Prediction of hydroxymethylfurfural yield in glucose conversion through investigation of lewis acid and organic solvent effects

Yeonjoon Kim, Ashutosh Mittal, David J. Robichaud, Heidi M. Pilath, Brian D. Etz, Peter C. St. John, David K. Johnson, Seonah Kim

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)14707-14721
Number of pages15
JournalACS Catalysis
Volume10
Issue number24
DOIs
StatePublished - Dec 18 2020

Funding

This work was authored in part by the National Renewable Energy Laboratory, managed and operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract no. DE-AC36-08GO28308. Funding was provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Bioenergy Technologies Office and in collaboration with the Consortium for Computational Physics and Chemistry (CCPC) and the Chemical Catalysis for Bioenergy Consortium (ChemCatBio). Computational resources were provided by the Computational Sciences Center at National Renewable Energy Laboratory and by the NSF Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by NSF grant no. ACI-1053575.

Keywords

  • Cosolvent effect
  • Glucose conversion
  • Hydroxymethylfurfural
  • Lewis acid effect
  • Multivariate model

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