Crotonaldehyde is an important intermediate in the chemical industry and usually produced from acetaldehyde in aqueous solution. Recently, new results on the reactions which yield crotonaldehyde from acetaldehyde have become available. It was shown that the formation of aldoxane from acetaldehyde and acetaldol, as well as the oligomer formation in the system acetaldehyde and water have to be taken into account. In the present paper, the established process for the production of crotonaldehyde is analyzed based on that new information. A model for the physico-chemical properties of the relevant mixtures is developed as well as an equilibrium stage based process model. The models are implemented in a steady state process simulation tool which is used for numerical studies of the process. The results provide unexpected insights in the process which contains distillations in which complex reactions occur. A conceptual process design is carried out applying a structured approach. The performance of the process is analyzed and potential for its optimization is discussed.

Acetaldehyde is an important intermediate in the chemical industry and often used in mixtures with water. These mixtures are reactive multicomponent systems, as acetaldehyde forms oligomers with water. Quantitative studies of the resulting speciation are scarce in the literature and limited to the formation of the smallest oligomer, ethane‐1,1‐diol. Therefore, in the present work, a comprehensive study of chemical equilibria in mixtures of acetaldehyde and water was carried out by quantitative 1H‐ and 13C‐NMR spectroscopy. The study covers temperatures between 275 and 338 K and overall acetaldehyde mole fractions between about 0.05 and 0.95 mol/mol. The peak assignment is given for both the 1H‐ and 13C‐NMR spectra. From the speciation data, obtained from the peak area fractions, numbers for the chemical equilibrium constants of the oligomer formation are obtained and a correlation is presented. © 2014 American Institute of Chemical Engineers AIChE J, 61: 177–187, 2015

Mixtures of acetaldehyde and water are reactive multicomponent systems because poly(oxymethylmethylene) glycols are formed. A study on the kinetics of the formation of these oligomers was carried out using a new microreactor NMR probe head that combines online flow H-1 NMR spectroscopy with microreaction technology. The study covers temperatures between 278 and 298 K and pH values between 3.5 and 10.3. From the peak areas in the H-1 NMR spectra, quantitative results for the conversion of acetaldehyde were obtained. On the basis of the new data, a reaction kinetic model was developed and numbers for the kinetic constants of poly(oxymethylmethylene) glycol formation were determined together with a correlation that describes their dependence on the temperature and pH value.

Designing chemical processes is a multi-criteria optimization problem with conflicting objectives. It can efficiently be solved using Pareto sets. These sets contain all solutions for which an improvement in any objective can only be achieved by accepting a decline in at least one other objective. This work integrates a novel algorithm to determine Pareto sets in a state-of-the-art steady-state flow sheet simulator. An approximation of predefined accuracy of the Pareto set, which can be convex or non-convex, is calculated. The decision maker can then navigate interactively on the Pareto set and explore the different optimal solutions. His decision is, hence, embedded in the knowledge of the entire Pareto set. The application of the method is illustrated by an example in which a distillation process for the separation of an azeotropic mixture (acetone + chloroform) is designed. Two process variants are compared: a pressure-swing and an entrainer distillation.

Crotonaldehyde is an interesting intermediate in the chemical industry. It is usually produced from aqueous acetaldehyde in a two step process in which the first step is carried out under basic and the second step under acidic conditions. It is commonly assumed that acetaldehyde is converted in the first step to acetaldol and that acetaldol is subsequently dehydrated in the second step to crotonaldehyde. We demonstrate by 1H and 13C NMR spectroscopic studies that acetaldol is hardly present in the reacting solutions at lower temperatures and that the key intermediate is aldoxane (2,6-dimethyl-1,3-dioxane-4-ol). For the first time, data on the chemical equilibrium of the aldoxane formation in aqueous acetaldehyde solutions is provided. Furthermore, preliminary information on the kinetics of that reaction is presented.

Process development in chemical industry is a multiobjective optimization problem. Objectives of this optimization are for example product quality, raw material and investment cost, energy efficiency, reliability or health, safety, and environmental issues. Parameters for this optimization are, e.g., feed stock, utilities, process configuration, equipment, operating parameters, and site.In process design, the developer usually generates a certain number of process variants by varying process parameters intuitively. The process is usually stopped if a solution is found that is acceptable regarding all or at least most criteria, optimality cannot be guaranteed. The present paper describes a feasible alternative approach, which is a real multiobjective optimization based on the Pareto optimality concept. The Pareto front describes a set of solutions where no improvement in one objective can be reached without at least getting worse in another objective. The Pareto front allows investigating the trade-offs between different objectives, but the final choice of the design is left to the user. In the present work the multiobjective optimization is used together with a decision support system, which allows navigating within the Pareto front and thereby finding the best compromise between the objectives in a rational and efficient way.

Process development in chemical industry is a multiobjective optimization problem. Objectives of this optimization are for example product quality, raw material and investment cost, energy efficiency, reliability or health, safety, and environmental issues. Parameters for this optimization are, e. g., feed stock, utilities, process configuration, equipment, operating parameters, and site.In process design, the developer usually generates a certain number of process variants by varying process parameters intuitively. The process is usually stopped if a solution is found that is acceptable regarding all or at least most criteria, optimality cannot be guaranteed. The present paper describes a feasible alternative approach, which is a real multiobjective optimization based on the Pareto optimality concept. The Pareto front describes a set of solutions where no improvement in one objective can be reached without at least getting worse in another objective. The Pareto front allows investigating the trade-offs between different objectives, but the final choice of the design is left to the user. In the present work the multiobjective optimization is used together with a decision support system, which allows navigating within the Pareto front and thereby finding the best compromise between the objectives in a rational and efficient way.