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<p>Bio-oil produced via biomass waste pyrolysis has the considerable potential as a petroleum alternative. Hence, this study selects corn stalk as the raw material and optimizes its pyrolysis parameters by employing response surface methodology (RSM) to achieve optimal bio-oil yield and higher heating value (HHV). Then, the mathematical regression models are established to predict kinetic parameters of the pyrolysis process. Results showed that: The interactions between reaction temperature and catalyst dosage and heating rate and catalyst dosage have a significant effect on bio-oil yield; the interaction between reaction temperature and catalyst dosage has significant effects on bio-oil HHV; RSM results of bio-oil yield showed that optimal reaction conditions are 615&#xa0;°C of reaction temperature, 29&#xa0;s of reaction time, 113&#xa0;°C/min of heating rate, and 8.2:1 of catalyst dosage; and the optimal reaction conditions for bio-oil HHV are 597&#xa0;°C of reaction temperature, 33&#xa0;s of reaction time, 109&#xa0;°C/min of heating rate, and 7:1 of catalyst dosage. The results of verification tests prove that the models have the high accuracy and reliability. (3) The quadratic regression equations obtained by linear fitting could accurately predict the <i>n</i>, <i>E</i>, and <i>A</i> values of corn stalk pyrolysis, and they are quite accurate in the temperature range of 200–550&#xa0;°C. This study can further improve the theoretical foundation for industrial application of bio-oil via biomass waste pyrolysis.</p>

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Parameters Optimization and Kinetic Model Establishment of Corn Stalk Pyrolysis to Produce Bio-Oil

  • 期刊论文

  • 发表日期：

    2026年3月9日

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  • Kui Zheng,
  • Geng Xu,
  • Shiqiu Zhang

摘要

Bio-oil produced via biomass waste pyrolysis has the considerable potential as a petroleum alternative. Hence, this study selects corn stalk as the raw material and optimizes its pyrolysis parameters by employing response surface methodology (RSM) to achieve optimal bio-oil yield and higher heating value (HHV). Then, the mathematical regression models are established to predict kinetic parameters of the pyrolysis process. Results showed that: The interactions between reaction temperature and catalyst dosage and heating rate and catalyst dosage have a significant effect on bio-oil yield; the interaction between reaction temperature and catalyst dosage has significant effects on bio-oil HHV; RSM results of bio-oil yield showed that optimal reaction conditions are 615 °C of reaction temperature, 29 s of reaction time, 113 °C/min of heating rate, and 8.2:1 of catalyst dosage; and the optimal reaction conditions for bio-oil HHV are 597 °C of reaction temperature, 33 s of reaction time, 109 °C/min of heating rate, and 7:1 of catalyst dosage. The results of verification tests prove that the models have the high accuracy and reliability. (3) The quadratic regression equations obtained by linear fitting could accurately predict the n, E, and A values of corn stalk pyrolysis, and they are quite accurate in the temperature range of 200–550 °C. This study can further improve the theoretical foundation for industrial application of bio-oil via biomass waste pyrolysis.