Simultaneous analysis of long-pulse laser irradiated plasma-facing materials (PFMs) microstructure and hardness by in-situ laser Opto-ultrasonic dual detection (LOUD)

Abstract

Laser-induced transient heat load events such as edge localized mode (ELM) could induce recrystallization, grain growth, surface degradation, and hardness changes. In this regard, we used the long-pulse laser beams with power densities ranging from 0.165 to 1.909 GW m−2 to simulate transient heat load events for pure tungsten and tungsten heavy alloy (WHA) materials. The investigated samples showed that pure tungsten exhibited a higher recrystallization threshold, steady grain growth, and less surface hardness deterioration than WHA. However, the real-time simultaneous analysis of structural and mechanical properties such as matrix elements, grain size, surface degradation, and hardness changes is challenging in this domain. Therefore, in this study, we utilized a novel laser Opto-ultrasonic dual detection (LOUD) multimodal technique that integrates the benefits of laser-induced breakdown spectroscopy (LIBS) and laser ultrasonic testing (LUT) for simultaneous and in-situ detection of elemental information, grain size and hardness. The preliminary results showed that the variation in hardness is well correlated with the LIBS calibration curve formed by the ionic to atomic line intensity ratio and plasma electron temperature (Te). Despite the different matrix compositions of both samples, the observed increase in the value of Te with hardness justifies the Saha-Eggert relation. The coefficient of determination (R2 ≥ 0.970) value in the calibration curve and Te for hardness evaluation showed the goodness of the fitted model. Furthermore, the correlation of grain size with ultrasonic acoustic attenuation (α) was analyzed by the pulse-echo technique of the ultrasonic waveform for investigated samples. The results showed that grain size is also directly associated with acoustic attenuation with R2 > 0.989. The findings showed that the regression coefficient has a good approximation, which demonstrates the preciseness and potential ability of the LOUD technique for in-situ grain size and hardness analysis.