Atomic-resolution Scanning Transmission Electron Microscopy Research Articles

Polarity controlled ScAlN multi-layer transduction structures grown by molecular beam epitaxy

We report on the molecular beam epitaxial growth and characterization of polarity-controlled single and multi-layer Scandium Aluminum Nitride (ScAlN) transduction structures grown directly on ScAlN templates deposited by physical vapor deposition (PVD) on Si(001) substrates. It is observed that direct epitaxial growth on PVD N-polar ScAlN leads to the flipping of polarity, resulting in metal (M)-polar ScAlN. By effectively removing the surface impurities, e.g., oxides, utilizing an in situ gallium (Ga)-assisted flushing technique, we show that high quality N-polar ScAlN epilayers can be achieved on PVD N-polar ScAlN templates. The polarity of ScAlN is confirmed by utilizing polarity-sensitive wet chemical etching and atomic-resolution scanning transmission electron microscopy. Through interface engineering, i.e., the controlled formation or removal of surface oxides, we have further demonstrated the ability to epitaxially grow an alternating tri-layer piezoelectric structure, consisting of N-polar, M-polar, and N-polar ScAlN layers. Such multi-layer, polarity-controlled ScAlN structures promise a manufacturable platform for the design and development of a broad range of acoustic and photonic devices.

Atomistic oxidation mechanism of Bi0.5Sb1.5Te3 (0001) surface

Surface oxidation can potentially influence transport properties of thermoelectric materials and service performance of thermoelectric devices. Here, the oxidation mechanism of the (0001) surface of a widely used p-type TE material, Bi0.5Sb1.5Te3 (BST), was investigated using spherical aberration corrected scanning transmission electron microscopy (STEM). Combining atomic resolution STEM and density function theory (DFT), it was revealed that oxidation occurs at room temperature in the dry air through O diffusion into the surface quintuple layer, facilitating formation of both cation and anion vacancies, weakening the Bi-Te and Sb-Te bonds, leading to oxidation product Sb2O3, amorphous Te, and Bi-rich Bi2Te3. Formation of a thin O-rich cation-deficient quintuple layer on the surface and the Bi-rich BST region can significantly reduce the interfacial reaction between BST and Ni electrode, as the reaction layer thickness is reduced by 75% after the surface oxidation. This work provides essential structural information on surface oxidation mechanism and its influence on properties and performance of TE materials and devices.

Earth-abundant Li-ion cathode materials with nanoengineered microstructures

AbstractManganese-based materials have tremendous potential to become the next-generation lithium-ion cathode as they are Earth abundant, low cost and stable. Here we show how the mobility of manganese cations can be used to obtain a unique nanosized microstructure in large-particle-sized cathode materials with enhanced electrochemical properties. By combining atomic-resolution scanning transmission electron microscopy, four-dimensional scanning electron nanodiffraction and in situ X-ray diffraction, we show that when a partially delithiated, high-manganese-content, disordered rocksalt cathode is slightly heated, it forms a nanomosaic of partially ordered spinel domains of 3–7 nm in size, which impinge on each other at antiphase boundaries. The short coherence length of these domains removes the detrimental two-phase lithiation reaction present near 3 V in a regular spinel and turns it into a solid solution. This nanodomain structure enables good rate performance and delivers 200 mAh g−1 discharge capacity in a (partially) disordered material with an average primary particle size of ∼5 µm. The work not only expands the synthesis strategies available for developing high-performance Earth-abundant manganese-based cathodes but also offers structural insights into the ability to nanoengineer spinel-like phases.

Real-Space Tilting Method for Atomic Resolution STEM Imaging of Nanocrystalline Materials.

Atomic-resolution scanning transmission electron microscopy (STEM) characterization requires precise tilting of the specimen to a high symmetric zone axis, which is usually processed in reciprocal space by following the diffraction patterns. However, for small-sized nanocrystalline materials, their diffraction patterns are often too faint to guide the tilting process. Here, a simple and effective tilting method is developed based on the diffraction contrast change of the shadow image in the Ronchigram. The misorientation angle of the specimen can be calculated and tilted to the zone axis based on the position of the shadow image with lowest intensity. This method requires no prior knowledge of the sample and the maximum misorientation angle that can be corrected is >±6.9° with sub-mrad accuracy. It operates in real space, without recording the diffraction patterns of the specimens, making it particularly effective for nanocrystalline materials. Combined with the scripting to control the microscope, the sample can be automatically tilted to the zone axis under low dose conditions (<0.17 e-Å- 2s-1), facilitating the imaging of beam sensitive materials such as zeolites or metal-organic frameworks. This automated tilting method can significantly contribute to the atomic-scale characterization of the nanocrystalline materials by STEM imaging.

