Zhao Haijun, Li Wenchong, Chen Yue, Xu Chunqiang, Li Bin, Luo Weidong, Qian Dong, Shi Zhixiang
School of Physics, Southeast University, Nanjing, 211189 China.
Information Physics Research Center, Nanjing University of Posts and Telecommunications, Nanjing, 210023 China.
Sci Rep. 2021 Mar 18;11(1):6249. doi: 10.1038/s41598-021-85364-6.
Electrical transport of both longitudinal and transverse directions carries rich information. Mobility spectrum analysis (MSA) is capable of extracting charge information from conductivity tensor, including charge types, concentration and mobilities. Using a numerical method based on maximum entropy principle, i.e., maximum entropy mobility spectrum analysis (MEMSA), mobility spectrum for [Formula: see text]-type PtBi[Formula: see text] is studied. Three hole-pockets and two electron-pockets were found, including a small hole pocket with very high mobility, which is very likely corresponding to Dirac Fermions. Benefiting from our high resolution result, we studied temperature dependence of carrier properties and explained the sign change phenomenon of Hall conductivity. We further compared the results with band structure obtained by our first principle calculation. The present results prove MEMSA is a useful tool of extracting carries' information in recently discovered Iron-based superconductors, and topological materials.
纵向和横向的电输运都承载着丰富的信息。迁移率谱分析（MSA）能够从电导率张量中提取电荷信息，包括电荷类型、浓度和迁移率。使用基于最大熵原理的数值方法，即最大熵迁移率谱分析（MEMSA），研究了[化学式：见原文]-型PtBi[化学式：见原文]的迁移率谱。发现了三个空穴口袋和两个电子口袋，其中包括一个具有非常高迁移率的小空穴口袋，很可能对应于狄拉克费米子。受益于我们的高分辨率结果，我们研究了载流子特性的温度依赖性，并解释了霍尔电导率的符号变化现象。我们进一步将结果与通过第一性原理计算得到的能带结构进行了比较。目前的结果证明，MEMSA是在最近发现的铁基超导体和拓扑材料中提取载流子信息的有用工具。
