Title: New insights for the valorisation of glycerol over MgO catalysts in the gas-phase - dataset

Citation
Smith LR, Smith PJ, Mugford KS, et al. (2018). New insights for the valorisation of glycerol over MgO catalysts in the gas-phase - dataset. Cardiff University. https://doi.org/10.17035/d.2018.0049493818

Dataset Details

Publisher: Cardiff University

Date (year) of data becoming publicly available: 2018

Data format: .txt, .run, .xls, .ASC

Software Required: Varian Star Gas Chromoatography Software, X'Pert HighScore,

Estimated total storage size of dataset: Less than 100 megabytes

Number of Files In Dataset: 18

DOI : 10.17035/d.2018.0049493818

DOI URL: http://doi.org/10.17035/d.2018.0049493818

Description

Glycerol, a waste product from bio-diesel production can be transformed over catalysts to methanol and other products without the need for gaseous hydrogen. Representative datasets compliment the published data contained in the table and figures. These include the chromatograms which show the components of the reaction mixture, thermal gravimetric analysis of used catalysts to show the release of carbon build up and X-ray diffraction patterns of the catalysts to show their structural identity. The chromatograms are generated from the reaction mixture which elutes from a modified silica capillary into a flame ionisation detector (for liquid samples) or a thermal conductivity detector (permanent gases). A voltage change is associated to the elution of a product and the peak area is then integrated against calibration curves for the product. The thermal gravimetric analysis data illustrates the fate of the sample as it is heated as a function of its mass. Here adsorbates can be removed at elevated temperatures and recorded as a mass loss which can be associated to the performance of the catalyst. The powder X-ray diffraction patterns are an indication of the crystallinity and structure of a metal oxide sample as in this case. The peak positions are related to the lattice and structural information can be generated to identify any permanent changes that take place during a reaction for example.

Research results based upon these data are published at http://doi.org/10.1039/c8cy02214c