Single-Image-Based Deep Learning for Precise Atomic Defect Identification.

Defect engineering is widely used to impart the desired functionalities on materials. Despite the widespread application of atomic-resolution scanning transmission electron microscopy (STEM), traditional methods for defect analysis are highly sensitive to random noise and human bias. While deep learning (DL) presents a viable alternative, it requires extensive amounts of training data with labeled ground truth. Herein, employing cycle generative adversarial networks (CycleGAN) and U-Nets, we propose a method based on a single experimental STEM image to tackle high annotation costs and image noise for defect detection. Not only atomic defects but also oxygen dopants in monolayer MoS2 are visualized. The method can be readily extended to other two-dimensional systems, as the training is based on unit-cell-level images. Therefore, our results outline novel ways to train the model with minimal data sets, offering great opportunities to fully exploit the power of DL in the materials science community.

Constructing Slip Stacking Diversity in Van der Waals Homobilayers.

The van der Waals (vdW) interface provides two important degrees of freedom-twist and slip-to tune interlayer structures and inspire unique physics. However, constructing diversified high-quality slip stackings (i.e., lattice orientations between layers are parallel with only interlayer sliding) is more challenging than twisted stackings due to angstrom-scale structural discrepancies between different slip stackings, sparsity of thermodynamically stable candidates and insufficient mechanism understanding. Here, using transition metal dichalcogenide (TMD) homobilayers as a model system, this work theoretically elucidates that vdW materials with low lattice symmetry and weak interlayer coupling allow the creation of multifarious thermodynamically advantageous slip stackings, and experimentally achieves13 and 9 slip stackings in 1T″-ReS2 and 1T″-ReSe2 bilayers via direct growth, which are systematically revealed by atomic-resolution scanning transmission electron microscopy (STEM), angle-resolved polarization Raman spectroscopy, and second harmonic generation (SHG) measurements. This work also develops modulation strategies to switch the stacking via grain boundaries (GBs) and to expand the slip stacking library from thermodynamic to kinetically favored structures via in situ thermal treatment. Finally, density functional theory (DFT) calculations suggest a prominent dependence of the pressure-induced electronic band structure transition on stacking configurations. These studies unveil a unique vdW epitaxy and offer a viable means for manipulating interlayer atomic registries.

Deciphering the Atomic-Scale Structural Origin for Photoluminescence Quenching in Tin-Lead Alloyed Perovskite Nanocrystals.

The development of tin-lead alloyed halide perovskite nanocrystals (PNCs) is highly desirable for creating ultrastable, eco-friendly optoelectronic applications. However, the current incorporation of tin into the lead matrix results in severe photoluminescence (PL) quenching. To date, the precise atomic-scale structural origins of this quenching are still unknown, representing a significant barrier to fully realizing the potential of these materials. Here, we uncover the distinctive defect-related microstructures responsible for PL quenching using atomic-resolution scanning transmission electron microscopy and theoretical calculations. Our findings reveal an increase in point defects and Ruddlesden-Popper (RP) planar faults with increasing tin content. Notably, the point defects include a spectrum of vacancies and previously overlooked antisite defects with bromide vacancies and cation antisite defects emerging as the primary contributors to deep-level defects. Furthermore, the RP planar faults exhibit not only the typical rock-salt stacking pattern found in pure Pb-based PNCs but also previously undocumented microstructures rich in bromide vacancies and deep-level cation antisite defects. Direct strain imaging uncovers severe lattice distortion and significant inhomogeneous strain distributions caused by point defect aggregation, potentially breaking the local force balance and driving RP planar fault formation via lattice slippage. Our work illuminates the nature and evolution of defects in tin-lead alloyed halide perovskite nanocrystals and their profound impact on PL quenching, providing insights that support future material strategies in the development of less toxic tin-lead alloyed perovskite nanocrystals.

