Oxygen octahedra picker: A software tool to extract quantitative information from STEM images

Insights into Strain Engineering: From Ferroelectrics to Related Functional Materials and Beyond

Ferroelectrics have become indispensable components in various application fields, including information processing, energy harvesting, and electromechanical conversion, owing to their unique ability to exhibit electrically or mechanically switchable polarization. The distinct polar noncentrosymmetric lattices of ferroelectrics make them highly responsive to specific crystal structures. Even slight changes in the lattice can alter the polarization configuration and response to external fields. In this regard, strain engineering has emerged as a prevalent regulation approach that not only offers a versatile platform for structural and performance optimization within ferroelectrics but also unlocks boundless potential in various functional materials. In this review, we systematically summarize the breakthroughs in ferroelectric-based functional materials achieved through strain engineering and progress in method development. We cover research activities ranging from fundamental attributes to wide-ranging applications and novel functionalities ranging from electromechanical transformation in sensors and actuators to tunable dielectric materials and information technologies, such as transistors and nonvolatile memories. Building upon these achievements, we also explore the endeavors to uncover the unprecedented properties through strain engineering in related chemical functionalities, such as ferromagnetism, multiferroicity, and photoelectricity. Finally, through discussions on the prospects and challenges associated with strain engineering in the materials, this review aims to stimulate the development of new methods for strain regulation and performance boosting in functional materials, transcending the boundaries of ferroelectrics.

Direct visualization of stacking-selective self-intercalation in epitaxial Nb1+xSe2 films

Two-dimensional (2D) van der Waals (vdW) materials offer rich tuning opportunities generated by different stacking configurations or by introducing intercalants into the vdW gaps. Current knowledge of the interplay between stacking polytypes and intercalation often relies on macroscopically averaged probes, which fail to pinpoint the exact atomic position and chemical state of the intercalants in real space. Here, by using atomic-resolution electron energy-loss spectroscopy in a scanning transmission electron microscope, we visualize a stacking-selective self-intercalation phenomenon in thin films of the transition-metal dichalcogenide (TMDC) Nb1+xSe2. We observe robust contrasts between 180°-stacked layers with large amounts of Nb intercalants inside their vdW gaps and 0°-stacked layers with little detectable intercalants inside their vdW gaps, coexisting on the atomic scale. First-principles calculations suggest that the films lie at the boundary of a phase transition from 0° to 180° stacking when the intercalant concentration x exceeds ~0.25, which we could attain in our films due to specific kinetic pathways. Our results offer not only renewed mechanistic insights into stacking and intercalation, but also open up prospects for engineering the functionality of TMDCs via stacking-selective self-intercalation.

Quantitative mapping of strain and displacement fields over HR-TEM and HR-STEM images of crystals with reference to a virtual lattice

A method for the reciprocal space treatment of high-resolution transmission electron microscopy (HR-TEM) and high-resolution scanning transmission electron microscopy (HR-STEM) images has been developed. Named "Absolute strain" (AbStrain), it allows for quantification and mapping of interplanar distances and angles, displacement fields and strain tensor components with reference to a user-defined Bravais lattice and with their corrections from the image distortions specific to HR-TEM and HR-STEM imaging. We provide the corresponding mathematical formalism. AbStrain goes beyond the restriction of the existing method known as geometric phase analysis by enabling direct analysis of the area of interest without the need for reference lattice fringes of a similar crystal structure on the same field of view. In addition, for the case of a crystal composed of two or more types of atoms, each with its own sub-structure constraint, we developed a method named "Relative displacement" for extracting sub-lattice fringes associated to one type of atom and measuring atomic columns displacements associated to each sub-structure with reference to a Bravais lattice or to another sub-structure. The successful application of AbStrain and Relative displacement to HR-STEM images of functional oxide ferroelectric heterostructures is demonstrated.

Strain-induced Mn valence state variation in CaMnO3-δ/substrate interfaces: electronic reconstruction versus oxygen vacancies

This study investigates the nanoscale crystalline and electronic structures of the interfaces between CaMnO_3-δ and substrates such as SrTiO₃ (001) and LaAlO₃ (001) by employing advanced transmission electron microscopy and electron energy loss spectroscopy techniques. The objective is to comprehend the influence of different strains on the Mn valence state. Our findings reveal that the Mn valence state remains relatively stable in the region of a weakly tensile-strained interface, whereas it experiences a significant decrease from Mn⁴⁺ to Mn^2.3+ in the region of a strongly tensile-strained interface. Although this reduction in valence appears to be consistent with the electron reconstruction scenario, the observed increase in the out-of-plane lattice constant at the interface implies the accumulation of oxygen vacancies at the interface. Consequently, the present study offers a comprehensive understanding of the intricate relationships among the Mn valence state, local structure, and formation of oxygen vacancies in the context of two distinct strain cases. This knowledge is essential for tailoring the interface properties and guiding future developments in the field of oxide heterostructures.

