研究目的
To solve the problems of the FAWS technology in the photovoltaic industry by presenting a novel fixed-free abrasive combined wire sawing (FFACWS) technology for cutting PV polycrystalline silicon, which aims to remove or greatly reduce the wire marks and amorphous layer on the slice surface.
研究成果
The FFACWS technology effectively combines the advantages of the FAWS and the LAWS, removing or greatly reducing the wire marks and ductile grooves on the slice surface. The surface roughness and kerf loss are influenced by the size and mass fraction of SiC abrasives, workpiece feed speed, and wire speed. The study provides a better combination of process parameters for achieving desired surface morphology and roughness.
研究不足
The study is limited to the range of processing parameters investigated, and the effect of SiC abrasives size is related to the matching of the protruding height of the fixed abrasives on the wire surface.
1:Experimental Design and Method Selection
The study employs a single-factor and orthogonal experimental design to investigate the effect of size and mass fraction of SiC abrasives in the slurry, workpiece feed speed, and wire speed on the surface morphology, roughness, and kerf loss of polycrystalline silicon slices.
2:Sample Selection and Data Sources
The processed polycrystalline silicon samples are of size 8 mm × 10 mm × 30 mm. The surface morphology, surface roughness, and kerf loss are measured and analyzed.
3:List of Experimental Equipment and Materials
Reciprocating diamond wire saw, electroplated diamond wire, SiC abrasives, polyethylene glycol (PEG300) solution.
4:Experimental Procedures and Operational Workflow
The wire sawing process involves spraying slurry with loose SiC abrasives into the sawing area. The surface morphology is observed using an Olympus precision optical microscope, and surface roughness is measured using a surface roughness measuring instrument.
5:Data Analysis Methods
The effect of process parameters on surface morphology and roughness is analyzed, and the mathematical model of surface roughness is established by regression of orthogonal test results.
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