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.

SiX2 (X = S, Se) Single Chains and (Si-Ge)X2 Quaternary Alloys.

Layered or chain materials have received significant research attention owing to their interesting physical properties, which can dramatically change when the material is thinned from bulk (three-dimensional) to thin two-dimensional sheet or one-dimensional (1D) chain form. Materials with the stoichiometry AX2 with A = Si or Ge and X = S or Se form an especially intriguing semiconducting class. For example, bulk silicon dichalcogenides (SiX2) consist of 1D chains held together by van der Waals forces. Although this structural configuration has the potential to reveal interesting physical phenomena within the 1D limit, obtaining SiX2 single chains has been challenging. We here examine experimentally and theoretically SiX2 materials in the low chain number limit. Carbon nanotubes serve as growth templates and stabilize and protect the structures, and atomic-resolution scanning transmission electron microscopy directly identifies the atomic structure. Two distinct chain structures are observed for SiX2. SixGe1-xS2(1-y)Se2y quaternary alloy chains are also synthesized and characterized, demonstrating tunable semiconducting properties at the atomic-chain level. Density functional theory calculations reveal that the band gap of these alloy chains can be widely tuned through composition engineering. This work offers the possibilities for synthesizing and controlling semiconductor compositions at the single-chain limit to tailor material properties.

High-Entropy Transition Metal Phosphorus Trichalcogenides for Rapid Sodium Ion Diffusion.

High-entropy strategies are regarded as a powerful means to enhance performance in energy storage fields. The improved properties are invariably ascribed to entropy stabilization or synergistic cocktail effect. Therefore, the manifested properties in such multicomponent materials are usually unpredictable. Elucidating the precise correlations between atomic structures and properties remains a challenge in high-entropy materials (HEMs). Herein, atomic-resolution scanning transmission electron microscopy annular dark field (STEM-ADF) imaging and four dimensions (4D)-STEM are combined to directly visualize atomic-scale structural and electric information in high-entropy FeMnNiVZnPS3. Aperiodic stacking is found in FeMnNiVZnPS3 accompanied by high-density strain soliton boundaries (SSBs). Theoretical calculation suggests that the formation of such structures is attributed to the imbalanced stress of distinct metal-sulfur bonds in FeMnNiVZnPS3. Interestingly, the electric field concentrates along the two sides of SSBs and gradually diminishes toward the two-dimensional (2D) plane to generate a unique electric field gradient, strongly promoting the ion-diffusion rate. Accordingly, high-entropy FeMnNiVZnPS3 demonstrates superior ion-diffusion coefficients of 10-9.7-10-8.3 cm2 s-1 and high-rate performance (311.5 mAh g-1 at 30 A g-1). This work provides an alternative way for the atomic-scale understanding and design of sophisticated HEMs, paving the way for property engineering in multi-component materials.

Single atoms and metal nanoclusters anchored to graphene vacancies

Fabricating dispersed single atoms and size-controlled metal nanoclusters remains a difficult challenge due to sintering. Here, we demonstrate that atoms and clusters can be immobilized using atomically clean defect-engineered graphene as the matrix. The graphene is first cleaned of surface contamination with laser heating, after which low-energy Ar irradiation is used to create spatially well-separated vacancies into it. Metal atoms are then evaporated either via thermal or ebeam evaporation onto graphene, where they diffuse until being trapped into a vacancy. The density of embedded structures can be controlled through irradiation dose, and the size of the structures through evaporation time. The resulting structures are confirmed through atomic-resolution scanning transmission electron microscopy and electron energy loss spectroscopy. We demonstrate here incorporation of Al, Ti, Fe, Ag and Au single atoms or nanoclusters, but the method should work equally well for other elements.

New Poisson denoising method for pulse-count STEM imaging

With the recent progress in the development of detectors in electron microscopy, it has become possible to directly count the number of electrons per pixel, even with a scintillator-type detector, by incorporating a pulse-counting module. To optimize a denoising method for electron counting imaging, in this study, we propose a Poisson denoising method for atomic-resolution scanning transmission electron microscopy images. Our method is based on the Markov random field model and Bayesian inference, and we can reduce the electron dose by a factor of about 15 times or further below. Moreover, we showed that the method of reconstruction from multiple images without integrating them performs better than that from an integrated image.

