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<p>The worldwide adoption of eco-friendly fuels significantly alleviates the detrimental impacts of alterations in climate, primarily driven by fossil fuel-derived greenhouse gas emissions. Biodiesel has been recognized as a viable substitute fuel for address the escalating global vitality demands. This global predicament compels producers and researchers to strategically leverage oils as feedstock for biodiesel production, ensuring maximum efficacy and sustainability. Given this context, it becomes imperative to rigorously scrutinize the transesterification parameters and embark on pioneering optimization studies to significantly augment biodiesel yield. The process for generating biodiesel from Karanja oil utilizing a household microwave is meticulously investigated in this manuscript, which delineates an intricate mathematical framework for optimizing production of biodiesel. The principal objective of this work presents a novel approach to optimizing biodiesel production by integrating pilot experiments with Response Surface Methodology. Empirical data from pilot trials were used to determine precise operational ranges for key parameters— percentage of methanol to oil, catalyst concentration, microwave power and reaction duration—tailored to Karanja oil, a non-edible feedstock. To achieve this, Response Surface Methodology with a Box-Behnken Design encompassing three tiers and four components was employed for comprehensive modelling and optimization. A polynomial model of second-order robustly approximates the response surface, thereby enabling the precise analysis of optimal process variable values. An optimum biodiesel yield of 99.981% was achieved under the specified conditions of a 48.776% molar proportion, 1.455% KOH concentration, a reaction duration of 4.059&#xa0;min and 302.113 W power. The results underscore that Response Surface Methodology not only provides a potent framework for optimizing biodiesel production but also substantially minimizes experimental efforts through predictive and sophisticated statistical analysis.</p>

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Optimization of Process Parameters and Biodiesel Extraction of Pogamia Pinnata via Response Surface Methodology

  • 期刊论文

  • 发表日期：

    2025年5月25日

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  • Anshika,
  • Vivek Goel,
  • Sunil Kumar

摘要

The worldwide adoption of eco-friendly fuels significantly alleviates the detrimental impacts of alterations in climate, primarily driven by fossil fuel-derived greenhouse gas emissions. Biodiesel has been recognized as a viable substitute fuel for address the escalating global vitality demands. This global predicament compels producers and researchers to strategically leverage oils as feedstock for biodiesel production, ensuring maximum efficacy and sustainability. Given this context, it becomes imperative to rigorously scrutinize the transesterification parameters and embark on pioneering optimization studies to significantly augment biodiesel yield. The process for generating biodiesel from Karanja oil utilizing a household microwave is meticulously investigated in this manuscript, which delineates an intricate mathematical framework for optimizing production of biodiesel. The principal objective of this work presents a novel approach to optimizing biodiesel production by integrating pilot experiments with Response Surface Methodology. Empirical data from pilot trials were used to determine precise operational ranges for key parameters— percentage of methanol to oil, catalyst concentration, microwave power and reaction duration—tailored to Karanja oil, a non-edible feedstock. To achieve this, Response Surface Methodology with a Box-Behnken Design encompassing three tiers and four components was employed for comprehensive modelling and optimization. A polynomial model of second-order robustly approximates the response surface, thereby enabling the precise analysis of optimal process variable values. An optimum biodiesel yield of 99.981% was achieved under the specified conditions of a 48.776% molar proportion, 1.455% KOH concentration, a reaction duration of 4.059 min and 302.113 W power. The results underscore that Response Surface Methodology not only provides a potent framework for optimizing biodiesel production but also substantially minimizes experimental efforts through predictive and sophisticated statistical analysis.