| Title |
Multi-objective Bayesian optimisation of a two-step synthesis of p-cymene from crude sulphate turpentine |
| ID_Doc |
6254 |
| Authors |
Jorayev, P; Russo, D; Tibbetts, JD; Schweidtmann, AM; Deutsch, P; Bull, SD; Lapkin, AA |
| Title |
Multi-objective Bayesian optimisation of a two-step synthesis of p-cymene from crude sulphate turpentine |
| Year |
2022 |
| Published |
|
| Abstract |
Production of functional molecules from renewable bio-feedstocks and bio-waste has the potential to significantly reduce the greenhouse gas emissions. However, the development of such processes commonly requires invention and scale-up of highly selective and robust chemistry for complex reaction networks in bio-waste mixtures. We demonstrate an approach to optimising a chemical route for multiple objectives starting from a mixture derived from bio-waste. We optimise the recently developed route from a mixture of waste terpenes to p-cymene. In the first reaction step it was not feasible to build a detailed kinetic model. A Bayesian multiple objectives optimisation algorithm TS-EMO was used to optimise the first two steps of reaction for maximum conversion and selectivity. The model suggests a set of very different conditions that result in simultaneous high values of the two outputs. (c) 2021 Elsevier Ltd. All rights reserved. |
| PDF |
https://repository.tudelft.nl/islandora/object/uuid%3Aa3342439-9f09-4801-ba73-8abd9f017479/datastream/OBJ/download
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