Systematic methods for solvent design : towards better reactive processes

The focus of this thesis is the development of novel methodologies for systematic identification of optimal solvents for chemical reactions. Two aspects are considered: the integrated solvent and process design using a mixed solvent, and the design of an optimal solvent using ab initio methods that do not rely on experimental data. A methodology is developed for the integrated design of a CO2-expanded solvent in a reaction process. Posing as objective function the cost of the process, for a defined production rate, an optimisation problem is formulated, with decision variables that include the organic co-solvent, the composition and the mass of the mixed solvent. Emphasis is placed on the prediction of the reaction rate, for which the solvatochromic equation combined with a preferential solvation model are used, and on solid-vapour-liquid phase equilibrium, for which the group-contribution volume translated Peng-Robinson equation of state is used. The proposed methodology is applied to the Diels-Alder reaction of anthracene and 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD), and three CO2-expanded solvents are considered (acetone, acetonitrile and methanol). Acetonitrile and acetone are found to offer good performance over a range of CO2 concentrations. The importance of taking into account multiple process performance indicators, when designing gas-expanded liquids, is highlighted. As a further step toward systematic solvent design approaches that are not limited by the availability of experimental data and consider a large number of candidate solvents, an ab initio methodology is developed for the design of optimal solvents for reactions. The developed method combines quantum mechanical calculations with a computer-aided molecular design formulation. In order to limit the number of QM calculations but also retain accuracy and ensure convergence, the Kriging approach is used. Kriging is a response surface approach, which has recently attracted a lot of attention because it is an exact extrapolator with a statistical interpretation which makes it stand out from other methods. The proposed approach is used successfully to identify promising solvents for the Menschutkin reaction of phenacyl bromide and pyridine and the Cope elimination of methylamine oxide. The use of Kriging as the surrogate model is found to lead to improved solvents when compared to the simpler solvatochromic equation used in previous work.Open Acces

On the optimal design of gas-expanded liquids based on process performance

AbstractGas-expanded liquids (GXLs) are mixed solvents composed of an organic solvent and a compressible gas, usually carbon dioxide (CO2) due to its environmental and economic advantages. The best choice of GXL, as defined by the specific organic solvent and the CO2 composition, depends strongly on the process in which the solvent is to be used. Given the large range of possible choices, there is a need to predict the impact of GXL design on process performance from economic and environmental perspectives. In this work, we present a design methodology in which limited experimental data are used to build a predictive model which allows a wider design space to be assessed. The proposed methodology for the integrated design of CO2-expanded solvent and process is applied to the Diels–Alder reaction of anthracene and 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD). Three organic co-solvents are studied: acetonitrile, methanol and acetone. Given that the process cost is sensitive to the operating pressure and reactor volume, a trade-off between reaction rate constant and solubility is required in order to design an optimal process from a cost perspective. From a total cost perspective and in terms of energy consumption, it is found that designs with small amounts of CO2 or, in the case of acetone, without any CO2, offer the best performance. However, CO2 use is found to lead to a significant reduction in organic solvent inventory, up to 70 % in some cases. In this work the importance of taking multiple performance criteria, including process metrics, into account when designing GXLs is demonstrated