(185c) Optimal Synthesis of Reaction Networks for the Manufacture of Benzaldehyde from Toluene Via the P-Graph Methodology

Herein, the optimal and near-optimal reaction networks yielding benzaldehyde from toluene are algorithmically synthesized from a set of reactions of industrial interest. This is accomplished by the judicious adaptation of the principles and methodology of process-network synthesis (PNS) based on P-graphs; thus, the problem explored in this work is termed reaction-network synthesis (RNS) accordingly. In fact, RNS is the first step in optimizing chemical processes via PNS whose design is guided by the P-graph framework. At the outset, the feasible reaction networks are selected from the set of all plausible reactions producing benzaldehyde from toluene available in the literature; this selection is effected by ranking the plausible reactions by their industrial significance. Moreover, the reactions selected are stoichiometrically balanced and depicted by P-graphs, thereby graphically representing the reacting species, i.e., reactants and products. Subsequently, the superstructure formed by combining the P-graphs of the feasible reactions is generated by resorting to algorithm maximal-structure generation (MSG). In addition, the combinatorially and stoichiometrically feasible reaction networks are determined from the superstructure via algorithm solution-structure generation (SSG) and integer linear programming (LP). Finally, the optimal and near-optimal reaction networks are identified from those stoichiometrically feasible by means of an objective function defined in terms of the profit that could be obtained from the reactions. Furthermore, the objective function embeds the reaction networks’ environmental impact by means of suitable metrics, such as explosiveness and aquatic-toxicity potential.