Glycerol Hydrogenolysis Goes SMART─Separating Reaction Steps as a Key for Tailoring Selectivity and Reaction Control

The next generation of flexible, efficient, and robust chemical processes requires adaptive, resilient, and autonomous process systems that drive the transition from fossil to renewable feedstocks as one of the central challenges in building climate-neutral and sustainable chemical value chains. One central element will be the next generation of reactors that are SMART─Sustainable, Multipurpose, Autonomous, Resilient, and Transferable─merging process engineering with materials science, analytics, electronics, and data science. Herein, the chemical hydrogenolysis of glycerol to 1,2-propanediol (1,2-PDO) was used as a case study for tailoring selectivity and reaction control by coupling modeling with experimental approaches for process control, demonstrating adaptive reactor behavior. In detail, the reaction was split into a high-temperature step for the endothermic glycerol dehydration under an inert atmosphere and a consecutive low-temperature step under a hydrogen atmosphere, optimizing the reaction conditions for both reactions and deducing individual kinetic parameters by a graphical analysis of one-factor-at-a-time variations and a global nonlinear regression for the temporal concentration data. The results yield a reaction order of around 0.27 for glycerol with an activation energy of 43 kJ mol–1 for the dehydration step as well as reaction orders of zero for acetol and around 2.15 for hydrogen at an activation energy of 57 kJ mol–1 for the hydrogenation step. The simulated concentration profiles highlight the good agreement between the model and the experimental data. This allows for the implementation of the two-step reaction in a SMART reactor, strengthening the vision of a future generation of autonomous, resilient, and transferable process systems.

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Journal
Industrial & Engineering Chemistry Research
Published
2026-05-27
DOI
https://doi.org/10.1021/acs.iecr.6c00905
Primary Topic
Catalysis for Biomass Conversion
Type
article
Field-Weighted Citation Impact
0.00

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article

Glycerol Hydrogenolysis Goes SMART─Separating Reaction Steps as a Key for Tailoring Selectivity and Reaction Control

Dorothea Voß, Jakob Albert, Leandros Paschalidis, Mirko Skiborowski et al.
Industrial & Engineering Chemistry Research
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article

Glycerol Hydrogenolysis Goes SMART─Separating Reaction Steps as a Key for Tailoring Selectivity and Reaction Control

Dorothea Voß, Jakob Albert, Leandros Paschalidis, Mirko Skiborowski, Piet Hassenstein, Jan-Dominik H. Krueger
article en

Abstract

The next generation of flexible, efficient, and robust chemical processes requires adaptive, resilient, and autonomous process systems that drive the transition from fossil to renewable feedstocks as one of the central challenges in building climate-neutral and sustainable chemical value chains. One central element will be the next generation of reactors that are SMART─Sustainable, Multipurpose, Autonomous, Resilient, and Transferable─merging process engineering with materials science, analytics, electronics, and data science. Herein, the chemical hydrogenolysis of glycerol to 1,2-propanediol (1,2-PDO) was used as a case study for tailoring selectivity and reaction control by coupling modeling with experimental approaches for process control, demonstrating adaptive reactor behavior. In detail, the reaction was split into a high-temperature step for the endothermic glycerol dehydration under an inert atmosphere and a consecutive low-temperature step under a hydrogen atmosphere, optimizing the reaction conditions for both reactions and deducing individual kinetic parameters by a graphical analysis of one-factor-at-a-time variations and a global nonlinear regression for the temporal concentration data. The results yield a reaction order of around 0.27 for glycerol with an activation energy of 43 kJ mol–1 for the dehydration step as well as reaction orders of zero for acetol and around 2.15 for hydrogen at an activation energy of 57 kJ mol–1 for the hydrogenation step. The simulated concentration profiles highlight the good agreement between the model and the experimental data. This allows for the implementation of the two-step reaction in a SMART reactor, strengthening the vision of a future generation of autonomous, resilient, and transferable process systems.

Industrial & Engineering Chemistry Research
Universität Hamburg (DE), Hamburg University of Technology (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 10%
Catalysis for Biomass Conversion
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