Atomic Columns Research Articles

Towards atom counting from first moment STEM images: Methodology and possibilities

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 potential 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.

Comparison of terrestrial exospheric hydrogen 3D distributions at solar minimum and maximum using TWINS Lyman-α observations

Remote sensing observations of far-ultraviolet (FUV) emissions have been used to estimate 3D neutral hydrogen (H) density models of the terrestrial exosphere under solar minimum (2008) and solar maximum (2013 and 2015) conditions. Specifically, we used Lyman-alpha (Lyman-α, FUV at 121.6 nm) radiance data acquired by the Lyman-alpha detectors (LADs) onboard NASA’s TWINS satellites, collected over several days for each of the 3 years to provide sufficient coverage of the exospheric region. The datasets included Lyman-α measurements taken only above Earth radii (Re) of 3.75, assumed to be the optically thin region of the exosphere, where the measured Lyman-α intensity along a line of sight (LOS) is linearly proportional to the atomic hydrogen column density. Based on the calibration using multiple UV-bright stars, a significant decrease in TWINS1 LAD1/2 sensitivities was found for 2013 (LAD2 ∼1/2, LAD ∼1/3) and 2015 (LAD2 ∼1/3, LAD ∼1/7) compared to 2008. The calibration uncertainty was derived to be, on average, 5%. We estimated the 3D global hydrogen density distributions from these radiance data using two different tomographic inversion methods: first, a parametric fitting method based on a spherical harmonic function of order 3 and second, a high degree-of-freedom retrieval approach to validate our retrievals of H density. Both inversion methods consistently incorporate the effects of Lyman-α absorption within the exosphere and Lyman-α re-emission from Earth’s albedo. Our results reveal that H densities during solar maximum conditions are, on average, 30%–40% higher than those during solar minimum. All models showed a high concentration of atomic H on the dayside and nightside near the Sun–Earth line, which determines a nose/geotail structure consistent with theoretical effects from the solar radiation pressure. Furthermore, we identified that H-density enhancements during solar maximum with respect to solar minimum conditions occur at mid-to-high latitudes, particularly on the dusk side, while no significant enhancement seems to occur near the dayside nose.

Obtaining 3D Atomic Reconstructions from Electron Microscopy Images Using a Bayesian Genetic Algorithm: Possibilities, Insights, and Limitations.

The Bayesian genetic algorithm (BGA) is a powerful tool to reconstruct the 3D structure of mono-atomic single-crystalline metallic nanoparticles imaged using annular dark field scanning transmission electron microscopy. The number of atoms in a projected atomic column in the image is used as input to obtain an accurate and atomically precise reconstruction of the nanoparticle, taking prior knowledge and the finite precision of atom counting into account. However, as the number of parameters required to describe a nanoparticle with atomic detail rises quickly with the size of the studied particle, the computational costs of the BGA rise to prohibitively expensive levels. In this study, we investigate these computational costs and propose methods and control parameters for efficient application of the algorithm to nanoparticles of at least up to 10 nm in size.

Electromagnetically induced transparency using selective reflection radiation from a thin Rb vapor cell

We have investigated electromagnetically induced transparency (EIT) in the spectrum of selective reflection at the interface between Rb atomic vapor and a dielectric nanocell window made of technical sapphire. Two types of spectroscopic cells were used: a nanocell with atomic vapor column thicknesses ranging from 150 to 1200 nm, and a 50μm-thick microcell. We have compared electromagnetically induced transparency resonances in a Λ-type atomic system observed using selective reflection as the probe radiation and/or transmission radiation. It was demonstrated that for thicknesses below 1000 nm, the selective reflection technique is more advantageous. Notably, at a thickness of ∼150nm, electromagnetically induced transparency resonance is clearly observed using selective reflection, while it is nearly absent when using transmission radiation. This enables the realization of ∼150nm spatial resolution in mapping a strongly inhomogeneous magnetic field of 3.3 G/μm.

Current opinion on the prospect of mapping electronic orbitals in the transmission electron microscope: State of the art, challenges and perspectives.

