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Continuous heterogeneous synthesis of hexafluoroacetone and its machine learning-assisted optimization.
- Source :
- Journal of Flow Chemistry; Sep2023, Vol. 13 Issue 3, p337-346, 10p
- Publication Year :
- 2023
-
Abstract
- Conventional batch synthesis of hexafluoroacetone (HFA), an important pharmaceutical intermediate, suffers from complex catalyst preparation, harsh reaction conditions (up to 200 °C), and low selectivity. In this study, we developed a continuous flow system that employs a micro packed-bed reactor (MPBR) filled with Lewis acid catalysts. After an initial screening of reaction conditions and catalysts in the batch reactor, a Bayesian Optimization model and the multi-objective optimization algorithm qNEHVI were used to find a compromise between conversion and energy efficiency for the reaction in the continuous flow system. After 14 rounds of experiments, BO found the best results with conversion of 98.6%, selectivity of 99.9%, and an energy cost of 0.121 kWh per kg of product at 25.1 °C, atmospheric pressure, and a GHSV of 931.5 h<superscript>− 1</superscript> reaction conditions. The study demonstrates that BO can be used as an efficient tool for multi-objective optimization of heterogeneous catalysis in continuous flow. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 2062249X
- Volume :
- 13
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Journal of Flow Chemistry
- Publication Type :
- Academic Journal
- Accession number :
- 169910925
- Full Text :
- https://doi.org/10.1007/s41981-023-00273-1