本研究利用 electron ptychography 的高剂量效率和像差校正能力，结合第一性原理模拟，成功探测了单层 WS2 原始与缺陷处的电荷转移，并实现了原子结构与电荷转移的独立分析。
摘要：
原子尺度的电子电荷转移能够揭示有关化学键的基本信息，但与原子结构相比，对其直接成像要困难得多。电荷密度主要由原子核主导，化学键仅引起微小的扰动。因此，探测由化学键引起的任何变化需要比成像结构和总电荷密度更高的灵敏度。在此，我们利用 electron ptychography 的高剂量效率及其校正透镜像差的能力，达到了在原始和含缺陷的单层 WS\ extsubscript{2} 中探测电荷转移所需的灵敏度。实验结果与第一性原理图像模拟取得了极好的一致性，其中热漫散射通过基于密度泛函理论的有限温度分子动力学进行了显式建模。我们使用的聚焦探针叠层成像配置还提供了同时收集环形暗场信号的重要能力，该信号可以明确地用原子结构和原子的化学同一性来解释，而独立于电荷转移。我们的结果既展示了叠层重建的强大能力，也说明了定量精确的模拟对辅助其解释的重要性。
英文摘要：
Electronic charge transfer at the atomic scale can reveal fundamental information about chemical bonding, but is far more challenging to directly image than the atomic structure. The charge density is dominated by the atomic nuclei, with bonding causing only a small perturbation. Thus detecting any change due to bonding requires a higher level of sensitivity than imaging structure and the overall charge density. Here we achieve the sensitivity required to detect charge transfer in both pristine and defected monolayer WS\textsubscript{2} using the high dose efficiency of electron ptychography and its ability to correct for lens aberrations. Excellent agreement is achieved with first-principles image simulations including where thermal diffuse scattering is explicitly modeled via finite-temperature molecular dynamics based on density functional theory. The focused-probe ptychography configuration we use also provides the important ability to concurrently collect the annular dark-field signal, which can be unambiguously interpreted in terms of the atomic structure and chemical identity of the atoms, independently of the charge transfer. Our results demonstrate both the power of ptychographic reconstructions and the importance of quantitatively accurate simulations to aid their interpretation.
Scanning transmission electron microscopy (STEM) is the most widespread adopted tool for atomic scale characterization of two-dimensional (2D) materials. Many 2D materials remain susceptible to electron beam damage, despite the standardized practice to reduce the beam energy from 200 keV to 80 or 60 keV. Although, all elements present can be detected by atomic electrostatic potential imaging using integrated differential phase contrast (iDPC) STEM or electron ptychography, capturing dynamics with atomic resolution and enhanced sensitivity has remained a challenge. Here, by using iDPC-STEM, we …
Real-Time Atomic-Resolution Electron Phase Imaging without Probe Calibration via Ptychography-Supervised Learning
Fudan University（复旦大学）；National Tsing Hua University（国立清华大学）；National Center for Instrumentation Research, National Institutes of Applied Research（国家应用研究院国家仪器研究中心）；Institute for Infocomm Research, A*STAR（新加坡科技研究局资讯通信研究院）；The University of Sydney（悉尼大学）
From ripples to defects, edges and grain boundaries, the 3D atomic structure of 2D materials is critical to their properties. However the damage inflicted by conventional 3D analysis precludes its use with fragile 2D materials, particularly for the analysis of local defects. Here we dramatically increase the potential for precise local 3D atomic structure analysis of 2D materials, with both greatly improved dose efficiency and sensitivity to light elements. We demonstrate light atoms can now be located in complex 2D materials with picometer precision at doses 30 times lower than previously pos…
The electron-hole symmetry in graphene monolayer, which is analogous to the inherent symmetric structure between electrons and positrons of the Universe, plays a crucial role in the chirality and chiral tunnelling of massless Dirac fermions. Here we demonstrate that both strain and charged-defect scattering could break this symmetry dramatically in graphene monolayer. In our experiment, the Fermi velocities of electrons and holes are measured directly through Landau level spectroscopy. In strained graphene with lattice deformation and curvature, the and are measured as 1.2 x 106 m/s and 1.02 x…
Measuring degeneracy and broken-symmetry states of a system at nanoscale requires extremely high energy and spatial resolution, which has so far eluded direct observation. Here, we realize measurement of the degeneracy and subtle broken-symmetry states of graphene at nanoscale for the first time. By using edge-free graphene quantum dots, we are able to measure valley splitting and valley-contrasting spin splitting of graphene at the single-electron level. Our experiments detect large valley splitting around atomic defects of graphene due to the coexistence of sublattice symmetry breaking and t…
We hypothesize that avalanche-like releases of energy accumulated in materials due to radioactivity and other sources can produce parasitic background in dark matter particles searches and low-energy threshold detectors. We explore this hypothesis using published data on low-energy background in detectors and available condensed-matter physics information on excitations, defects, and energetic molecules which can be present in materials.
Aberration-corrected optics have made electron microscopy at atomic-resolution a widespread and often essential tool for nanocharacterization. Image resolution is dominated by beam energy and the numerical aperture of the lens (α), with state-of-the-art reaching ~0.47 Å at 300 keV. Two-dimensional materials are imaged at lower beam energies to avoid knock-on damage, limiting spatial resolution to ~1 Å. Here, by combining a new electron microscope pixel array detector with the dynamic range to record the complete distribution of transmitted electrons and full-field ptychography to recover phase…
Oak Ridge National Laboratory（橡树岭国家实验室）；University of Michigan-Ann Arbor（密歇根大学安娜堡分校）；Hope College（霍普学院）；University of Puerto Rico at Mayagüez（波多黎各大学马亚圭斯分校）
Electron microscopy is widely used to explore defects in crystal structures, but human detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalable to large numbers of images or real-time analysis. In this work, we discuss the application of machine learning approaches to find the location and geometry of different defect clusters in irradiated steels. We show that a deep learning based Faster R-CNN analysis system has a performance comparable to human analysis with relatively small training data sets. This study proves the promising ability to apply deep lear…
Defect Detection in Magnetic Systems Using U-Net and Statistical Measures
University of Duisburg-Essen（杜伊斯堡-埃森大学）；Massachusetts General Hospital（马萨诸塞州总医院）；University of Heidelberg（海德堡大学）；Technical University of Darmstadt（达姆施塔特工业大学）
University of Wisconsin-Madison（威斯康星大学麦迪逊分校）；Oak Ridge National Laboratory（橡树岭国家实验室）；University of Oxford（牛津大学）；University of Michigan - Ann Arbor（密歇根大学安娜堡分校）
Videos captured using Transmission Electron Microscopy (TEM) can encode details regarding the morphological and temporal evolution of a material by taking snapshots of the microstructure sequentially. However, manual analysis of such video is tedious, error-prone, unreliable, and prohibitively time-consuming if one wishes to analyze a significant fraction of frames for even videos of modest length. In this work, we developed an automated TEM video analysis system for microstructural features based on the advanced object detection model called YOLO and tested the system on an in-situ ion irradi…
