Sasaki Yusei, Yamamoto Kazuo, Anada Satoshi, Yoshimoto Noriyuki
Graduate School of Science and Engineering, Iwate University, 4-3-5 Ueda, Morioka, Iwate 020-8551, Japan.
Nanostructures Research Laboratory, Japan Fine Ceramics Center, 2-4-1 Mutsuno, Atsuta-ku, Nagoya, Aichi 456-8587, Japan.
Microscopy (Oxf). 2023 Nov 24;72(6):485-493. doi: 10.1093/jmicro/dfad019.
To improve the performance of organic light-emitting diodes (OLEDs), it is essential to understand and control the electric potential in the organic semiconductor layers. Electron holography (EH) is a powerful technique for visualizing the potential distribution with a transmission electron microscope. However, it has a serious issue that high-energy electrons may damage the organic layers, meaning that a low-dose EH is required. Here, we used a machine learning technique, three-dimensional (3D) tensor decomposition, to denoise electron interference patterns (holograms) of bilayer OLEDs composed of N,N'-di-[(1-naphthyl)-N,N'-diphenyl]-(1,1'-biphenyl)-4,4'-diamine (α-NPD) and tris-(8-hydroxyquinoline)aluminum (Alq3), acquired under a low-dose rate of 130 e- nm-2 s-1. The effect of denoising on the phase images reconstructed from the holograms was evaluated in terms of both the phase measurement error and the peak signal-to-noise ratio. We achieved a precision equivalent to that of a conventional measurement that had an exposure time 60 times longer. The electric field within the Alq3 layer decreased as the cumulative dose increased, which indicates that the Alq3 layer was degraded by the electron irradiation. On the basis of the degradation of the electric field, we concluded that the tolerance dose without damaging the OLED sample is about 1.7 × 105 e- nm-2, which is about 0.6 times that of the conventional EH. The combination of EH and 3D tensor decomposition denoising is capable of making a time series measurement of an OLED sample without any effect from the electron irradiation.
为了提高有机发光二极管（OLED）的性能，了解并控制有机半导体层中的电势至关重要。电子全息术（EH）是一种利用透射电子显微镜可视化电势分布的强大技术。然而，它存在一个严重问题，即高能电子可能会损坏有机层，这意味着需要低剂量的电子全息术。在此，我们使用了一种机器学习技术——三维（3D）张量分解，对由N，N'-二[（1-萘基）-N，N'-二苯基] -（1，1'-联苯）-4，4'-二胺（α-NPD）和三（8-羟基喹啉）铝（Alq3）组成的双层OLED在130 e- nm-2 s-1的低剂量率下获取的电子干涉图案（全息图）进行去噪。从全息图重建的相位图像的去噪效果通过相位测量误差和峰值信噪比进行评估。我们实现了与曝光时间长60倍的传统测量相当的精度。随着累积剂量的增加，Alq3层内的电场降低，这表明Alq3层因电子辐照而降解。基于电场的降解，我们得出结论，不损坏OLED样品的耐受剂量约为1.7×105 e- nm-2，约为传统电子全息术的0.6倍。电子全息术与3D张量分解去噪的结合能够对OLED样品进行时间序列测量，而不受电子辐照的任何影响。
