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Prediction of Temperature-Dependent Henry's Law Constants by Matrix Completion.

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Laboratory of Engineering Thermodynamics, RPTU Kaiserslautern, Erwin-Schrödinger-Str. 44, Kaiserslautern 67663, Germany.

Methods for predicting Henry's law constants describing the solubility of solutes in solvents as a function of temperature are essential in chemical engineering. While isothermal properties of binary mixtures can conveniently be predicted with matrix completion methods (MCMs) from machine learning, we advance their application to the temperature-dependent prediction of in the present work by combining them with physical equations describing the temperature dependence. For training the methods, experimental data for 122 solutes and 399 solvents ranging from 173.

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