Emergent and robust ferromagnetic-insulating state in highly strained ferroelastic LaCoO3 thin films

Transition metal oxides are promising candidates for the next generation of spintronic devices due to their fascinating properties that can be effectively engineered by strain, defects, and microstructure. An excellent example can be found in ferroelastic LaCoO₃ with paramagnetism in bulk. In contrast, unexpected ferromagnetism is observed in tensile-strained LaCoO₃ films, however, its origin remains controversial. Here we simultaneously reveal the formation of ordered oxygen vacancies and previously unreported long-range suppression of CoO₆ octahedral rotations throughout LaCoO₃ films. Supported by density functional theory calculations, we find that the strong modification of Co 3d-O 2p hybridization associated with the increase of both Co-O-Co bond angle and Co-O bond length weakens the crystal-field splitting and facilitates an ordered high-spin state of Co ions, inducing an emergent ferromagnetic-insulating state. Our work provides unique insights into underlying mechanisms driving the ferromagnetic-insulating state in tensile-strained ferroelastic LaCoO₃ films while suggesting potential applications toward low-power spintronic devices.

Machine learning in electron microscopy for advanced nanocharacterization: current developments, available tools and future outlook

In the last few years, electron microscopy has experienced a new methodological paradigm aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine learning and artificial intelligence are answering this call providing powerful resources towards automation, exploration, and development. In this review, we evaluate the state-of-the-art of machine learning applied to electron microscopy (and obliquely, to materials and nano-sciences). We start from the traditional imaging techniques to reach the newest higher-dimensionality ones, also covering the recent advances in spectroscopy and tomography. Additionally, the present review provides a practical guide for microscopists, and in general for material scientists, but not necessarily advanced machine learning practitioners, to straightforwardly apply the offered set of tools to their own research. To conclude, we explore the state-of-the-art of other disciplines with a broader experience in applying artificial intelligence methods to their research (e.g., high-energy physics, astronomy, Earth sciences, and even robotics, videogames, or marketing and finances), in order to narrow down the incoming future of electron microscopy, its challenges and outlook.

Emergent multiferroism with magnetodielectric coupling in EuTiO3 created by a negative pressure control of strong spin-phonon coupling

Negative pressure has emerged as a powerful tool to tailor the physical properties of functional materials. However, a negative pressure control of spin-phonon coupling for engineering magnetism and multiferroicity has not been explored to date. Here, using uniform three-dimensional strain-induced negative pressure in nanocomposite films of (EuTiO₃)_0.5:(MgO)_0.5, we demonstrate an emergent multiferroicity with magnetodielectric coupling in EuTiO₃, matching exactly with density functional theory calculations. Density functional theory calculations are further used to explore the underlying physics of antiferromagnetic-paraelectric to ferromagnetic-ferroelectric phase transitions, the spin-phonon coupling, and its correlation with negative pressures. The observation of magnetodielectric coupling in the EuTiO₃ reveals that an enhanced spin-phonon coupling originates from a negative pressure induced by uniform three-dimensional strain. Our work provides a route to creating multiferroicity and magnetoelectric coupling in single-phase oxides using a negative pressure approach.

Negative pressure tailors the physical properties of functional oxide materials. Here, the authors demonstrate an emergent multiferroism with magnetodielectric coupling in EuTiO₃ created by a negative pressure control of strong spin-phonon coupling.

Disentangling Coexisting Structural Order Through Phase Lock-In Analysis of Atomic-Resolution STEM Data

As a real-space technique, atomic-resolution STEM imaging contains both amplitude and geometric phase information about structural order in materials, with the latter encoding important information about local variations and heterogeneities present in crystalline lattices. Such phase information can be extracted using geometric phase analysis (GPA), a method which has generally focused on spatially mapping elastic strain. Here we demonstrate an alternative phase demodulation technique and its application to reveal complex structural phenomena in correlated quantum materials. As with other methods of image phase analysis, the phase lock-in approach can be implemented to extract detailed information about structural order and disorder, including dislocations and compound defects in crystals. Extending the application of this phase analysis to Fourier components that encode periodic modulations of the crystalline lattice, such as superlattice or secondary frequency peaks, we extract the behavior of multiple distinct order parameters within the same image, yielding insights into not only the crystalline heterogeneity but also subtle emergent order parameters such as antipolar displacements. When applied to atomic-resolution images spanning large (~0.5 × 0.5 μm2) fields of view, this approach enables vivid visualizations of the spatial interplay between various structural orders in novel materials.

