Precision and sustainable grinding of SiC through Acidithiobacillus ferrooxidans: enhancing iron-based diamond grinding wheel performance with biological in-process dressing
Source abstract
Abstract
Abrasive grain passivation and bond clogging critically limit the efficiency and process stability of diamond grinding of silicon carbide (SiC). To address these limitations, biological in-process dressing (BID) is integrated into the grinding of metal-bonded diamond wheels to regulate binder removal and abrasive grain protrusion. The dressing performance of biological fluids at different jet velocities was systematically compared with distilled water, focusing on grinding force, material removal depth, and process stability. The results demonstrate that BID significantly enhances overall grinding performance. At a jet velocity of 4 m/s, the grinding force was reduced by 38.15%, while the grinding depth completion rate reached 96.75%, corresponding to a 12.93% increase in actual removal depth relative to distilled water. During prolonged grinding, the deviation between the actual and target removal depths reached approximately 19% for the distilled water group, whereas it remained within 5% under BID conditions, indicating markedly improved process stability. Meanwhile, the microbial metabolite concentration (Fe 3+ ≈ 4.99 g/L) and pH (≈ 2.30) remained stable, indicating sustained microbial activity throughout the grinding process. Although the SiC surfaces after fine grinding exhibited relatively high surface roughness (74.5 - 89.1 nm), this reflects the intrinsic characteristics of the fine grinding stage rather than the final polished surface quality. Overall, BID provides an effective and environmentally benign strategy for enhancing the efficiency and sustainability of diamond grinding for hard and brittle materials.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Surface Polishing Techniques · Advanced machining processes and optimization · Metal Extraction and Bioleaching
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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