Above-room-temperature chiral skyrmion lattice and Dzyaloshinskii–Moriya interaction in a van der Waals ferromagnet Fe3−xGaTe2

Skyrmions in existing 2D van der Waals (vdW) materials have primarily been limited to cryogenic temperatures, and the underlying physical mechanism of the Dzyaloshinskii–Moriya interaction (DMI), a crucial ingredient for stabilizing chiral skyrmions, remains inadequately explored. Here, we report the observation of Néel-type skyrmions in a vdW ferromagnet Fe3−xGaTe2 above room temperature. Contrary to previous assumptions of centrosymmetry in Fe3−xGaTe2, the atomic-resolution scanning transmission electron microscopy reveals that the off-centered FeΙΙ atoms break the spatial inversion symmetry, rendering it a polar metal. First-principles calculations further elucidate that the DMI primarily stems from the Te sublayers through the Fert–Lévy mechanism. Remarkably, the chiral skyrmion lattice in Fe3−xGaTe2 can persist up to 330 K at zero magnetic field, demonstrating superior thermal stability compared to other known skyrmion vdW magnets. This work provides valuable insights into skyrmionics and presents promising prospects for 2D material-based skyrmion devices operating beyond room temperature.

Synthesis and in-depth structure determination of a novel metastable high-pressure CrTe3 phase

This study reports the synthesis and crystal structure determination of a novel CrTe3 phase using various experimental and theoretical methods. The average stoichiometry and local phase separation of this quenched high-pressure phase were characterized by ex situ synchrotron powder X-ray diffraction and total scattering. Several structural models were obtained using simulated annealing, but all suffered from an imperfect Rietveld refinement, especially at higher diffraction angles. Finally, a novel stoichiometrically correct crystal structure model was proposed on the basis of electron diffraction data and refined against powder diffraction data using the Rietveld method. Scanning electron microscopy–energy-dispersive X-ray spectrometry (EDX) measurements verified the targeted 1:3 (Cr:Te) average stoichiometry for the starting compound and for the quenched high-pressure phase within experimental errors. Scanning transmission electron microscopy (STEM)–EDX was used to examine minute variations of the Cr-to-Te ratio at the nanoscale. Precession electron diffraction (PED) experiments were applied for the nanoscale structure analysis of the quenched high-pressure phase. The proposed monoclinic model from PED experiments provided an improved fit to the X-ray patterns, especially after introducing atomic anisotropic displacement parameters and partial occupancy of Cr atoms. Atomic resolution STEM and simulations were conducted to identify variations in the Cr-atom site-occupancy factor. No significant variations were observed experimentally for several zone axes. The magnetic properties of the novel CrTe3 phase were investigated through temperature- and field-dependent magnetization measurements. In order to understand these properties, auxiliary theoretical investigations have been performed by first-principles electronic structure calculations and Monte Carlo simulations. The obtained results allow the observed magnetization behavior to be interpreted as the consequence of competition between the applied magnetic field and the Cr–Cr exchange interactions, leading to a decrease of the magnetization towards T = 0 K typical for antiferromagnetic systems, as well as a field-induced enhanced magnetization around the critical temperature due to the high magnetic susceptibility in this region.

Picometer-Scale Atomic Shifts Governing Subdisordered Structures in Diamond.

Diamond is considered the most promising next-generation semiconductor material due to its excellent physical characteristics. It has been more than three decades since the discovery of a special structure named n-diamond. However, despite extensive efforts, its crystallographic structure and properties are still unclear. Here, we show that subdisordered structures in diamond provide an explanation for the structural feature of n-diamond. Monocrystalline diamond with subdisordered structures is synthesized via the chemical vapor deposition method. Atomic-resolution scanning transmission electron microscopy characterizations combined with the picometer-precision peak finder technology and diffraction simulations reveal that picometer-scale shifts of atoms within cells of diamond govern the subdisordered structures. First-principles calculations indicate that the bandgap of diamond decreases rapidly with increasing shifting distance, in accordance with experimental results. These findings clarify the crystallographic structure and electronic properties of n-diamond and provide new insights into the bandgap adjustment in diamond.

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.