Probing Multiscale Disorder in Pyrochlore and Related Complex Oxides in the Transmission Electron Microscope: A Review

Transmission electron microscopy (TEM), and its counterpart, scanning TEM (STEM), are powerful materials characterization tools capable of probing crystal structure, composition, charge distribution, electronic structure, and bonding down to the atomic scale. Recent (S)TEM instrumentation developments such as electron beam aberration-correction as well as faster and more efficient signal detection systems have given rise to new and more powerful experimental methods, some of which (e.g., 4D-STEM, spectrum-imaging, in situ/operando (S)TEM)) facilitate the capture of high-dimensional datasets that contain spatially-resolved structural, spectroscopic, time- and/or stimulus-dependent information across the sub-angstrom to several micrometer length scale. Thus, through the variety of analysis methods available in the modern (S)TEM and its continual development towards high-dimensional data capture, it is well-suited to the challenge of characterizing isometric mixed-metal oxides such as pyrochlores, fluorites, and other complex oxides that reside on a continuum of chemical and spatial ordering. In this review, we present a suite of imaging and diffraction (S)TEM techniques that are uniquely suited to probe the many types, length-scales, and degrees of disorder in complex oxides, with a focus on disorder common to pyrochlores, fluorites and the expansive library of intermediate structures they may adopt. The application of these techniques to various complex oxides will be reviewed to demonstrate their capabilities and limitations in resolving the continuum of structural and chemical ordering in these systems.

Optimizing Nonrigid Registration for Scanning Transmission Electron Microscopy Image Series

Achieving sub-picometer precision measurements of atomic column positions in high-resolution scanning transmission electron microscope images using nonrigid registration (NRR) and averaging of image series requires careful optimization of experimental conditions and the parameters of the registration algorithm. On experimental data from SrTiO3 [100], sub-pm precision requires alignment of the sample to the zone axis to within 1 mrad tilt and sample drift of less than 1 nm/min. At fixed total electron dose for the series, precision in the fast scan direction improves with shorter pixel dwell time to the limit of our microscope hardware, but the best precision along the slow scan direction occurs at 6 μs/px dwell time. Within the NRR algorithm, the “smoothness factor” that penalizes large estimated shifts is the most important parameter for sub-pm precision, but in general, the precision of NRR images is robust over a wide range of parameters.

Probing Charge Accumulation at SrMnO3/SrTiO3 Heterointerfaces via Advanced Electron Microscopy and Spectroscopy

The last three decades have seen a growing trend toward studying the interfacial phenomena in complex oxide heterostructures. Of particular concern is the charge distribution at interfaces, which is a crucial factor in controlling the interface transport behavior. However, the study of the charge distribution is very challenging due to its small length scale and the intricate structure and chemistry at interfaces. Furthermore, the underlying origin of the interfacial charge distribution has been rarely studied in-depth and is still poorly understood. Here, by a combination of aberration-corrected scanning transmission electron microscopy (STEM) and spectroscopy techniques, we identify the charge accumulation in the SrMnO₃ (SMO) side of SrMnO₃/SrTiO₃ heterointerfaces and find that the charge density attains the maximum of 0.13 ± 0.07 e^-/unit cell (uc) at the first SMO monolayer. Based on quantitative atomic-scale STEM analyses and first-principle calculations, we explore the origin of interfacial charge accumulation in terms of epitaxial strain-favored oxygen vacancies, cationic interdiffusion, interfacial charge transfer, and space-charge effects. This study, therefore, provides a comprehensive description of the charge distribution and related mechanisms at the SMO/STO heterointerfaces, which is beneficial for the functionality manipulation via charge engineering at interfaces.

