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Visual detection of defects in carbon steel using magnetic nanoemulsions: Effect of stabilizing moieties on the defect detection sensitivity

[Display omitted] •Visual detection of defects reported in carbon steel using magnetic nanoemulsions.•Visually discernible colour contrast observed over the defect regions.•Location and widths of the defects quantified from intensity profiling.•Nature of the stabilizing moieties influence defect det...

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Published in:Sensors and actuators. A. Physical. 2020-10, Vol.314, p.112220, Article 112220
Main Authors: Nandy, Manali, Lahiri, B.B., Philip, John
Format: Article
Language:English
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Summary:[Display omitted] •Visual detection of defects reported in carbon steel using magnetic nanoemulsions.•Visually discernible colour contrast observed over the defect regions.•Location and widths of the defects quantified from intensity profiling.•Nature of the stabilizing moieties influence defect detection sensitivity.•Electrostatically stabilized emulsions exhibited superior detection sensitivity. The defect detection sensitivity of magnetic nanoemulsions (MNEs) stabilized with different functional moieties such as anionic surfactant, co-polymer and a weak polyelectrolyte is reported here. The visually discernible colour contrast over the defective regions and the corresponding Bragg’s reflection, originating from the linear chain-like structures formed by the leakage magnetic flux are experimentally measured and compared with the theoretically obtained profiles. The linear chain-like structures, formed by the MNEs, are also visualized using atomic force and optical phase contrast microscopy studies. Defect detection studies are carried out on carbon steel samples with artificially made defects (rectangular slots) and the variations in defect detection sensitivity (colour contrast) are assessed under different stabilizing moieties. It is found that the electrostatically stabilized MNEs exhibited superior defect detection sensitivity, as compared to the polymeric stabilizers. The microscopic origin for sensitivity variations, is studied by measuring the inter-droplet forces and hydrodynamic diameter. The inter-droplet force measurements show that the lower decay length is better for improving the defect detection sensitivity. Through image processing and intensity profiling, the defect widths are accurately estimated, which are in good agreements with the actual defect dimensions. The intensity profiles are found to vary linearly with the defect depth for the shallower defects. These results are useful to tailor MNEs with superior defect detection sensitivity and long-term stability towards development of MNE-based thin film sensors for automated and superior defect detection strategies.
ISSN:0924-4247
1873-3069
DOI:10.1016/j.sna.2020.112220