Bio-inspired involute groove pad textures for enhanced material removal and surface quality in SiC chemical mechanical polishing

Optimizing polishing pad texture is critical for the chemical mechanical polishing (CMP) of hard materials like silicon carbide (SiC). This study introduces a novel bio-inspired involute groove design for polishing pads, drawing inspiration from the nautilus chamber. Based on reactor theory and a modified Preston's equation, the influence of groove geometry on slurry dynamics and contact pressure was investigated. Three involute groove textures with varying base circle radii of 40, 50, and 60 mm were systematically analyzed through fluid dynamics and stress simulations. Simulations predicted that the 60 mm radius texture (LP-C) yields the most uniform slurry flow and a desirable Gaussian-like pressure distribution. Subsequent CMP experiments on SiC substrates validated these findings; the 60 mm radius pad enhanced the material removal rate by at least 18.87 % and reduced surface roughness by 15.10 % compared to the other designs. These results provide a validated design strategy for advanced pad textures, demonstrating that optimizing involute groove geometry is a highly effective approach to improving CMP performance for challenging ceramic materials. • Theoretical analysis of Preston's equation revealed the significant impact of surface grooves on CMP results. • Flow field simulations evaluated the slurry flow and force uniformity with different base circle radii during CMP. • The stress distribution simulation optimized the Gaussian-like material removal pattern of involute grooves. • SiC polishing experiments validated the machining efficiency and quality of various textured-pads.

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Publication Details

Journal
Journal of Materials Research and Technology
Published
2025-09-23
DOI
https://doi.org/10.1016/j.jmrt.2025.09.172
Citations
1
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
5.34
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article

Bio-inspired involute groove pad textures for enhanced material removal and surface quality in SiC chemical mechanical polishing

1 citations
Journal of Materials Research and Technology
Computational and Text Analysis Methods
5.34
article

Bio-inspired involute groove pad textures for enhanced material removal and surface quality in SiC chemical mechanical polishing

article en
1 citations

Abstract

Optimizing polishing pad texture is critical for the chemical mechanical polishing (CMP) of hard materials like silicon carbide (SiC). This study introduces a novel bio-inspired involute groove design for polishing pads, drawing inspiration from the nautilus chamber. Based on reactor theory and a modified Preston's equation, the influence of groove geometry on slurry dynamics and contact pressure was investigated. Three involute groove textures with varying base circle radii of 40, 50, and 60 mm were systematically analyzed through fluid dynamics and stress simulations. Simulations predicted that the 60 mm radius texture (LP-C) yields the most uniform slurry flow and a desirable Gaussian-like pressure distribution. Subsequent CMP experiments on SiC substrates validated these findings; the 60 mm radius pad enhanced the material removal rate by at least 18.87 % and reduced surface roughness by 15.10 % compared to the other designs. These results provide a validated design strategy for advanced pad textures, demonstrating that optimizing involute groove geometry is a highly effective approach to improving CMP performance for challenging ceramic materials. • Theoretical analysis of Preston's equation revealed the significant impact of surface grooves on CMP results. • Flow field simulations evaluated the slurry flow and force uniformity with different base circle radii during CMP. • The stress distribution simulation optimized the Gaussian-like material removal pattern of involute grooves. • SiC polishing experiments validated the machining efficiency and quality of various textured-pads.

Journal of Materials Research and TechnologyVol. 39
Chang'an University (CN), Beijing Machine Tool Research Institute (CN), Xi'an Jiaotong University (CN)
Openalex Percentile: Top 3%
Computational and Text Analysis Methods
5.34
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