Fast Pixelated Detectors in Scanning Transmission Electron Microscopy. Part II: Post-Acquisition Data Processing, Visualization, and Structural Characterization

Fast pixelated detectors incorporating direct electron detection (DED) technology are increasingly being regarded as universal detectors for scanning transmission electron microscopy (STEM), capable of imaging under multiple modes of operation. However, several issues remain around the post-acquisition processing and visualization of the often very large multidimensional STEM datasets produced by them. We discuss these issues and present open source software libraries to enable efficient processing and visualization of such datasets. Throughout, we provide examples of the analysis methodologies presented, utilizing data from a 256 × 256 pixel Medipix3 hybrid DED detector, with a particular focus on the STEM characterization of the structural properties of materials. These include the techniques of virtual detector imaging; higher-order Laue zone analysis; nanobeam electron diffraction; and scanning precession electron diffraction. In the latter, we demonstrate a nanoscale lattice parameter mapping with a fractional precision ≤6 × 10−4 (0.06%).

Nanoparticle Recognition on Scanning Probe Microscopy Images Using Computer Vision and Deep Learning

Identifying, counting and measuring particles is an important component of many research studies. Images with particles are usually processed by hand using a software ruler. Automated processing, based on conventional image processing methods (edge detection, segmentation, etc.) are not universal, can only be used on good-quality images and need to set a number of parameters empirically. In this paper, we present results from the application of deep learning to automated recognition of metal nanoparticles deposited on highly oriented pyrolytic graphite on images obtained by scanning tunneling microscopy (STM). We used the Cascade Mask-RCNN neural network. Training was performed on a dataset containing 23 STM images with 5157 nanoparticles. Three images containing 695 nanoparticles were used for verification. As a result, the trained neural network recognized nanoparticles in the verification set with 0.93 precision and 0.78 recall. Predicted contour refining with 2D Gaussian function was a proposed option. The accuracies for mean particle size calculated from predicted contours compared with ground truth were in the range of 0.87-0.99. The results were compared with outcomes from other generally available software, based on conventional image processing methods. The advantages of deep learning methods for automatic particle recognition were clearly demonstrated. We developed a free open-access web service "ParticlesNN" based on the trained neural network, which can be used by any researcher in the world.

Measuring Dynamic Structural Changes of Nanoparticles at the Atomic Scale Using Scanning Transmission Electron Microscopy

We propose a new method to measure atomic scale dynamics of nanoparticles from experimental high-resolution annular dark field scanning transmission electron microscopy images. By using the so-called hidden Markov model, which explicitly models the possibility of structural changes, the number of atoms in each atomic column can be quantified over time. This newly proposed method outperforms the current atom-counting procedure and enables the determination of the probabilities and cross sections for surface diffusion. This method is therefore of great importance for revealing and quantifying the atomic structure when it evolves over time via adatom dynamics, surface diffusion, beam effects, or during in situ experiments.

Direct Observation of Huge Flexoelectric Polarization around Crack Tips

Flexoelectricity is especially relevant for nanoscale structures, and it is expected to be largest at the tip of cracks. We demonstrate the presence of a huge flexoelectric polarization at crack tips in SrTiO₃ by direct observation with scanning transmission electron microscopy. We observe an averaged polarization of 62 ± 16 μC cm^-2 in the three unit cells adjacent to the crack tip, which is one of the largest flexoelectric polarizations ever reported. The polarization is screened by an electron density of 0.7 ± 0.1 e^-/uc localized within one unit cell. These findings reveal the relevance of flexoelectricity for the science of crack formation and propagation.

The Atomic Circus: Small Electron Beams Spotlight Advanced Materials Down to the Atomic Scale

Defects in crystalline materials have a tremendous impact on their functional behavior. Controlling and tuning of these imperfections can lead to marked improvements in their physical, electrical, magnetic, and optical properties. Thanks to the development of aberration-corrected (scanning) transmission electron microscopy (STEM/TEM), direct visualization of defects at multiple length scales has now become possible, including those critically important defects at the atomic scale. Thorough understanding of the nature and dynamics of these defects is the key to unraveling the fundamental origins of structure-property relationships. Such insight can therefore allow the creation of new materials with desired properties through appropriate defect engineering. Herein, several examples of new insights obtained from representative functional materials are shown, including piezoelectrics/ferroelectrics, oxide interfaces, thermoelectrics, electrocatalysts, and 2D materials.

