Using waste drug tablets as catalyst in the novel transesterification/ultrasonic:electrical shock (TRANS/US-ESH) method for biofuel production

Indian Chemical Engineer, Год журнала: 2025, Номер unknown, С. 1 - 18

Опубликована: Апрель 16, 2025

Язык: Английский

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Integrated approach for response surface methodology optimization in biochar and bio-oil production from Moringa seeds: Pyrolysis enhancement with zeolite catalyst

Bioresource Technology Reports, Год журнала: 2025, Номер unknown, С. 102123 - 102123

Опубликована: Апрель 1, 2025

Язык: Английский

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Optimization of ultrasound-assisted biodiesel production from python fat oil using response surface methodology

Energy Nexus, Год журнала: 2024, Номер unknown, С. 100331 - 100331

Опубликована: Окт. 1, 2024

Язык: Английский

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Process Intensification of Biodiesel Production by Optimization Using Box-Behnken Design: a Review

Chemical Engineering and Processing - Process Intensification, Год журнала: 2024, Номер unknown, С. 110110 - 110110

Опубликована: Дек. 1, 2024

Язык: Английский

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Optimization of the Reaction Conditions in Biodiesel Production: The Case of Baobab Seed Oil as Alternative Feedstock

Journal of Chemistry, Год журнала: 2024, Номер 2024(1)

Опубликована: Янв. 1, 2024

Biodiesel production from underutilized seed oils offers a sustainable and environmentally friendly alternative to fossil fuels for energy generation. The present study focuses on employing response surface methodology (RSM) based Box–Behnken experimental design (BBED) optimize the reaction conditions in biodiesel baobab oil. investigates impact of various variables yield. Specifically, explores influence temperature (40°C–70°C), time (60–120 min), catalyst concentration (0.5–1.5 wt. %), oil‐to‐ethanol ratio (1:3–1:9 mol/mol) optimal After screening as mentioned above, optimized were determined be follows: 55°C, 60 min, 1.5 %, an 1:6 mol/mol. These gave percentage yield 98.6%. Notably, properties obtained met recommended standards. Furthermore, statistical analysis revealed adjusted R 2 value 0.9465, closely aligned with predicted 0.8703, difference less than 0.2. This indicates congeniality data model predictions. Additionally, variance (ANOVA) derived quadratic RSM indicated that could accurately predict conversion 97.32% accuracy, providing insights into observed variations.

Язык: Английский

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Machine learning assisted reactor and full process optimization design for alcohol oxidation

Chemical Engineering Science, Год журнала: 2024, Номер unknown, С. 121165 - 121165

Опубликована: Дек. 1, 2024

Язык: Английский

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