TY - JOUR
T1 - Kinetics of Acid-Catalyzed Dehydration of Alcohols in Mixed Solvent Modeled by Multiscale DFT/MD
AU - Tran, Bolton
AU - Milner, Scott T.
AU - Janik, Michael J.
N1 - Publisher Copyright:
© 2022 American Chemical Society. All rights reserved.
PY - 2022/11/4
Y1 - 2022/11/4
N2 - Acid-catalyzed alcohol dehydration is a key reaction step in biomass upgrading, kinetics of which are significantly affected by mixed aqueous solvents. Computational modeling can provide fundamental understanding of solvation effects in catalysis, and ultimately a predictive tool for optimizing reactivity and selectivity. We introduce a multiscale method that combines density functional theory (DFT) with classical molecular dynamics (MD) to investigate the effect of mixed solvents (water with DMSO/GVL/MeCN) on the kinetics of acid-catalyzed dehydration of t-butanol and fructose. We determine the thermodynamically stable form of the excess proton (i.e., the catalyst) in mixed solvents. In water/GVL and water/MeCN mixtures, the excess proton resides on a water cluster (H5O2+). In water/DMSO, it forms a DMSO-H3O+cluster in a bulk water/DMSO mixture, but appears as H5O2+when close to an alcohol reactant. We model the E1 dehydration mechanism on t-butanol and fructose with DFT, and subsequently solvate each reaction intermediate and transition state with MD. Reaction free energy profiles for the elementary steps are mapped out at different solvent compositions. Our predictions compare well to results of Mellmer et al. Nature Catalysis 2018, 1, 199-207 and Nature Communications 2019, 10, 1-10, for both AIMD-measured reaction free energy profiles and experimental rate constants. By decoupling the gas-phase and solvation free energies, our calculation provides a clear interpretation of the solvation effects on an absolute free energy scale, and furthermore deconvolutes these effects into intuitive short-range electronic and longer range electrostatic interactions. Furthermore, our approach reveals solvent structuring around the reaction intermediates and the transition state. Our scalable DFT/MD approach provides a potentially powerful tool to predict reaction kinetics in condensed phases as well as detailed structural and energetic understanding of solvation effects in catalysis.
AB - Acid-catalyzed alcohol dehydration is a key reaction step in biomass upgrading, kinetics of which are significantly affected by mixed aqueous solvents. Computational modeling can provide fundamental understanding of solvation effects in catalysis, and ultimately a predictive tool for optimizing reactivity and selectivity. We introduce a multiscale method that combines density functional theory (DFT) with classical molecular dynamics (MD) to investigate the effect of mixed solvents (water with DMSO/GVL/MeCN) on the kinetics of acid-catalyzed dehydration of t-butanol and fructose. We determine the thermodynamically stable form of the excess proton (i.e., the catalyst) in mixed solvents. In water/GVL and water/MeCN mixtures, the excess proton resides on a water cluster (H5O2+). In water/DMSO, it forms a DMSO-H3O+cluster in a bulk water/DMSO mixture, but appears as H5O2+when close to an alcohol reactant. We model the E1 dehydration mechanism on t-butanol and fructose with DFT, and subsequently solvate each reaction intermediate and transition state with MD. Reaction free energy profiles for the elementary steps are mapped out at different solvent compositions. Our predictions compare well to results of Mellmer et al. Nature Catalysis 2018, 1, 199-207 and Nature Communications 2019, 10, 1-10, for both AIMD-measured reaction free energy profiles and experimental rate constants. By decoupling the gas-phase and solvation free energies, our calculation provides a clear interpretation of the solvation effects on an absolute free energy scale, and furthermore deconvolutes these effects into intuitive short-range electronic and longer range electrostatic interactions. Furthermore, our approach reveals solvent structuring around the reaction intermediates and the transition state. Our scalable DFT/MD approach provides a potentially powerful tool to predict reaction kinetics in condensed phases as well as detailed structural and energetic understanding of solvation effects in catalysis.
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U2 - 10.1021/acscatal.2c03978
DO - 10.1021/acscatal.2c03978
M3 - Article
AN - SCOPUS:85140344058
SN - 2155-5435
VL - 12
SP - 13193
EP - 13206
JO - ACS Catalysis
JF - ACS Catalysis
IS - 21
ER -