. Secondly, the metal nano catalyst was prepared by a certain method. Then, the viscosity reduction treatment was carried out under the optimal processing conditions of microwave-only treatment, nano-catalyst-only treatment, and treatment using nano-catalysts assisted with microwave treatment. After the processing, we used solubility to separate the group components to obtain SARA (saturates, aromatics, resins and asphaltenes), used a Fourier infrared spectrometer to perform infrared analysis, used an element analyzer to determine the C, H, O, N, and S content, and used a gas chromatography mass spectrometry to detect changes in the composition of the oil sample to finally explore the mechanism of viscosity reduction.

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SARA data: First, we used n-heptane, toluene, and n-butanol to separate the asphaltene and hard resin with a Soxhlet extractor. Then, the remaining sample was separated in an alumina adsorption column, washed with petroleum ether, benzene, and petroleum ether (1:1), and benzene and ethanol (1:1). This was followed by vacuum drying and weighing, after which the quality was recorded. Infrared spectrum:We took blank oil samples and treated heavy-oil emulsions, and used a Fourier infrared spectrometer to perform infrared analysis on the blank, nano-catalyst-treated, microwave-treated, and nano-catalyst assisted with microwave treated oil samples. The resolution is 0.2 cm, the scanning frequency is 20 times/second, and the scanning range is 400 cm-1 ~ 4000 cm-1. Element analysis: We used an electronic balance to weigh the mass to an accuracy of 0.001. We used an element analyzer to determine the C, H, O, N, and S content. The elements’ content was monitored using sensors connected to the computer to observe the changes. Three sets of data were measured for each experiment, and the average value was used as the result. gas chromatography mass spectrometry data: The gas chromatograph cannot effectively detect substances that have a boiling point higher than 320 °C. Hence, to reduce any pollution of the instrument, we selected the oil sample from section 2.3.3 that has had the asphaltene and hard resin removed, for analysis. We imported the obtained experimental data into the Canvas software, and set the start time to 13 min and the end time to 45 min. We then performed peak detection and set the signal-to-noise ratio to 2. After removing the column bleed, solvent peaks, and some impurities, we searched the NIST library and determined the substance structure and chemical formula for qualitative analysis and used the FID detection results for quantitative analysis.