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Performance Evaluation of Benzyl Alcohol Oxidation with tert-Butyl Hydroperoxide to Benzaldehyde Using the Response
Ikenna Chibuzor Emeji1, Michael Kumi2, Reinout Meijboom1
1Faculty of Science, Department of Chemical Sciences-APK, University of Johannesburg. P.O. Box 524, Auckland Park 2600 Johannesburg 2006, South Africa.
This study optimized benzaldehyde synthesis using a ceria-zirconia catalyst and advanced modeling techniques. The adaptive neuro-fuzzy inference system (ANFIS) best predicted high yields for this green chemistry approach.
Area of Science:
- Catalysis
- Materials Science
- Chemical Engineering
Background:
- Selective oxidation of benzyl alcohol to benzaldehyde is crucial for chemical synthesis.
- Developing efficient and sustainable catalytic systems is a key challenge.
- Mesoporous ceria-zirconia catalysts offer unique properties for oxidation reactions.
Purpose of the Study:
- To model and optimize the selective oxidation of benzyl alcohol to benzaldehyde using a mesoporous ceria-zirconia catalyst.
- To compare the predictive capabilities of artificial neural network (ANN), response surface methodology (RSM), and adaptive neuro-fuzzy inference system (ANFIS) for this reaction.
- To evaluate the green chemistry metrics of the optimized process.
Main Methods:
- Synthesis of a mesoporous ceria-zirconia catalyst via the inverse micelle method.
- Characterization of the catalyst's structure and properties.
- Optimization of reaction parameters (catalyst amount, temperature, time) using ANN, RSM, and ANFIS models.
- Evaluation of model performance using statistical error functions and ANOVA.
- Calculation of green chemistry metrics (E-factor, Mass Intensity, Mass Productivity).
Main Results:
- The synthesized ceria-zirconia catalyst exhibited desirable structural properties like hysteresis loops and a sponge-like morphology.
- Optimal reaction conditions yielded a maximum benzaldehyde yield of 98.4%.
- The ANFIS model demonstrated the highest accuracy in predicting benzaldehyde yield, followed by RSM.
- The reaction exhibited favorable green chemistry metrics, with a low E-factor (1.57) and Mass Intensity (2.57).
Conclusions:
- The mesoporous ceria-zirconia catalyst is effective for the selective oxidation of benzyl alcohol to benzaldehyde.
- ANFIS is the most suitable model for predicting reaction outcomes in this system.
- The developed methodology offers a green and sustainable route for benzaldehyde synthesis under mild conditions.
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