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- W4384789916 abstract "In extractive distillation (ED), a suitable solvent is added to increase the relative volatility of azeotropic or close-boiling mixtures, thereby facilitating the separation. The viability and efficiency of this separation are largely dependent on the selection of solvent. In this work, solvents are optimally designed to improve the performance of ED processes by a molecular property targeting method. Specifically, optimal solvents are identified by directly targeting desirable molecular properties obtained from process optimization. First, data-driven process models are established to estimate key performance indicators of the ED process with the most important process-relevant physical properties of the solvents. Based on the established models, multi-objective optimization is then performed to maximize the product purity while minimizing energy cost, through which optimal molecular properties are obtained. Hypothetical target molecules featuring the desirable properties are thereby generated. Subsequently, several real solvents that approximate the optimal property profiles of the hypothetical molecules are selected from a large solvent database. In a final assessment step, the performance of these real solvent candidates is evaluated via detailed process simulations. The proposed molecular-property-targeting solvent design methodology is demonstrated by the separation of 1-butene and 1,3-butadiene. For this separation task, three real solvents are finally identified, allowing for a higher product purity and lower energy consumption compared to the benchmark solvent n-methyl-2-pyrrolidone (NMP)." @default.
- W4384789916 created "2023-07-20" @default.
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- W4384789916 date "2023-01-01" @default.
- W4384789916 modified "2023-10-01" @default.
- W4384789916 title "Molecular Property Targeting for Optimal Solvent Design in Extractive Distillation Processes" @default.
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- W4384789916 doi "https://doi.org/10.1016/b978-0-443-15274-0.50199-2" @default.
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