Our work is focused on the structure-based calculation of thermophysical properties and predictive thermodynamics for thermal separation processes. Thermophysical properties are predicted by data-driven models such as group contribution, QSPR and Machine Learning. And the predictive thermodynamics are based on the openCOSMO-RS model.
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