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The vapor-liquid equilibrium (VLE) of methane + water mixtures has been studied with nuclear magnetic resonance (NMR) spectroscopy. This work had two primary goals. The first goal was to develop methods that broaden the utility of NMR spectroscopy for VLE measurements. In this regard, we report a method by which the liquid-phase and vapor-phase compositions are measured in separate experiments by adjusting the height of the liquid phase in the sample tube. We also report a method for hastening phase equilibration by adding glass beads to the sample and repeatedly inverting the sample tube. The second goal of this work was to collect VLE data on a challenging mixture with real-world importance. Mixtures of methane + water are a useful test case because of their challenging characteristics, including the widely differing vapor pressures of the two components. One use for accurate VLE data on methane + water mixtures is to better predict the formation of harmful liquid phases in natural gas pipelines. Herein we utilize 1H NMR spectroscopy to measure the VLE of methane + water mixtures at temperatures of 299.73, 307.98, and 323.25 K, and pressures ranging from 0.69 MPa to 13.89 MPa. Experiments were carried out with a 600 MHz spectrometer. Mixtures were prepared and equilibrated in a high pressure zirconia sample tube with an integrated needle valve. NMR-based VLE measurements on the liquid phase are in good agreement with available literature data and with Henry’s Law predictions at low pressures. However, the commonly used GERG-2008 model for natural gas systems deviates dramatically from the experimental data for the liquid phase. NMR-based VLE measurements on the vapor-phase resulted in measured water concentrations that are systematically lower than available literature data and models. This systematic offset is likely caused by peak overlap in the NMR spectra.
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Understanding Particle-fluid interaction dynamics in turbulent flow
Almost every aspect of the global water cycle involves a mixture of fluids and particles – raindrop formation, ocean currents and water percolation through the soil. This mixture of gas and liquid or liquid and solid causes behaviour that is important to understand, but difficult to predict. This is particularly true when turbulent flow occurs. Dr Lian-Ping Wang at the University of Delaware has developed models and methods that have greatly improved our ability to understand and predict phenomena from localised rainfall patterns to particle transport in industrial processes.
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- Award ID(s):
- 1706130
- PAR ID:
- 10064620
- Date Published:
- Journal Name:
- Scientia
- Volume:
- 113
- Issue:
- 115
- ISSN:
- 1899-0630
- Page Range / eLocation ID:
- 50 to 54
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.26320/SCIENTIA43