The concept of electronic orbitals has enabled the understanding of a wide range of physical and chemical properties of solids through the definition of, for example, chemical bonding between atoms. In the transmission electron microscope, which is one of the most used and powerful analytical tools for high-spatial-resolution analysis of solids, the accessible quantity is the local distribution of electronic states. However, the interpretation of electronic state maps at atomic resolution in terms of electronic orbitals is far from obvious, not always possible, and often remains a major hurdle preventing a better understanding of the properties of the system of interest. In this review, the current state of the art of the experimental aspects for electronic state mapping and its interpretation as electronic orbitals is presented, considering approaches that rely on elastic and inelastic scattering, in real and reciprocal spaces. This work goes beyond resolving spectral variations between adjacent atomic columns, as it aims at providing deeper information about, for example, the spatial or momentum distributions of the states involved. The advantages and disadvantages of existing experimental approaches are discussed, while the challenges to overcome and future perspectives are explored in an effort to establish the current state of knowledge in this field. The aims of this review are also to foster the interest of the scientific community and to trigger a global effort to further enhance the current analytical capabilities of transmission electron microscopy for chemical bonding and electronic structureanalysis.

Investigation of the Octahedral Network Structure in Formamidinium Lead Bromide Nanocrystals by Low-Dose Scanning Transmission Electron Microscopy.

Metal halide perovskites (MHP) are highly promising semiconductors. In this study, we focus on FAPbBr3 nanocrystals, which are of great interest for green light-emitting diodes. Structural parameters significantly impact the properties of MHPs and are linked to phase instability, which hampers long-term applications. Clearly, there is a need for local and precise characterization techniques at the atomic scale, such as transmission electron microscopy. Because of the high electron beam sensitivity of MHPs, these investigations are extremely challenging. Here, we applied a low-dose method based on four-dimensional scanning transmission electron microscopy. We quantified the observed elongation of the projections of the Br atomic columns, suggesting an alternation in the position of the Br atoms perpendicular to the Pb-Br-Pb bonds. Together with molecular dynamics simulations, these results remarkably reveal local distortions in an on-average cubic structure. Additionally, this study provides an approach to prospectively investigating the fundamental degradation mechanisms of MHPs.

Orthorhombic Polar Phase in Sodium Niobate Nanoribbons.

Ferroelectric materials exhibit switchable spontaneous polarization below Curie's temperature, driven by octahedral distortions and rotations, as well as ionic displacements. The ability to manipulate polarization coupled with persistent remanence, drives diverse applications, including piezoelectric devices. In the last two decades, nanoscale exploration has unveiled unique material properties influenced by morphology, including the capability to manipulate polarization, patterns, and domains. This paper focuses on the characterization of nanometric sodium niobate (SN) synthesized from metallic niobium through alkali hydrothermal treatment, utilizing electron microscopy techniques, including high-resolution differential phase contrast (DPC) in scanning transmission electron microscopy (STEM). The material exhibits a nanoribbon structure forming a tree root-like network. The study identifies crystallographic phase, atomic columns displacement directions, and surface features, such as exposed planes and the absence of particular atomic columns. The high sensitivity of integrated DPC images proves crucial in overcoming observational challenges in other STEM modes. These observations are essential for potential applications in electronic, photocatalytic, and chemical reaction contexts.

Localization and segmentation of atomic columns in supported nanoparticles for fast scanning transmission electron microscopy

To accurately capture the dynamic behavior of small nanoparticles in scanning transmission electron microscopy, high-quality data and advanced data processing is needed. The fast scan rate required to observe structural dynamics inherently leads to very noisy data where machine learning tools are essential for unbiased analysis. In this study, we develop a workflow based on two U-Net architectures to automatically localize and classify atomic columns at particle-support interfaces. The model is trained on non-physical image simulations, achieves sub-pixel localization precision, high classification accuracy, and generalizes well to experimental data. We test our model on both in situ and ex situ experimental time series recorded at 5 frames per second of small Pt nanoparticles supported on CeO2(111). The processed movies show sub-second dynamics of the nanoparticles and reveal site-specific movement patterns of individual atomic columns.

Electromagnetically induced transparency with magnetically induced ΔF=0,mF=0→mF=0 probe transition

Interest in magnetically induced (MI) transitions of alkali metal atoms is caused by the fact that their intensities can exceed the intensities of ‘regular’ atomic transitions in a wide magnetic field range (200–4000 G). The goal of this work was to form and study, for the first time, electromagnetically induced transparency (EIT) resonance in a strong magnetic field using probe radiation tuned to |Fg=F,mF=0⟩→|Fe=F,mF=0⟩ MI transition, which is forbidden in zero magnetic fields. Two narrow-band linearly polarized cw diode lasers were used to form EIT resonance on a Λ-type system of a Cs atomic D2 line in a strong transverse magnetic field (up to 1000 G). The resonance was formed in a Cs atomic vapor nanocell with an atomic vapor column thickness of 850 nm.

