(301f) Autoacceleration in L-Proline-Catalyzed Aldol-Type Reactions: A DFT and Microkinetic Modeling Study
AIChE Annual Meeting
Tuesday, November 10, 2009 - 5:00pm to 5:21pm
Aldol-type reactions are essential for the formation of complex hydrocarbons from smaller molecules. The pharmaceutical, petrochemical, and agricultural industries can derive only a limited number of paraffins, naphthenes, and aromatic components from petroleum refining. The current catalyst range for these processes extends from traditional strong acids and bases, transition metals, and heterogeneous materials to environmentally friendly enzymes and catalytic antibodies. While conventional methods can be plagued by harsh reaction conditions, corrosive reagents and costly protecting groups, enzymes and catalytic antibodies have high substrate specificity. However, they can be costly to engineer.
L-proline, an amino acid, represents a class of biomimetic catalytic materials called organocatalysts. Under homogeneous conditions, L-proline promotes aldol-type reactions at low temperatures, exhibits a high yield, enantioselectivity and atom efficiency, and is inexpensive to synthesize. Nevertheless, a practical limitation to the use of L-proline as a catalyst stems from long reaction times and a low turnover number.
Recently, auto-inductive behavior has been observed in L-proline-assisted α-aminoxylation and α-amination reactions. As a consequence, these processes occur on the time scale of minutes or hours. Experimental kinetics techniques are unable to pinpoint definitively the nature of the rate-enhancing interactions in the catalytic cycle. To date, all L-proline assisted aldol-type reactions are considered to proceed via the same biomimetic catalytic cycle involving the formation of an enamine intermediate. Therefore, to understanding the origin of the unusual kinetic behavior in certain L-proline-catalyzed reactions, we used density functional theory (DFT) to map the reaction coordinates of an aldol addition and an α-aminoxylation reaction. All stable intermediates and transition states along the reaction coordinates were located using the Gaussian 03 computational chemistry software. Currently, in the literature, there exist several hypotheses for the source of autoacceleration. Our study explored their validity. In order to identify the rate-limiting step in each process, microkinetic models were developed employing rate parameters calculated from the quantum chemical results and standard statistical thermodynamics methods. As a result, we were able to diagnose the observed auto-inductive behavior as well as prescribe targets for catalyst improvement.