基于一阶矩 STEM 图像进行原子计数：方法与可能性
Towards atom counting from first moment STEM images: methodology and possibilities
AI总结：
本文提出基于统计模型和均匀加权最小二乘估计的一阶矩 STEM 图像原子柱投影势定量方法，并证明其较 HAADF STEM 计数更精确，且可用体相晶体模拟库支持不同形状样品的原子计数。
摘要：
通过一项基于模拟的研究，我们开发了一种基于统计模型的定量方法，用于原子分辨率一阶矩扫描透射电子显微镜（STEM）图像。该方法使用均匀加权最小二乘估计量来确定图像的未知结构参数，并分离来自单个原子柱的贡献。通过这种方式，实现了对每个原子柱投影势的定量。由于原子柱的积分投影势与其所含原子数呈线性比例关系，因此它可以作为原子计数的基础。在存在噪声的情况下，我们将基于一阶矩 STEM 成像的原子计数性能与传统 HAADF STEM 的原子计数性能进行了比较。通过这一比较，我们证明了一阶矩 STEM 图像在获得更精确原子计数方面的优势。最后，我们将从楔形样品的一阶矩图像中提取的积分强度与体相晶体的相应数值进行了比较。这些数值之间发现的高度一致性证明了使用体相晶体模拟作为参考库的稳健性。这使得通过与这些库值进行比较，能够对不同形状的样品进行原子计数。
英文摘要：
Through a simulation-based study we develop a statistical model-based quantification method for atomic resolution first moment scanning transmission electron microscopy (STEM) images. This method uses the uniformly weighted least squares estimator to determine the unknown structure parameters of the images and to isolate contributions from individual atomic columns. In this way, a quantification of the projected potential per atomic column is achieved. Since the integrated projected potential of an atomic column scales linearly with the number of atoms it contains, it can serve as a basis for atom counting. The performance of atom counting from first moment STEM imaging is compared to that from traditional HAADF STEM in the presence of noise. Through this comparison, we demonstrate the advantage of first moment STEM images to attain more precise atom counts. Finally, we compare the integrated intensities extracted from first-moment images of a wedge-shaped sample to those values from the bulk crystal. The excellent agreement found between these values proves the robustness of using bulk crystal simulations as a reference library. This enables atom counting for samples with different shapes by comparison with these library values.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