Practical High Piezoelectricity in Barium Titanate Ceramics Utilizing Multiphase Convergence with Broad Structural Flexibility

Due to growing environmental concerns on the toxicity of lead-based piezoelectric materials, lead-free alternatives are urgently required but so far have not been able to reach competitive performance. Here we employ a novel phase-boundary engineering strategy utilizing the multiphase convergence, which induces a broad structural flexibility in a wide phase-boundary zone with contiguous polymorphic phase transitions. We achieve an ultrahigh piezoelectric constant ( d₃₃) of 700 ± 30 pC/N in BaTiO₃-based ceramics, maintaining >600 pC/N over a wide composition range. Atomic resolution polarization mapping by Z-contrast imaging reveals the coexistence of three ferroelectric phases (T + O + R) at the nanoscale with nanoscale polarization rotation between them. Theoretical simulations confirm greatly reduced energy barriers facilitating polarization rotation. Our lead-free material exceeds the performance of the majority of lead-based systems (including the benchmark PZT-5H) in the temperature range of 10-40 °C, making it suitable as a lead-free replacement in practical applications. This work offers a new paradigm for designing lead-free functional materials with superior electromechanical properties.

Material structure, properties, and dynamics through scanning transmission electron microscopy

Scanning transmission electron microscopy (STEM) has advanced rapidly in the last decade thanks to the ability to correct the major aberrations of the probe-forming lens. Now, atomic-sized beams are routine, even at accelerating voltages as low as 40 kV, allowing knock-on damage to be minimized in beam sensitive materials. The aberration-corrected probes can contain sufficient current for high-quality, simultaneous, imaging and analysis in multiple modes. Atomic positions can be mapped with picometer precision, revealing ferroelectric domain structures, composition can be mapped by energy-dispersive X-ray spectroscopy (EDX) and electron energy loss spectroscopy (EELS), and charge transfer can be tracked unit cell by unit cell using the EELS fine structure. Furthermore, dynamics of point defects can be investigated through rapid acquisition of multiple image scans. Today STEM has become an indispensable tool for analytical science at the atomic level, providing a whole new level of insights into the complex interplays that control material properties.

Correcting the linear and nonlinear distortions for atomically resolved STEM spectrum and diffraction imaging

Specimen and stage drift as well as scan distortions can lead to a mismatch between true and desired electron probe positions in scanning transmission electron microscopy (STEM) which can result in both linear and nonlinear distortions in the subsequent experimental images. This problem is intensified in STEM spectrum and diffraction imaging techniques owing to the extended dwell times (pixel exposure time) as compared to conventional STEM imaging. As a consequence, these image distortions become more severe in STEM spectrum/diffraction imaging. This becomes visible as expansion, compression and/or shearing of the crystal lattice, and can even prohibit atomic resolution and thus limits the interpretability of the results. Here, we report a software tool for post-correcting the linear and nonlinear image distortions of atomically resolved 3D spectrum imaging as well as 4D diffraction imaging. This tool improves the interpretability of distorted STEM spectrum/diffraction imaging data.

Quantitative comparison of bright field and annular bright field imaging modes for characterization of oxygen octahedral tilts

Octahedral tilt behavior is increasingly recognized as an important contributing factor to the physical behavior of perovskite oxide materials and especially their interfaces, necessitating the development of high-resolution methods of tilt mapping. There are currently two major approaches for quantitative imaging of tilts in scanning transmission electron microscopy (STEM), bright field (BF) and annular bright field (ABF). In this paper, we show that BF STEM can be reliably used for measurements of oxygen octahedral tilts. While optimal conditions for BF imaging are more restricted with respect to sample thickness and defocus, we find that BF imaging with an aberration-corrected microscope with the accelerating voltage of 300kV gives us the most accurate quantitative measurement of the oxygen column positions. Using the tilted perovskite structure of BiFeO₃ (BFO) as our test sample, we simulate BF and ABF images in a wide range of conditions, identifying the optimal imaging conditions for each mode. We show that unlike ABF imaging, BF imaging remains directly quantitatively interpretable for a wide range of the specimen mistilt, suggesting that it should be preferable to the ABF STEM imaging for quantitative structure determination.

Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting

Scanning transmission electron microscopy (STEM) data with atomic resolution can contain a large amount of information about the structure of a crystalline material. Often, this information is hard to extract, due to the large number of atomic columns and large differences in intensity from sublattices consisting of different elements. In this work, we present a free and open source software tool for analysing both the position and shapes of atomic columns in STEM-images, using 2-D elliptical Gaussian distributions. The software is tested on variants of the perovskite oxide structure. By first fitting the most intense atomic columns and then subtracting them, information on all the projected sublattices can be obtained. From this, we can extract changes in the lattice parameters and shape of A-cation columns from annular dark field images of perovskite oxide heterostructures. Using annular bright field images, shifts in oxygen column positions are also quantified in the same heterostructure. The precision of determining the position of atomic columns is compared between STEM data acquired using standard acquisition, and STEM-images obtained as an image stack averaged after using non-rigid registration.