Prediction of Hydroxymethylfurfural Yield in Glucose Conversion through Investigation of Lewis Acid and Organic Solvent Effects

• Published in: ACS catalysis 2020-12, Vol.10 (24), p.14707-14721
• Main Authors: Kim, Yeonjoon, Mittal, Ashutosh, Robichaud, David J, Pilath, Heidi M, Etz, Brian D, St. John, Peter C, Johnson, David K, Kim, Seonah
• Format: Article
• Language: English
• Subjects: cosolvent effect; glucose conversion; hydroxymethylfurfural; INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Lewis acid effect; multivariate model
• ISSN: 2155-5435; 2155-5435
• DOI: 10.1021/acscatal.0c04245

Hydroxymethylfurfural (HMF) is one of the important renewable platform compounds that can be obtained from biomass feedstocks through glucose conversion catalyzed by Brønsted and Lewis acids. However, it is challenging to enhance the HMF yield due to side reactions. In this study, a systematic approach combining theory and experiment was performed to investigate the influence of Lewis acids and organic solvents on the HMF yield. For the Lewis acid effect, a relationship between chemical hardness and experimental HMF yields was found in the rate-limiting step of glucose-to-fructose isomerization for six metal chlorides; HMF production was promoted when the metal chloride and a substrate had a similar chemical hardness. To study the organic solvent effect, a multivariate model was developed based on the insights gained from the mechanistic study of fructose dehydration, to predict HMF yields in a given water-organic cosolvent system. It showed a reliable accuracy in evaluating HMF yields with a mean absolute error (MAE) of 3.0% with respect to experimental HMF yields for 13 solvents, and also predicted HMF yields with a MAE of 10.7% for four new solvents. Chemical interpretation of the model revealed that it is desirable to use a solvent capable of stabilizing the carbocation intermediates with low proton transfer activity and high hydrogen bond basicity, to maximize the HMF yield. This multivariate model informs experimentalists about rational selection of solvents with very low computational costs needed to calculate only six variables for each solvent. It can be expanded to other catalytic systems such as heterogeneous Brønsted–Lewis bifunctional catalysts and enables optimization of reaction conditions to obtain other useful platform molecules through biomass conversion.