Screening for New Efficient and Sustainable-by-Design Solvents to Assist the Extractive Fermentation of Glucose to Bioethanol Fuels

The production of bioethanol fuels using extractive fermentation increases the efficiency of the bioconversion reaction by reducing the toxic product inhibition. The choice of appropriate solvents to remove the bioethanol product without inhibiting the fermentation is important to enable industrial scale application. This work applies computer-aided molecular design technologies to systematically screen a wide variety of candidate solvents to enhance the separation, also considering the microorganisms that perform the fermentation. The performance of the candidates was evaluated using a rigorous process simulator for extractive fermentation, assisted by functional group-contribution (QSPR/QSAR) models for the prediction of various solvent properties, including toxicity and life cycle impacts. The solvent designs generated through this approach can provide powerful insights on the kind of molecular structures and functionalities that satisfy the process objectives and constraints, as well the desired sustainability features.

A New Robust Approach for Reactor Network Synthesis by Combination of Mathematical Method and NSGAII

In this research, a simple procedure for synthesis of reactor network (RN) is presented. This method could find the best possible optimum solutions with high grantees for the synthesis of RN, which generally is kind of mixed integer nonlinear programming (MINLP) models. In this work, instead of solving the discrete and continuous variables simultaneously, (like MINLP problems), a combination of stochastic algorithm and mathematical methods (i. e. Non-dominated Sorting Genetic Algorithm II (NSGA II) + quasi LP (QLP)) has been used. The reason for using NSGA II is because of the possibility of considering several objective functions instead of a single function in obtaining RN synthesis solutions. This algorithm could provide several optimal structure of RNs as set of final optimal solutions by use of its operators. The isothermal RNs produced by NSGA II are sent to QLP model to compute the amount of objective functions. In the QLP model, whilst all continues variables of RN calculated with just using a linear and a non-linear equations set with outer search loop, their general objective functions are also calculated. Comparison the results with the references shows that the presented method is capable of producing better solutions, which, in some cases improvement of about one percent in concentration of the main material in the product and a decrease of 77 % of the residence time of the materials in the reactor system is observed.

A Multi-Level Methodology for Conceptual Reaction-Separation Process Design

Generic technology is presented for the optimal screening of reaction and separation process interactions. The proposed scheme enables the use of particularly rich superstructure formulations that are comprised of two types of generic synthesis units with flexible representation modes. A reaction unit enables a detailed representation of the reaction and a conceptual representation of separation systems is facilitated through separation task units. Possible process design interactions are embedded in the superstructure formulations as combinations of generic units. The design options are explored using stochastic optimisation techniques suitable for this class of problems. The synthesis scheme supports the decision making process in early process design stages and prepares problem definitions for later stages. Conceptual screening functionalities reveal design insights into the performance of complex reaction-separation systems based on the limited modelling information available early in design. This enables the identification and inclusion of the relevant design information into the superstructure formulations employed in the subsequent design stages.