Journal
CHEMICAL ENGINEERING SCIENCE
Volume 137, Issue -, Pages 613-625Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ces.2015.07.010
Keywords
Computer-aided molecular design (CAMD); Reaction solvent design; Design under uncertainty; Quantitative structure-property relationship (QSPR); Conductor-like screening model (COSMO)
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Funding
- Deutsche Forschungsgemeinschaft (DFG)
- International Max Planck Research School (IMPRS) for Advanced Methods in Process and System Engineering (Magdeburg)
- Max Planck Society in Germany for the Max Planck Partner Group at the East China University of Science and Technology in Shanghai
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Solvents can have significant effects on chemical reactions, however, their huge number makes the selection very difficult and costly. This work presents a systematic method for the design of reaction solvents. Kinetic models are built by correlating experimentally determined reaction rate constants in a small set of known solvents with corresponding solvent theoretical descriptors determined from quantum chemical calculations. Optimal solvents are then identified from the solution of an optimization-based molecular design problem. Besides the deterministic optimization, a robust solvent design framework is proposed to identify solvents that possess the best reaction performance under model uncertainties. The methodology is exemplified for a competitive Diels-Alder reaction with the objective of maximizing the production of the desired product relative to that of the byproduct. Compared to the best experimentally identified solvent, a 10.9% improvement in reaction performance can be achieved with our designed solvent. It is proven that the proposed method is an efficient tool for fast identification of high-performance solvents for chemical reactions. Moreover, it potentially promotes the development of new solvents. (C) 2015 Elsevier Ltd. All rights reserved.
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