论文标题
使用人工神经网络扫描传输电子显微镜中电子光相位差的近实时诊断
Near-real-time diagnosis of electron optical phase aberrations in scanning transmission electron microscopy using an artificial neural network
论文作者
论文摘要
在最先进的扫描传输电子显微镜中优化空间分辨率的关键是能够精确测量和纠正探针形成透镜的电子光畸变的能力。已经提出了几种以最高精度和准确性进行畸变测量和校正的诊断方法，尽管通常以相对较长的收购时间为代价。在这里，我们说明了如何使用人工智能来提供对单个ronchigrams畸变的近实时诊断。表现出的像差测量速度很重要，因为显微镜条件可能会迅速变化，并且对于基于MEMS的硬件校正元件的运行，其内在稳定性比常规电磁镜头的固有稳定性较小。
The key to optimizing spatial resolution in a state-of-the-art scanning transmission electron microscope is the ability to precisely measure and correct for electron optical aberrations of the probe-forming lenses. Several diagnostic methods for aberration measurement and correction with maximum precision and accuracy have been proposed, albeit often at the cost of relatively long acquisition times. Here, we illustrate how artificial intelligence can be used to provide near-real-time diagnosis of aberrations from individual Ronchigrams. The demonstrated speed of aberration measurement is important as microscope conditions can change rapidly, as well as for the operation of MEMS-based hardware correction elements that have less intrinsic stability than conventional electromagnetic lenses.
