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<p>Chemical mechanical polishing (CMP) combines mechanical and chemical effects to achieve ultra-precision machining technology for global planarization of semiconductor materials. As the most ideal semiconductor material in the future, diamond shows great potential in the semiconductor industry. Polycrystalline diamond (PCD) is suitable for more application scenarios, so its surface quality requirements are getting higher and higher. In this study, a surface roughness prediction model of PCD was constructed by analyzing the microscopic interaction between workpiece-abrasive-polishing pad during CMP. At the same time, taking the surface roughness as the evaluation index, the response surface experiment was designed to explore the influence of polishing pressure, polishing speed and abrasive concentration on the surface roughness and their interaction relationship, and the regression model of three process parameters on the surface roughness model was established. Taking the minimum surface roughness value as the goal, the optimal process parameter combination obtained according to the regression model is: the predicted surface roughness is 4.164&#xa0;nm. The actual surface roughness obtained by the experiment is 3.924&#xa0;nm, and the error between the actual value and the predicted value is 5.76%.</p>

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Surface roughness model and process parameter optimization of polycrystalline diamond chemical mechanical polishing

  • 期刊论文

  • 发表日期：

    2026年7月14日

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  • Zhuang Song,
  • Zehan Jin,
  • Haoran Tang,
  • Wanxue Zhang,
  • Zhaoze Li,
  • Jiajun Xu,
  • Guo Xiaoguang

摘要

Chemical mechanical polishing (CMP) combines mechanical and chemical effects to achieve ultra-precision machining technology for global planarization of semiconductor materials. As the most ideal semiconductor material in the future, diamond shows great potential in the semiconductor industry. Polycrystalline diamond (PCD) is suitable for more application scenarios, so its surface quality requirements are getting higher and higher. In this study, a surface roughness prediction model of PCD was constructed by analyzing the microscopic interaction between workpiece-abrasive-polishing pad during CMP. At the same time, taking the surface roughness as the evaluation index, the response surface experiment was designed to explore the influence of polishing pressure, polishing speed and abrasive concentration on the surface roughness and their interaction relationship, and the regression model of three process parameters on the surface roughness model was established. Taking the minimum surface roughness value as the goal, the optimal process parameter combination obtained according to the regression model is: the predicted surface roughness is 4.164 nm. The actual surface roughness obtained by the experiment is 3.924 nm, and the error between the actual value and the predicted value is 5.76%.