Limited data based kinetic modeling and optimization of propionic acid synthesis over supported Rh/C catalyst

The importance and need for greener and more sustainable chemical processes and technologies can hardly be overestimated. However, many industries still produce a considerable amount of waste. Reusing these waste streams is an indispensable piece towards realizing fully circular and sustainable economy. Accordingly, it is imperative to operate chemical processes with maximal recycling to minimize waste generation. The study presents in the aforedescribed spirit, the synthesis of propionic acid, where the various goals are optimally realized by unleashing the predictive power of nonlinear process model. A method for synthesizing propionic acid is through the heterogeneous catalytic reaction route between ethylene gas, carbon monoxide, and water. The atom efficiency of the process is 100% with the possibility of fully separating the products and recirculating the unreacted starting materials. Hence, the chemistry of the proposed catalytic route is material efficient. To make the process operate well, we apply the available measured data co construct a kinetic model, and use it to optimize the system subject to various goals. The data were not primarily measured for modeling, but for parametric reactor analysis. Yet, using the apriori knowledge about the process (i.e., the microkinetics of the reactions), the data enabled the kinetic model identification, resulting in a fitting on the measured outputs characterized by a coefficient of determination of 0.76. The operating parameters were optimized by using this model to enhance the energy and material efficiency of the process. The optimized turnover frequency happened to be is 3.974 mol / m 3 catalyst/s , reached at 264 °C, 12 bar and ethylene:CO:H 2 O:EtI = 0.379:0.098:0.506:0.016 starting material ratio. • Kinetic model identification based on limited experimental data. • Two-phase propionic acid synthesis was investigated in fixed bed catalytic tubular reactor. • Eley-Rideal type kinetic model was derived based on the reaction mechanism. • The kinetic parameters were identified using a genetic algorithm. • The operational condition of the reactor was optimized through the operating parameters.

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Publication Details

Journal
Chemical Engineering Journal Advances
Published
2024-12-06
DOI
https://doi.org/10.1016/j.ceja.2024.100693
Citations
1
Primary Topic
Catalysis for Biomass Conversion
Type
article
Field-Weighted Citation Impact
0.18
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article

Limited data based kinetic modeling and optimization of propionic acid synthesis over supported Rh/C catalyst

Ágnes Bárkányi, Botond Szilágyi, Jenő Bódis, László Balogh et al.
1 citations
Chemical Engineering Journal Advances
Catalysis for Biomass Conversion
0.18
article

Limited data based kinetic modeling and optimization of propionic acid synthesis over supported Rh/C catalyst

Ágnes Bárkányi, Botond Szilágyi, Jenő Bódis, László Balogh, Attila Egedy
article en
1 citations

Abstract

The importance and need for greener and more sustainable chemical processes and technologies can hardly be overestimated. However, many industries still produce a considerable amount of waste. Reusing these waste streams is an indispensable piece towards realizing fully circular and sustainable economy. Accordingly, it is imperative to operate chemical processes with maximal recycling to minimize waste generation. The study presents in the aforedescribed spirit, the synthesis of propionic acid, where the various goals are optimally realized by unleashing the predictive power of nonlinear process model. A method for synthesizing propionic acid is through the heterogeneous catalytic reaction route between ethylene gas, carbon monoxide, and water. The atom efficiency of the process is 100% with the possibility of fully separating the products and recirculating the unreacted starting materials. Hence, the chemistry of the proposed catalytic route is material efficient. To make the process operate well, we apply the available measured data co construct a kinetic model, and use it to optimize the system subject to various goals. The data were not primarily measured for modeling, but for parametric reactor analysis. Yet, using the apriori knowledge about the process (i.e., the microkinetics of the reactions), the data enabled the kinetic model identification, resulting in a fitting on the measured outputs characterized by a coefficient of determination of 0.76. The operating parameters were optimized by using this model to enhance the energy and material efficiency of the process. The optimized turnover frequency happened to be is 3.974 mol / m 3 catalyst/s , reached at 264 °C, 12 bar and ethylene:CO:H 2 O:EtI = 0.379:0.098:0.506:0.016 starting material ratio. • Kinetic model identification based on limited experimental data. • Two-phase propionic acid synthesis was investigated in fixed bed catalytic tubular reactor. • Eley-Rideal type kinetic model was derived based on the reaction mechanism. • The kinetic parameters were identified using a genetic algorithm. • The operational condition of the reactor was optimized through the operating parameters.

Chemical Engineering Journal AdvancesVol. 21
University of Pannonia (HU), Budapest University of Technology and Economics (HU), Babeș-Bolyai University (RO)
Openalex Percentile: Top 50%
Catalysis for Biomass Conversion
0.18
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