Total Third-Degree Variation for Noise Reduction in Atomic-Resolution STEM Images.

Scanning Transmission Electron Microscopy (STEM) enables direct determination of atomic arrangements in materials and devices. However, materials such as battery components are weak for electron beam irradiation and low electron doses are required to prevent beam-induced damages. Noise removal is thus essential for precise structural analysis of electron beam sensitive materials at atomic resolution. Total square variation (TSV) regularization is an algorithm that exhibits high noise removal performance. However, the use of the TSV regularization term leads to significant image blurring and intensity reduction. To address these problems, we here propose a new approach adopting L2 norm regularization based on higher-order total variation. An atomic-resolution STEM image can be approximated as a set of smooth curves represented by quadratic functions. Since the third-degree derivative of any quadratic function is 0, total third-degree variation (TTDV) is suitable for a regularization term. The application of TTDV for denoising the atomic-resolution STEM image of CaF2 observed along the [001] zone axis is shown, where we can clearly see the Ca and F atomic columns without compromising image quality.

Defect Density and Atomic Defect Recognition in the Middle Layer of a Trilayer MoS2 Stack.

Molybdenum disulfide (MoS2) is one of the most intriguing two-dimensional materials, and moreover, its single atomic defects can significantly alter the properties. These defects can be both imaged and engineered using spherical and chromatic aberration-corrected high-resolution transmission electron microscopy (CC/CS-corrected HRTEM). In a few-layer stack, several atoms are vertically aligned in one atomic column. Therefore, it is challenging to determine the positions of missing atoms and the damage cross-section, particularly in the not directly accessible middle layers. In this study, we introduce a technique for extracting subtle intensity differences in CC/CS-corrected HRTEM images. By exploiting the crystal structure of the material, our method discerns chalcogen vacancies even in the middle layer of trilayer MoS2. We found that in trilayer MoS2 the middle layer's damage cross-section is about ten times lower than that in the monolayer. Our findings could be essential for the application of few-layer MoS2 in nanodevices.

Moiré fringe imaging of heterostructures by scanning transmission electron microscopy

A heterostructured crystalline bilayer specimen is known to produce moiré fringes (MFs) in the conventional transmission electron microscopy (TEM). However, the understanding of how these patterns form in scanning transmission electron microscopy (STEM) remains limited. Here, we extended the double-scattering model to establish the imaging theory of MFs in STEM for a bilayer sample and applied this theory to successfully explain both experimental and simulated STEM images of a perovskite PbZrO3/SrTiO3 system. Our findings demonstrated that the wave vectors of electrons exiting from Layer-1 and their relative positions with the atomic columns of Layer-2 should be taken into account. The atomic column misalignment leads to a faster reduction in the intensity of the secondary scattering beam compared to the single scattering beam as the scattering angle increases. Consequently, the intensity distribution of MFs in the bright field (BF)-STEM can be still described as the product of two single atomic images. However, in high angle annular dark field (HAADF)-STEM, it is approximately described as the superposition of the two images. Our work not only fills a knowledge gap of MFs in incoherent imaging, but also emphasizes the importance of the coherent scattering restricted by the real space when analyzing the HAADF-STEM imaging.

Crystal plane orientation-dependent surface atom diffusion in sub-10-nm Au nanocrystals.

Surface atom diffusion is a ubiquitous phenomenon in nanostructured metals with ultrahigh surface-to-volume ratios. However, the fundamental atomic mechanism of surface atom diffusion remains elusive. Here, we report in situ atomic-scale observations of surface pressure-driven atom diffusion in gold nanocrystals at room temperature using high-resolution transmission electron microscopy with a high-speed detection camera. The topmost layer of atoms on (001) plane initially diffuse in a column-by-column manner. As diffusion proceeds, the remaining atomic columns collectively inject into adjacent underlayer, accompanied by nucleation of a surface dislocation. In comparison, atoms on (111) plane directly diffuse to the base without collective injection. Quantitative calculations indicate that these crystal plane orientation-dependent atom diffusion behaviors contribute to the larger diffusion coefficient of (111) plane compared to (001) plane in addition to the effect of diffusion activation energy. Our findings provide valuable insights into atomic mechanisms of diffusion-dominant morphology evolution of nanostructured metals and guide the design of nanostructured materials with enhanced structural stability.

