This experiment employed laser-induced breakdown spectroscopy (LIBS) to enhance the accuracy of depth profiling in plasma-facing materials, paving the way for improved understanding of plasma-wall interactions in nuclear fusion reactors.
Researchers from Dalian University of Technology in China have conducted a comprehensive experimental and modeling study on the depth profiling of multilayer deposition materials using laser-induced breakdown spectroscopy (LIBS) (1). Their work, published in the journal Spectrochimica Acta Part B: Atomic Spectroscopy, sheds light on the intricate patterns of erosion and deposition occurring in the plasma-facing materials (PFMs) of magnetic confinement fusion devices.
Plasma-wall interaction (PWI) is a critical aspect of nuclear fusion research, and understanding the behavior of deposition layers on PFMs is key to advancing this field. LIBS has emerged as an effective remote monitoring method for investigating these layers, but challenges arise in accurately distinguishing interfaces between deposition layers and substrates. The accuracy of measuring the deposition layer thickness is pivotal for precise PWI research.
PWI is a critical aspect of nuclear fusion research because it directly impacts the performance and success of fusion reactors. The interaction between the hot plasma and the surrounding materials forming the reactor walls can lead to erosion and damage, posing significant challenges in maintaining the integrity of the containment vessel. Understanding and mitigating PWI is crucial for developing materials that can withstand the extreme conditions of a fusion reactor, ensuring sustained and efficient fusion reactions while extending the operational lifespan of the reactor.
This experiment involved depth profiling of multilayer samples with nickel (Ni) layers on copper (Cu) using LIBS with a nanosecond-pulse laser. The conditions mimicked those in a nuclear fusion device, with the experiment conducted under a pressure of 5 × 10−5 mbar. The study aimed to improve the accuracy of LIBS depth profiling, addressing challenges associated with the identification of interfaces in multilayer materials.
To enhance the precision of LIBS depth analysis, the researchers developed a two-dimensional model. This model incorporated factors such as the laser beam profile and interface roughness to reconstruct and predict the elemental depth profile distribution of Ni-Cu multilayer materials. The correlation coefficients between the experimental and modeling data exceeded 0.99, indicating a high level of accuracy in the predictions.
A key innovation introduced in the study was a locating approach for interface identification based on the model's predictions. The relative errors of all Ni layer thicknesses were found to be less than 5.1%, showcasing the feasibility and accuracy of the developed model. This approach holds promise for improving the precision of LIBS depth profiling in layer thickness analysis, thereby advancing its application in in situ LIBS diagnosis for PWI research.
The results underscore the significance of the two-dimensional numerical model in refining LIBS depth profiling. By overcoming challenges associated with interface identification and layer thickness measurement, this research contributes to the broader goal of enhancing our understanding of plasma-wall interaction in nuclear fusion devices. The study's success in predicting and locating interfaces opens new avenues for the practical application of LIBS in the field of PWI research, bringing us closer to unlocking the full potential of this diagnostic technique in plasma-facing material analysis.
This research not only provides valuable insights for industry experts but also contributes to the accessibility of scientific knowledge, aligning with the broader goal of driving engagement and interest from the general public in the field of nuclear fusion research.
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(1) Liu, S.; Li, C.; Wu, H.; et al. Experimental and Model Study of LIBS Depth Profile for Multilayer Deposition Materials. Spectrochim. Acta, Part B 2023, 209, 106783. DOI: 10.1016/j.sab.2023.106783