Microstructural investigation of epitaxial aluminum films grown by molecular beam epitaxy

High-quality epitaxial Al thin films with thickness in nano-to atomic-scale were grown on Si, sapphire, and GaAs substrates by molecular beam epitaxy. Microstructure of Al films as well as the interfacial bonding between Al and substrates were carefully investigated. Structural analyses from x-ray diffraction (XRD) and scanning transmission electron microscopy (STEM) shows that the Al (111) films are epitaxially grown on Si, sapphire, and GaAs substrates. Atomic-resolution STEM imaging reveals smooth and sharp interfaces without any interlayer between Al films and substrate; and the interfacial bonding are determined as Al–Si, Al–O, and Al–Ga for Al grown on Si, sapphire, and GaAs, respectively. Atomic force microscopy shows very smooth surfaces of Al films with roughness of 0.16–0.75 nm. Secondary ion mass spectrometry (SIMS) reveals the chemical composition of the deposited films, highlighting the presence of minor amounts of trapped hydroxide content.

Tuning grain boundary cation segregation with oxygen deficiency and atomic structure in a perovskite compositionally complex oxide thin film

Compositionally complex oxides (CCOs) are an emerging class of materials encompassing high entropy and entropy stabilized oxides. These promising advanced materials leverage tunable chemical bond structure, lattice distortion, and chemical disorder for unprecedented properties. Grain boundary (GB) and point defect segregation to GBs are relatively understudied in CCOs even though they can govern macroscopic material properties. For example, GB segregation can govern local chemical (dis)order and point defect distribution, playing a critical role in electrochemical reaction kinetics, and charge and mass transport in solid electrolytes. However, compared with conventional oxides, GBs in multi-cation CCO systems are expected to exhibit more complex segregation phenomena and, thus, prove more difficult to tune through GB design strategies. Here, GB segregation was studied in a model perovskite CCO LaFe0.7Ni0.1Co0.1Cu0.05Pd0.05O3−x textured thin film by (sub-)atomic-resolution scanning transmission electron microscopy imaging and spectroscopy. It is found that GB segregation is correlated with cation reducibility—predicted by an Ellingham diagram—as Pd and Cu segregate to GBs rich in oxygen vacancies (VO··). Furthermore, Pd and Cu segregation is highly sensitive to the concentration and spatial distribution of VO·· along the GB plane, as well as fluctuations in atomic structure and elastic strain induced by GB local disorder, such as dislocations. This work offers a perspective of controlling segregation concentration of CCO cations to GBs by tuning reducibility of CCO cations and oxygen deficiency, which is expected to guide GB design in CCOs.

Dependence of the Structural and Magnetic Properties on the Growth Sequence in Heterostructures Designed by YbFeO3 and BaFe12O19.

The structure and the chemical composition of individual layers as well as of interfaces belonging to the two heterostructures M1 (BaFe12O19/YbFeO3/YSZ) and M2 (YbFeO3/BaFe12O19/YSZ) grown by pulsed laser deposition on yttria-stabilized zirconia (YSZ) substrates are deeply characterized by using a combination of methods such as high-resolution X-ray diffraction, transmission electron microscopy (TEM), and atomic-resolution scanning TEM with energy-dispersive X-ray spectroscopy. The temperature-dependent magnetic properties demonstrate two distinct heterostructures with different coercivity, anisotropy fields, and first anisotropy constants, which are related to the defect concentrations within the individual layers and to the degree of intermixing at the interface. The heterostructure with the stacking order BaFe12O19/YbFeO3, i.e., M1, exhibits a distinctive interface without any chemical intermixture, while an Fe-rich crystalline phase is observed in M2 both in atomic-resolution EDX maps and in mass density profiles. Additionally, M1 shows high c-axis orientation, which induces a higher anisotropy constant K1 as well as a larger coercivity due to a high number of phase boundaries. Despite the existence of a canted antiferromagnetic/ferromagnetic combination (T < 140 K), both heterostructures M1 and M2 do not reveal any detectable exchange bias at T = 50 K. Additionally, compressive residual strain on the BaM layer is found to be suppressing the ferromagnetism, thus reducing the Curie temperature (Tc) in the case of M1. These findings suggest that M1 (BaFe12O19/YbFeO3/YSZ) is suitable for magnetic storage applications.

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.