Material removal rate model of single crystal diamond near atomic scale chemical mechanical polishing based on SOA

Traditional mechanical polishing faces significant challenges in achieving ideal surface quality on single crystal diamond (SCD). Chemical mechanical polishing (CMP), combining chemical oxidation and mechanical grinding, offers an effective solution for improving the surface quality of hard and brittle materials. Understanding the material removal characteristics of SCD during CMP is crucial. In this study, the instantaneous contact velocity model of the workpiece and the abrasive particles is established by geometric kinematics, and the instantaneous contact velocity of the abrasive particles at any point on the surface of the workpiece is obtained. Based on the Greenwood and Williamson elastic contact model, the microscopic contact model between the workpiece and the polishing pad is studied, and the effective contact area between the workpiece and the polishing pad and the number of abrasive particles in the effective contact area are obtained. Considering the elastic-plastic deformation in the CMP process of SCD, the micro-contact model between single abrasive particle and workpiece surface is further established, and then the material removal rate (MRR) prediction model of SCD CMP is established. Experimental results reveal the impact of polishing pressure and speed on MRR and surface roughness. The theoretical MRR values align with experimental trends, and the Seagull Optimization Algorithm (SOA) refines the model, reducing the average relative error between theoretical and experimental MRR to 5.98 % and 5.81 %, respectively. The results demonstrate the model's validity. The SCD with near atomic scale ultra-smooth surface is obtained, and the sub-nanometer surface roughness Sa is 0.311 nm. At the same time, the interaction mechanism between chemical oxidation and mechanical removal is investigated through atomic-scale analysis using the ReaxFF molecular dynamics model.

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Publication Details

Journal
Journal of Materials Research and Technology
Published
2025-03-13
DOI
https://doi.org/10.1016/j.jmrt.2025.03.109
Citations
10
Primary Topic
Advanced Surface Polishing Techniques
Type
article
Field-Weighted Citation Impact
6.74

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article

Material removal rate model of single crystal diamond near atomic scale chemical mechanical polishing based on SOA

Renke Kang, Wanxue Zhang, Zhuang Song, Zhaoze Li et al.
10 citations
Journal of Materials Research and Technology
Advanced Surface Polishing Techniques
6.74
article

Material removal rate model of single crystal diamond near atomic scale chemical mechanical polishing based on SOA

Renke Kang, Wanxue Zhang, Zhuang Song, Zhaoze Li, Xiaoguang Guo, Guanghui Fan
article en
10 citations

Abstract

Traditional mechanical polishing faces significant challenges in achieving ideal surface quality on single crystal diamond (SCD). Chemical mechanical polishing (CMP), combining chemical oxidation and mechanical grinding, offers an effective solution for improving the surface quality of hard and brittle materials. Understanding the material removal characteristics of SCD during CMP is crucial. In this study, the instantaneous contact velocity model of the workpiece and the abrasive particles is established by geometric kinematics, and the instantaneous contact velocity of the abrasive particles at any point on the surface of the workpiece is obtained. Based on the Greenwood and Williamson elastic contact model, the microscopic contact model between the workpiece and the polishing pad is studied, and the effective contact area between the workpiece and the polishing pad and the number of abrasive particles in the effective contact area are obtained. Considering the elastic-plastic deformation in the CMP process of SCD, the micro-contact model between single abrasive particle and workpiece surface is further established, and then the material removal rate (MRR) prediction model of SCD CMP is established. Experimental results reveal the impact of polishing pressure and speed on MRR and surface roughness. The theoretical MRR values align with experimental trends, and the Seagull Optimization Algorithm (SOA) refines the model, reducing the average relative error between theoretical and experimental MRR to 5.98 % and 5.81 %, respectively. The results demonstrate the model's validity. The SCD with near atomic scale ultra-smooth surface is obtained, and the sub-nanometer surface roughness Sa is 0.311 nm. At the same time, the interaction mechanism between chemical oxidation and mechanical removal is investigated through atomic-scale analysis using the ReaxFF molecular dynamics model.

Journal of Materials Research and TechnologyVol. 36
Dalian University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 3%
Advanced Surface Polishing Techniques
6.74
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