Atomic-Scale Distribution and Evolution of Strain in Pt Nanoparticles Grown on MoS2 Nanosheet.

Interface strain significantly affects the band structure and electronic states of metal-nanocrystal-2D-semiconductor heterostructures, impacting system performance. While transmission electron microscopy (TEM) is a powerful tool for studying interface strain, its accuracy may be compromised by sample overlap in high-resolution images due to the unique nature of the metal-nanocrystals-2D-semiconductors heterostructure. Utilizing digital dark-field technology, the substrate influence on metal atomic column contrasts is eliminated, improving the accuracy of quantitative analysis in high-resolution TEM images. Applying this method to investigate Pt on MoS2 surfaces reveals that the heterostructure introduces a tensile strain of ≈3% in Pt nanocrystal. The x-directional linear strain in Pt nanocrystals has a periodic distribution that matches the semi-coherent interface between Pt nanocrystals and MoS2, while the remaining strain components localize mainly on edge atomic steps. These results demonstrate an accurate and efficient method for studying interface strain and provide a theoretical foundation for precise heterostructure fabrication.

Atomically Resolved Phase Coexistence in VO2 Thin Films.

Concurrent structural and electronic transformations in VO2 thin films are of 2-fold importance: enabling fine-tuning of the emergent electrical properties in functional devices, yet creating an intricate interfacial domain structure of transitional phases. Despite the importance of understanding the structure of VO2 thin films, a detailed real-space atomic structure analysis in which the oxygen atomic columns are also resolved is lacking. Moreover, intermediate atomic structures have remained elusive due to the lack of robust atomically resolved quantitative analysis. Here, we directly resolve both V and O atomic columns and discover the presence of intermediate monoclinic (M2) phase nanolayers (less than 2 nm thick) in epitaxially grown VO2 films on a TiO2 (001) substrate, where the dominant part of VO2 undergoes a transition from the tetragonal (rutile) phase to the monoclinic M1 phase. Strain analysis suggests that the presence of the M2 phase is related to local strain gradients near the TiO2/VO2 interface. We unfold the crucial role of imaging the spatial configurations of the oxygen anions (in addition to V cations) by utilizing atomic-resolution electron microscopy. Our approach can be used to unravel the structural transitions in a wide range of correlated oxides, offering substantial implications for, e.g., optoelectronics and ferroelectrics.

Cryo-EM combined with image deconvolution to determine ZIF-8 crystal structure

Abstract Metal–organic frameworks (MOFs) are crystalline porous materials with tunable properties, exhibiting great potential in gas adsorption, separation and catalysis.[1,2] It is challenging to visualize MOFs with transmission electron microscopy (TEM) due to their inherent instability under electron beam irradiation. Here, we employ cryo-electron microscopy (cryo-EM) to capture images of MOF ZIF-8, revealing inverted-space structural information at a resolution of up to about 1.7 Å and enhancing its critical electron dose to around 20 e −/Å2. In addition, it is confirmed by electron-beam irradiation experiments that the high voltage could effectively mitigate the radiolysis, and the structure of ZIF-8 is more stable along the [100] direction under electron beam irradiation. Meanwhile, since the high-resolution electron microscope images are modulated by contrast transfer function (CTF) and it is difficult to determine the positions corresponding to the atomic columns directly from the images. We employ image deconvolution to eliminate the impact of CTF and obtain the structural images of ZIF-8. As a result, the heavy atom Zn and the organic imidazole ring within the organic framework can be distinguished from structural images.

Bayesian inference of atomic column positions in scanning transmission electron microscopy images

Abstract Atomic-resolution scanning transmission electron microscopy combined with 2D Gaussian fitting enables the accurate and precise identification of atomic column positions within a few picometers. The measurement performance significantly depends on the signal-to-noise ratio of the atomic columns. In areas with low signal-to-noise ratios, such as near surfaces, the measurement performance was lower than that of the bulk. However, previous studies evaluated the accuracy and precision only in bulk areas, underscoring the need for a method that quantitatively evaluates the accuracy and precision of each atomic column position with various signal-to-noise ratios. This study introduced Bayesian inference to assess the accuracy and precision of determining individual atomic column positions under various signals. We applied this method to simulated and experimental images and demonstrated its effectiveness in identifying statistically significant displacements, particularly near surfaces with signal degradation. The use of vector maps and kernel density estimate plots obtained from Bayesian inference provided a probabilistic understanding of the atom displacement. Therefore, this study highlighted the potential benefits of Bayesian inference in high-resolution imaging to reveal material properties.

