Helium retention feature in the boron deposited layer on tungsten substrate by laser-induced breakdown spectroscopy and machine learning approach

Helium retention feature in the boron deposited layer on tungsten substrate by laser-induced breakdown spectroscopy and machine learning approach

ITER is designed for a burning plasma operation in which Tungsten (W) tiles are used as the first wall and diverter materials. Studying He dynamics in B-coated W wall is essential to understanding the effect of boronized plasma-facing components in fusion reactors, as these post-conditioning materia...

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Bibliographic Details
Main Authors: Muhammad Amir Shabbir, Ran Hai, Zhonglin He, Zehua Liu, Fahad Rehman, Xue Bai, Jianping Mu, Ding Wu, Cong Li, Hongbin Ding
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Nuclear Materials and Energy
Subjects:
LIBS
ITER
Helium retention
Boron deposition
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2352179124001832
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