Bayesian Statistics to Elucidate the Kinetics of γ-Valerolactone from n-Butyl Levulinate Hydrogenation over Ru/C

Sarah Capecci; Yanjun Wang; Jose Delgado; Valeria Casson Moreno; Mélanie Mignot; Henrik Grénman; Dmitry Yu Murzin; Sébastien Leveneur

doi:10.1021/acs.iecr.1c02107

Bayesian Statistics to Elucidate the Kinetics of γ-Valerolactone from n-Butyl Levulinate Hydrogenation over Ru/C

Sarah Capecci
, Yanjun Wang
, Jose Delgado
, Valeria Casson Moreno
, Mélanie Mignot
, Henrik Grénman
, Dmitry Yu Murzin
, Sébastien Leveneur^*

^*Korresponderande författare för detta arbete

Forskningsoutput: Tidskriftsbidrag › Artikel › Vetenskaplig › Peer review

20 Citeringar (Scopus)

76 Nedladdningar (Pure)

Sammanfattning

The synthesis of γ-valerolactone (GVL), a platform molecule that can be produced from lignocellulosic biomass, was performed in this work by hydrogenation of an alkyl levulinate over Ru/C. Kinetic models reported in the literature are typically not compared with rival alternatives, even if a discrimination study is needed to find the optimum operating conditions. Different surface reaction kinetic models were thus considered in this work, specifically addressing hydrogenation of butyl levulinate to GVL, where the latter was used as a solvent to minimize potential solvent interference with the reaction, including its evaporation. The Bayesian approach was applied to evaluate the probability of each model. It was found that non-competitive Langmuir-Hinshelwood with no dissociation of the hydrogen model has the highest posterior probability.

Originalspråk	Engelska
Sidor (från-till)	11725-11736
Antal sidor	12
Tidskrift	Industrial and Engineering Chemistry Research
Volym	60
Nummer	31
Tidigt onlinedatum	29 juli 2021
DOI	https://doi.org/10.1021/acs.iecr.1c02107
Status	Publicerad - 11 aug. 2021
MoE-publikationstyp	A1 Tidskriftsartikel-refererad

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This study has been done in the framework of Task 2: “Green process: 2nd generation of biomass” of the AMED project. The authors thank the AMED project. The AMED project has been funded with the support from the European Union with the European Regional Development Fund (ERDF) and from the Regional Council of Normandie. For the analytical part (GC-FID), the authors thank the European Regional Development Fund (GreenChem) and the Laboratoire d’Excellence (LabEx) SynOrg (ANR-11-LABX-0029). The authors thank the Maîtrise des Risques et Environementaux department and the Erasmus program that made the research project of S.C. possible.

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https://urn.fi/URN:NBN:fi-fe2022120168454

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title = "Bayesian Statistics to Elucidate the Kinetics of γ-Valerolactone from n-Butyl Levulinate Hydrogenation over Ru/C",

abstract = "The synthesis of γ-valerolactone (GVL), a platform molecule that can be produced from lignocellulosic biomass, was performed in this work by hydrogenation of an alkyl levulinate over Ru/C. Kinetic models reported in the literature are typically not compared with rival alternatives, even if a discrimination study is needed to find the optimum operating conditions. Different surface reaction kinetic models were thus considered in this work, specifically addressing hydrogenation of butyl levulinate to GVL, where the latter was used as a solvent to minimize potential solvent interference with the reaction, including its evaporation. The Bayesian approach was applied to evaluate the probability of each model. It was found that non-competitive Langmuir-Hinshelwood with no dissociation of the hydrogen model has the highest posterior probability. ",

author = "Sarah Capecci and Yanjun Wang and Jose Delgado and \{Casson Moreno\}, Valeria and M{\'e}lanie Mignot and Henrik Gr{\'e}nman and Murzin, \{Dmitry Yu\} and S{\'e}bastien Leveneur",

note = "Funding Information: This study has been done in the framework of Task 2: “Green process: 2nd generation of biomass” of the AMED project. The authors thank the AMED project. The AMED project has been funded with the support from the European Union with the European Regional Development Fund (ERDF) and from the Regional Council of Normandie. For the analytical part (GC-FID), the authors thank the European Regional Development Fund (GreenChem) and the Laboratoire d{\textquoteright}Excellence (LabEx) SynOrg (ANR-11-LABX-0029). The authors thank the Ma{\^i}trise des Risques et Environementaux department and the Erasmus program that made the research project of S.C. possible. Publisher Copyright: {\textcopyright} 2021 American Chemical Society.",

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doi = "10.1021/acs.iecr.1c02107",

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AU - Capecci, Sarah

AU - Wang, Yanjun

AU - Delgado, Jose

AU - Casson Moreno, Valeria

AU - Mignot, Mélanie

AU - Grénman, Henrik

AU - Murzin, Dmitry Yu

AU - Leveneur, Sébastien

N1 - Funding Information: This study has been done in the framework of Task 2: “Green process: 2nd generation of biomass” of the AMED project. The authors thank the AMED project. The AMED project has been funded with the support from the European Union with the European Regional Development Fund (ERDF) and from the Regional Council of Normandie. For the analytical part (GC-FID), the authors thank the European Regional Development Fund (GreenChem) and the Laboratoire d’Excellence (LabEx) SynOrg (ANR-11-LABX-0029). The authors thank the Maîtrise des Risques et Environementaux department and the Erasmus program that made the research project of S.C. possible. Publisher Copyright: © 2021 American Chemical Society.

PY - 2021/8/11

Y1 - 2021/8/11

N2 - The synthesis of γ-valerolactone (GVL), a platform molecule that can be produced from lignocellulosic biomass, was performed in this work by hydrogenation of an alkyl levulinate over Ru/C. Kinetic models reported in the literature are typically not compared with rival alternatives, even if a discrimination study is needed to find the optimum operating conditions. Different surface reaction kinetic models were thus considered in this work, specifically addressing hydrogenation of butyl levulinate to GVL, where the latter was used as a solvent to minimize potential solvent interference with the reaction, including its evaporation. The Bayesian approach was applied to evaluate the probability of each model. It was found that non-competitive Langmuir-Hinshelwood with no dissociation of the hydrogen model has the highest posterior probability.

AB - The synthesis of γ-valerolactone (GVL), a platform molecule that can be produced from lignocellulosic biomass, was performed in this work by hydrogenation of an alkyl levulinate over Ru/C. Kinetic models reported in the literature are typically not compared with rival alternatives, even if a discrimination study is needed to find the optimum operating conditions. Different surface reaction kinetic models were thus considered in this work, specifically addressing hydrogenation of butyl levulinate to GVL, where the latter was used as a solvent to minimize potential solvent interference with the reaction, including its evaporation. The Bayesian approach was applied to evaluate the probability of each model. It was found that non-competitive Langmuir-Hinshelwood with no dissociation of the hydrogen model has the highest posterior probability.

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Bayesian Statistics to Elucidate the Kinetics of γ-Valerolactone from n-Butyl Levulinate Hydrogenation over Ru/C

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