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- W2899302011 abstract "Abstract This article contains data on vapor–liquid equilibrium modeling of 1533 gas-liquid solubilities divided over sixty binary systems viz. carbon monoxide, carbon dioxide, hydrogen, water, ethane, propane, pentane, hexane, methanol, ethanol, 1-propanol, 1-butanol, 1-pentanol, and 1-hexanol in the solvents phenanthrene, 1-hexadecanol, octacosane, hexadecane and tetraethylene glycol at pressures up to 5.5 MPa and temperatures from 293 to 553 K using literature data. The solvents are considered to be potentially significant in the conversion of synthesis gas through gas-slurry processes. Artificial neural networks limited to one hidden layer and up to five neurons in the hidden layer were used to predict the binary plots." @default.
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- W2899302011 date "2018-12-01" @default.
- W2899302011 modified "2023-09-25" @default.
- W2899302011 title "Supporting plots and tables on vapour–liquid equilibrium prediction for synthesis gas conversion using artificial neural networks" @default.
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- W2899302011 doi "https://doi.org/10.1016/j.dib.2018.10.129" @default.
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