DFT-Assisted Investigation of the Electric Field and Charge Density Distribution of Pristine and Defective 2D WSe2 by Differential Phase Contrast Imaging.

Most properties of solid materials are defined by their internal electric field and charge density distributions which so far are difficult to measure with high spatial resolution. Especially for 2D materials, the atomic electric fields influence the optoelectronic properties. In this study, the atomic-scale electric field and charge density distribution of WSe2 bi- and trilayers are revealed using an emerging microscopy technique, differential phase contrast (DPC) imaging in scanning transmission electron microscopy (STEM). For pristine material, a higher positive charge density located at the selenium atomic columns compared to the tungsten atomic columns is obtained and tentatively explained by a coherent scattering effect. Furthermore, the change in the electric field distribution induced by a missing selenium atomic column is investigated. A characteristic electric field distribution in the vicinity of the defect with locally reduced magnitudes compared to the pristine lattice is observed. This effect is accompanied by a considerable inward relaxation of the surrounding lattice, which according to first principles DFT calculation is fully compatible with a missing column of Se atoms. This shows that DPC imaging, as an electric field sensitive technique, provides additional and remarkable information to the otherwise only structural analysis obtained with conventional STEM imaging.

Precipitation strengthening and thermal stability in a conventionally non-heat treatable AA3xxx aluminium alloy

We report an unexpected yet significant precipitation-strengthening effect with remarkable thermal stability in an otherwise conventionally non-heat treatable AA3104 aluminium alloy. We reveal that a minor addition of Cu plays a critical role in the alloy's strength and thermal stability, and explain the underpinning mechanisms. The primary strengthening β′ phase can be engineered to exhibit distinctive structural characteristics, including regularly-spaced Cu atom columns at the coherent β′/Al interfaces, stacking faults and resultant domains. Our atomistic simulations rationalise that these microscopic characteristics are directly promoted by the Cu addition. The Cu-decorated interfaces promote β′ phase nucleation and result in strong, directional covalent-like Cu-Si bonding at the β′/Al interfaces. Specifically, the interfacial Cu columns increase the work of separation of the habit-plane interfaces and reduce the interface energy, resulting in significant strengthening and stabilising effects. The Cu columns also facilitate the stacking fault formation in the β′ phase. Collectively, these features enhance the strengthening effect and thermal stability of the precipitates. This study demonstrates the potential for exploring "new" features in "old" alloys to advance alloy science and technology.

Quantifying the thickness of WTe2 using atomic-resolution STEM simulations and supervised machine learning.

For two-dimensional (2D) materials, the exact thickness of the material often dictates its physical and chemical properties. The 2D quantum material WTe2 possesses properties that vary significantly from a single layer to multiple layers, yet it has a complicated crystal structure that makes it difficult to differentiate thicknesses in atomic-resolution images. Furthermore, its air sensitivity and susceptibility to electron beam-induced damage heighten the need for direct ways to determine the thickness and atomic structure without acquiring multiple measurements or transferring samples in ambient atmosphere. Here, we demonstrate a new method to identify the thickness up to ten van der Waals layers in Td-WTe2 using atomic-resolution high-angle annular dark-field scanning transmission electron microscopy image simulation. Our approach is based on analyzing the intensity line profiles of overlapping atomic columns and building a standard neural network model from the line profile features. We observe that it is possible to clearly distinguish between even and odd thicknesses (up to seven layers), without using machine learning, by comparing the deconvoluted peak intensity ratios or the area ratios. The standard neural network model trained on the line profile features allows thicknesses to be distinguished up to ten layers and exhibits an accuracy of up to 94% in the presence of Gaussian and Poisson noise. This method efficiently quantifies thicknesses in Td-WTe2, can be extended to related 2D materials, and provides a pathway to characterize precise atomic structures, including local thickness variations and atomic defects, for few-layer 2D materials with overlapping atomic column positions.