274678 Bio-Based Gasoline Additives: Product and Chemistry Selection Through Network Generation and Optimization
Several biomass-derived oxygenates, such as butanol and dimethylfuran (DMF), have been proposed as alternatives to ethanol for blending into current gasoline fuels. Each of these oxygenates can be synthesized from bio-based platform chemicals such as 5-hydroxymethylfurfural (HMF), acetone, ethanol, etc. in multiple ways. Consequently, there are several options for choosing the product (gasoline additive) and the synthesis route. We propose a strategy for optimal product and process chemistry selection by combining rule-based reaction network generation and mixed-integer linear programming (MILP).
Our strategy is composed of two steps. First, we use a reaction network generation tool, RING , developed in our group to construct a network of all possible reactions that are involved in converting bio-based platform compounds to potential gasoline additives. RING takes in as input reaction rules that determine the chemistries being explored. In this case, we include a broad spectrum of heterogeneous acid, base, and metal catalyzed chemistries as reaction rules.
Second, we formulate an MILP to determine the optimal vector of steady-state fluxes through the reaction network that minimizes catalyst use and reactor capital, and corresponds to an oxygenate blend that satisfies the requirements for gasoline additives. The objective function incorporates estimated reaction kinetics for each reaction based on the corresponding reaction rule. Due to the detailed chemistry of the reaction network being embedded into the MILP, the optimal vector determines (1) an oxygenate blend compatible with gasoline and (2) synthesis routes to produce each oxygenate from bio-based platform chemicals. Alternative synthesis routes and oxygenate blends are identified that have competitive objective functions.
This two-step strategy proposed here is generic and scalable for any product-cum-chemistry selection problem. The set of reaction rules, rate estimation, objective function and constraints formulation, and thermochemical analysis of the optimal synthesis routes will be presented and discussed.
 Rangarajan, S.; Bhan, A.; Daoutidis, P. Rule-based generation of thermochemical routes to biomass conversion, Industrial & Engineering Chemistry Research 2010, 49 (21), 10459-10470