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

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 carbocationmore » 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.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [1];  [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1755729
Report Number(s):
NREL/JA-2800-76844
Journal ID: ISSN 2155-5435; MainId:10488;UUID:49d7cd01-d109-430f-abe7-f3e3ae3a8151;MainAdminID:19057
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
ACS Catalysis
Additional Journal Information:
Journal Volume: 10; Journal Issue: 24; Journal ID: ISSN 2155-5435
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; glucose conversion; hydroxymethylfurfural; Lewis acid effect; cosolvent effect; multivariate model

Citation Formats

Kim, Yeonjoon, Mittal, Ashutosh, Robichaud, David J., Pilath, Heidi M., Etz, Brian D., St. John, Peter C., Johnson, David K., and Kim, Seonah. Prediction of Hydroxymethylfurfural Yield in Glucose Conversion through Investigation of Lewis Acid and Organic Solvent Effects. United States: N. p., 2020. Web. doi:10.1021/acscatal.0c04245.
Kim, Yeonjoon, Mittal, Ashutosh, Robichaud, David J., Pilath, Heidi M., Etz, Brian D., St. John, Peter C., Johnson, David K., & Kim, Seonah. Prediction of Hydroxymethylfurfural Yield in Glucose Conversion through Investigation of Lewis Acid and Organic Solvent Effects. United States. https://doi.org/10.1021/acscatal.0c04245
Kim, Yeonjoon, Mittal, Ashutosh, Robichaud, David J., Pilath, Heidi M., Etz, Brian D., St. John, Peter C., Johnson, David K., and Kim, Seonah. Mon . "Prediction of Hydroxymethylfurfural Yield in Glucose Conversion through Investigation of Lewis Acid and Organic Solvent Effects". United States. https://doi.org/10.1021/acscatal.0c04245. https://www.osti.gov/servlets/purl/1755729.
@article{osti_1755729,
title = {Prediction of Hydroxymethylfurfural Yield in Glucose Conversion through Investigation of Lewis Acid and Organic Solvent Effects},
author = {Kim, Yeonjoon and Mittal, Ashutosh and Robichaud, David J. and Pilath, Heidi M. and Etz, Brian D. and St. John, Peter C. and Johnson, David K. and Kim, Seonah},
abstractNote = {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.},
doi = {10.1021/acscatal.0c04245},
journal = {ACS Catalysis},
number = 24,
volume = 10,
place = {United States},
year = {Mon Nov 30 00:00:00 EST 2020},
month = {Mon Nov 30 00:00:00 EST 2020}
}

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