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Disordered MgB2 Superconductor Critical Temperature Modeling through Regression Trees
Physica C: Superconductivity and its Applications ( IF 1.7 ) Pub Date : 2022-04-29 , DOI: 10.1016/j.physc.2022.1354062
Yun Zhang , Xiaojie Xu

Magnesium boride superconductors are promising candidates in high energy physics applications. These superconductors have several advantages as compared to other high temperature superconductors, such as the absence of weaklinks in grain boundaries, abundant availability of raw materials, simple wire fabrication process, and increased isotropy in microstructure and material performance. Critical temperature, Tc, is the most critical parameter in superconductor characterizations. Various factors have impacts on Tc, including the chemical doping, irradiation, and synthesis conditions. It has been shown that disorders in the crystal structure lead to changes in normal state resistivities and Tc, which are correlated with each other. Here, the regression tree model is developed to predict Tc of disordered magnesium boride superconductors through room temperature resistivities. This modeling approach manifests a high degree of accuracy and stability, contributing to efficient low-cost estimations of critical temperature and understandings of disorder and superconductivity in MgB2 superconductors.



中文翻译:

通过回归树的无序 MgB 2 超导体临界温度建模

硼化镁超导体在高能物理应用中是有希望的候选者。与其他高温超导体相比,这些超导体具有几个优点,例如晶界没有薄弱环节、原材料的丰富可用性、简单的线材制造工艺以及微观结构和材料性能的各向同性增加。临界温度,C,是超导体表征中最关键的参数。各种因素都会影响C,包括化学掺杂、辐照和合成条件。已经表明,晶体结构的紊乱会导致正常状态电阻率和C, 它们相互关联。在这里,开发了回归树模型来预测C通过室温电阻率研究无序硼化镁超导体。这种建模方法表现出高度的准确性和稳定性,有助于对临界温度进行有效的低成本估计,并有助于理解 MgB 中的无序和超导性2超导体。

更新日期:2022-04-29
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