(29e) Enhancing Reaction Rates By Automated in silico Solvent Screening

Solvents have a large impact on the overall performance of chemical processes. In particular, solvents can significantly enhance chemical reactions by increasing reaction rates and selectivities [1]. Thus, solvents need to be carefully selected. Selecting suitable solvents is a challenging task since experimental data for reaction rates and selectivities are often scarce in early process design. Thus, solvents are usually selected from a limited set of known solvents based on heuristic guidelines and expert knowledge. However, this conventional approach does not exploit the potential of the large molecular design space of all possible solvents and likely results in suboptimal choices [2].

To overcome this limitation, we propose an automated solvent screening approach to select solvents in silicofor enhancing reaction rates. The key for this approach is the prediction of liquid phase reaction rates. For this purpose, we calculate gas phase reaction rates and solvation effects using quantum chemistry [3,4]. To reduce the computational burden of quantum chemistry to a level enabling efficient large-scale solvent screening, computationally expensive quantum mechanical calculations of gas phase reaction rates are performed only once per reaction. In contrast, solvation effects in the different solvents are computed with COSMO-RS [5] at low computational cost. Thus, reaction rates in different solvents are predicted efficiently and the resulting solvent screening allows for the evaluation of thousands of solvents within few days. Thereby, we can extend our recent solvent screening framework from equilibrium properties [6] to kinetic properties.

We apply our approach to a Carbamate cleavage reaction and identify solvents which enhance reaction rates compared to the benchmark solvent. The resulting framework is generally applicable to liquid phase reactions and allows the efficient screening of solvents for optimal reaction rates.

Literature

[1] Struebing, H., Ganase, Z., Karamertzanis, P. G., Siougkrou, E., Haycock, P., Piccione, P. M., Armstrong, A., Galindo, A. and Adjiman, C. S.: Computer-aided molecular design of solvents for accelerated reaction kinetics. Nature Chemistry 5 (2013), 952–957.

[2] Adjiman, C. S., Galindo, A. and Jackson, G.: Molecules Matter: the Expanding Envelope of Process Design. Computer-Aided Chemical Engineering 34 (2014), 55-64.

[3] Deglmann, P., Müller, I., Becker, F., Schäfer, A., Hungenberg, K.-D. and Weiß, H.: Prediction of Propagation Rate Coefficients in Free Radical Solution Polymerization Based on Accurate Quantum Chemical Methods: Vinylic and Related Monomers, Including Acrylates and Acrylic Acid. Macromolecular Reaction Engineering 3 (2009), 496-515.

[4] Kröger, L. C., Kopp, W. A. and Leonhard, K.: Prediction of Chain Propagation Rate Constants of Polymerization Reactions in Aqueous NIPAM/BIS and VCL/BIS Systems. The Journal of Physical Chemistry B 121 (2017), 2887-2895.

[5] Klamt, A., Eckert, F., Arlt, W.: COSMO-RS: an alternative to simulation for calculating thermodynamic properties of liquid mixtures. Annual Reviews of Chemical and Biomolecular Engineering 1 (2010), 101–122.

[6] Scheffczyk, J., Redepenning, C., Jens, C., Winter, B., Leonhard, K., Marquardt, W. and Bardow, A.: Massive, Automated Solvent Screening for Minimum Energy Demand in Hybrid Extraction-Distillation Using COSMO-RS. Chemical Engineering Research & Design 115 (2016), 433-442.