(445d) Ab-Initio and Computer-Aided Molecular Design for the Identification of Optimal Solvents for Reactions | AIChE

(445d) Ab-Initio and Computer-Aided Molecular Design for the Identification of Optimal Solvents for Reactions

Authors 

Siougkrou, E. - Presenter, Imperial College London, Centre for Process Systems Engineering
Adjiman, C. S., Imperial College London
Galindo, A., Imperial College London


A solvent is frequently used as a medium for liquid-phase reactions and its role is significant, especially in the control of reaction rates and temperature. The prediction of the effects of solvents on a given reaction and the rational choice of the most appropriate solvent for the reaction are complex challenges. Strübing et al.1 have proposed an algorithm for the Computer-Aided Molecular Design (CAMD) of solvents for chemical reactions, where quantum mechanical (QM) calculations and a surrogate (approximate) model are used for the prediction of the reaction rate constant in various solvents. This approach has been successfully applied to the design of an improved solvent for a Menschutkin reaction, which was subsequently tested experimentally and shown to lead to a 40% increase in the measured rate constant, relative to the best initial solvent. Here we develop the approach further by removing the need for a surrogate model, which can be shown to introduce modeling error in the overall methodology.  An optimisation CAMD formulation is used to predict the solvent that maximises the reaction rate. A design of several thousand potential molecules can be explored in this way. The reaction rate constants in the solvents tested during the course of the algorithm are obtained from QM calculations, using conventional transition state theory (CTST). The rate constant, according to CTST, is a function of the standard state free energy of solvation of the reactants and transition state. The free energy of solvation is calculated in this work from the SMD solvation model2. The proposed approach is compared to the CAMD algorithm of Strübing et al.1 through application to a Menschutkin SN2 reaction and the numerical performance and accuracy of both approaches is discussed. 

References

[1] H. Strübing, P. G. Karamertzanis, E. N. Pistikopoulos, A. Galindo, C. S. Adjiman, Solvent design for a Menschutkin reaction by using CAMD and DFT calculations, Comp. Aided Chem. Eng., 2010, 28, 1291-1296

[2]  A. V. Marenich, C. J. Cramer, D. G. Truhlar, Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions, J. Phys. Chem. B, 2009, 113, 6378-6396

See more of this Session: Process Design I

See more of this Group/Topical: Computing and Systems Technology Division