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<p>Boron carbide (B<sub>4</sub>C) is widely applied in high-end fields for its excellent comprehensive properties. Although self-propagating high-temperature synthesis (SHS) has the advantages of high efficiency and energy saving, its process parameters are experience-dependent, and it is difficult to synergistically optimize product purity and particle size. To solve these problems, this study used glucose as an organic carbon source and combined response surface methodology (RSM) to conduct multi-objective collaborative optimization of the SHS preparation process of B<sub>4</sub>C. The results show that the second-order regression model established based on RSM has good prediction accuracy, and the optimal process parameters are determined as follows: carbon content 0.87&#xa0;mol, argon pressure 1.18&#xa0;atm, compaction pressure 29.89&#xa0;MPa, and sample mass 50.23&#xa0;g. The B<sub>4</sub>C powder prepared under these conditions has a free carbon content as low as 0.601 wt%, a particle size of approximately 1.086&#xa0;μm, and well-developed crystallinity. The innovation of this study lies in the combination of organic carbon source regulation, SHS reaction, and RSM multi-objective optimization to realize the synergistic control of free carbon content and particle size. It provides a quantifiable and predictable optimization method for the preparation of high-performance B<sub>4</sub>C powder via the SHS process.</p>

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Process optimization of B4C powder synthesis based on organic carbon sources by response surface methodology

  • 期刊论文

  • 发表日期：

    2026年5月26日

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  • Ceng Wang,
  • Zhi-he Dou,
  • Ling-feng Wang,
  • Ge Jin,
  • Ting-an Zhang

摘要

Boron carbide (B4C) is widely applied in high-end fields for its excellent comprehensive properties. Although self-propagating high-temperature synthesis (SHS) has the advantages of high efficiency and energy saving, its process parameters are experience-dependent, and it is difficult to synergistically optimize product purity and particle size. To solve these problems, this study used glucose as an organic carbon source and combined response surface methodology (RSM) to conduct multi-objective collaborative optimization of the SHS preparation process of B4C. The results show that the second-order regression model established based on RSM has good prediction accuracy, and the optimal process parameters are determined as follows: carbon content 0.87 mol, argon pressure 1.18 atm, compaction pressure 29.89 MPa, and sample mass 50.23 g. The B4C powder prepared under these conditions has a free carbon content as low as 0.601 wt%, a particle size of approximately 1.086 μm, and well-developed crystallinity. The innovation of this study lies in the combination of organic carbon source regulation, SHS reaction, and RSM multi-objective optimization to realize the synergistic control of free carbon content and particle size. It provides a quantifiable and predictable optimization method for the preparation of high-performance B4C powder via the SHS process.