SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODEL

Finding the most efficient solvent for a chemical reaction can demand costly experimental procedure and the screening is usually limited to few solvents. The use of theoretical methods could accelerate the search for the best solvent, able to promote most effective kinetics and thermodynamics of a reaction. In this work, it was proposed an automated procedure that calculates the solvent effect for a chemical reaction using all the 179 solvents available in SMD (solvation model density). The reaction of 2-bromoacetophenone with pyridine was used as a test. The SMD model correctly predicts the reactivity trends for five solvents, which experimental data are available. We have found that sulfolane, a less usual solvent, is the best one for this reaction. The present study points out that computational screening of large set of solvents using the SMD model is a viable approach and could be useful for chemical reactions optimization.