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Optimal design of solvents for extractive reaction processes
Author(s) -
Zhou Teng,
Wang Jiayuan,
McBride Kevin,
Sundmacher Kai
Publication year - 2016
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.15360
Subject(s) - solvent , chemical reaction engineering , optimal design , chemistry , work (physics) , molecule , reaction conditions , chemical equilibrium , liquid phase , phase (matter) , genetic algorithm , reliability (semiconductor) , process engineering , organic chemistry , computer science , thermodynamics , engineering , catalysis , mechanical engineering , power (physics) , physics , machine learning
It is well known that solvents can have significant effects on rates and equilibrium compositions of chemical reactions. The computer‐aided molecular design (CAMD) of solvents for heterogeneous liquid phase reactions is challenging due to multiple solvent effects on reaction and phase equilibria. In this work, we propose a CAMD methodology based on a genetic algorithm (GA) for identifying optimal solvents for liquid phase reactions where the objective is to maximize the reaction equilibrium conversion. In particular, a novel molecular encoding method is introduced to facilitate the construction and evaluation of solvent molecules in a defined structure space. The reliability of the method for fast identification of optimal reaction solvents is demonstrated for a selected biphasic esterification reaction. The proposed approach opens up new perspectives for intensifying extractive reaction processes via the purposeful design of solvent molecules. © 2016 American Institute of Chemical Engineers AIChE J , 62: 3238–3249, 2016