WeChat Mini Program
Old Version Features

Microstructure Evolution and Effect on Deuterium Retention in TiC- and ZrC-Doped Tungsten under He+ Ion Irradiation

Metals(2023)

Zhejiang Univ Technol

Cited 4|Views26
Abstract
Combining the advantages of a wet chemical method and spark plasma sintering, carbide-doped materials W-1wt%TiC and W-1wt%ZrC were prepared. Microstructural evolution in W-1wt%TiC and W-1wt%ZrC under irradiation of 5 keV He+ at 600 °C to fluences up to 5.0 × 1021 ions/m2 with ion flux of about 8.8 × 1017 ions/m2s was investigated by transmission electron microscopy (TEM). The dislocation loop number density of W-1wt%TiC was higher than that of W-1wt%ZrC, but the average loop size of the W-1wt%TiC was in average smaller. There were no observable helium bubbles in W-1wt%TiC and W-1wt%ZrC, exhibiting higher radiation resistance to He+ compared to pure W. He+ pre-damaged and undamaged W-1wt%TiC and W-1wt%ZrC samples were irradiated by 5 keV D2+ to estimate the D retention in doped W materials. The irradiation damage impact of He+ on deuterium retention was examined by a method of thermal desorption spectroscopy (TDS). Compared with the undamaged samples, it was illustrated that D2 retention of W-1wt%TiC and W-1wt%ZrC increased after He+ pre-irradiation.
More
Translated text
Key words
carbide,microstructure evolution,irradiation damage,TDS,deuterium retention
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined