Multimodal characterization methodology of non-metallic inclusions in metal materials using laser-induced breakdown...

The determination of non-metallic inclusion with varying chemical compositions and microstructure in metal materials is helpful for improvement and development of internal quality and property. The recently proposed laser-induced breakdown spectroscopy (LIBS) method can rapidly identify simple diatomic inclusions and determine inclusion equivalent diameter. However, due to the lack of steel-matrix inclusion standard samples, the LIBS scanning measurements typically combined with scanning electron microscopy coupled with energy dispersive spectrometry (SEM-EDS) and statistical methods, which makes this method unable to conduct independent measurements.

In this paper, we propose a LIBS precision-targeted analysis methodology for multimodal characterization of chemical composition and microstructure for inclusions. A three-dimensional high-precision motion platform system and a microscopic imaging system were developed and constructed on the LIBS detection platform to achieve precise targeted positioning and measurement. The experimental conditions, including the relative distance between the microscope and LIBS, and the excitation mode of inclusions, were systematically optimized to improve the spectral quality and detection limits of LIBS precision-targeted analysis. More importantly, for the identification and quantitative analysis of complex and varied inclusions composed of varying element contents, univariate steel-matrix standard samples with controlled inclusions were designed and prepared. The concentration-spectral intensity calibration curves for Mn, Al, Ca, Mg, Ti, and Si elements were established, and the results were validated by conducting SEM-EDS.

This new method overcomes shortcomings of LIBS undirected scanning, significantly improving analytical efficiency and throughput, while opening the way for the high-throughput characterization of non-metallic inclusions in large-sized samples. This technique provided an effective means for the complex inclusion composition identification and cleanness process evaluation of metal material samples and thus for research and improvement of material property.