论文标题
FESE中的纳米级电子不均匀性
Nanoscale electronic inhomogeneity in FeSe$_{0.4}$Te$_{0.6}$ revealed through unsupervised machine learning
论文作者
论文摘要
我们报告了FESE $ _ {0.4} $ te $ _ {0.6} $的明显低能纳米级电子不均匀性，这是由于硒和柜员原子的分布，通过无访问的机器学习揭示了。通过无监督的聚类算法，鉴定出硒和柜子富含硒的特征光谱。与这些光谱相关的不均匀性可以清楚地追溯到差分电导率中，并在少数电子伏特的能量尺度以及费米能量的几毫米电伏内检测到。与ARPE相比，这种不均匀性可以与Fermi能量上方的电子样条链接。它与硒和柜子的局部分布直接相关。与超导间隙的大小没有明显的相关性，但是相干峰的高度显示出与检测到该带的强度的显着相关性，因此与局部化学成分。
We report on an apparent low-energy nanoscale electronic inhomogeneity in FeSe$_{0.4}$Te$_{0.6}$ due to the distribution of selenium and tellurium atoms revealed through unsupervised machine learning. Through an unsupervised clustering algorithm, characteristic spectra of selenium- and tellurium-rich regions are identified. The inhomogeneity linked to these spectra can clearly be traced in the differential conductance and is detected both at energy scales of a few electron volts as well as within a few millielectronvolts of the Fermi energy. By comparison with ARPES, this inhomogeneity can be linked to an electron-like band just above the Fermi energy. It is directly correlated with the local distribution of selenium and tellurium. There is no clear correlation with the magnitude of the superconducting gap, however the height of the coherence peaks shows significant correlation with the intensity with which this band is detected, and hence with the local chemical composition.
