Yang Ye , Ziqin Yang , Shuai Wu , Jianpeng Li , Tao Liu , Guangze Jiang , Hangxu Li , Zepeng Jiang , Jiaqi Liu , Yuan He , Wenlong Zhan
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引用次数: 0
Abstract
A computational model is developed to predict the nitrogen concentration profile within Nb utilized in superconducting radio-frequency (SRF) accelerators. This model incorporates variations in the sticking coefficient of nitrogen during the adsorption process on the Nb surface, along with the impact of nitride formation resulting from the reaction between Nb and nitrogen. The conclusions drawn from this model are compared with the outcomes of vertical test experiments. The computed results indicate that exhibiting a significant nitrogen doping effect is achieved when the nitrogen concentration is approximately 1E25 atom/m under various nitrogen doping recipes. This study enhances the understanding of the nitrogen doping process and enables the rapid determination of the optimal subsequent material removal thickness for various experimental recipes.
期刊介绍:
Physica C (Superconductivity and its Applications) publishes peer-reviewed papers on novel developments in the field of superconductivity. Topics include discovery of new superconducting materials and elucidation of their mechanisms, physics of vortex matter, enhancement of critical properties of superconductors, identification of novel properties and processing methods that improve their performance and promote new routes to applications of superconductivity.
The main goal of the journal is to publish:
1. Papers that substantially increase the understanding of the fundamental aspects and mechanisms of superconductivity and vortex matter through theoretical and experimental methods.
2. Papers that report on novel physical properties and processing of materials that substantially enhance their critical performance.
3. Papers that promote new or improved routes to applications of superconductivity and/or superconducting materials, and proof-of-concept novel proto-type superconducting devices.
The editors of the journal will select papers that are well written and based on thorough research that provide truly novel insights.