Influence of the grain chemical composition on the fused silica polishing at atomic scale using molecular dynamic simulations
Source abstract
Abstract
The optical glass materials are employed in various industries due to its desirable optical properties. These materials nevertheless require an ultra-smooth surface (Ra <1 nm average roughness) for correctly working. The understanding of the polishing process is essential to get the ultra-smooth surface. The polishing process begins at atomic scale, hindering its study in real time using experimental testing. Molecular dynamic (MD) simulation is powerful tool to assess this process at atom scale in real time. Although the influence of various polishing conditions on polished surface features has been evaluated in the literature, the grain chemical composition influence has not been studied yet. In the present paper, this condition influence on optical glass material polishing at atom scale was assessed using MD simulation. Fused silica was employed as optical glass test pieces, and the abrasive grains used were α-quartz, diamond and α-alumina. Force on the grain was from 0.5 pN to 16.0 pN and cut velocity was 20 m/s. Tersoff potential function method was used to represent the covalent bonds of the materials. The results showed simulations at ≥ 2.0 pN were unstable during polishing due to the mechanical failure. Grain sliding also produced a new microstructure in the glass via the dislocation and deformation of the chemical bonds. The material removal rate (MRR) furthermore was directly proportional to the grain force and the hardness of the grain. The increment in the grain force increased the friction force. Grain chemical composition moreover influenced on the polishing phenomena.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Surface Polishing Techniques · Diamond and Carbon-based Materials Research · Force Microscopy Techniques and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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