Chemically induced Jahn-Teller ordering on manganite surfaces

Resurrected and Tunable Conductivity and Ferromagnetism in the Secondary Growth La0.7Ca0.3MnO3 on Transferred SrTiO3 Membranes

To avoid the epitaxy dilemma in various thin films, such as complex oxide, silicon, organic, metal/alloy, etc., their stacking at an atomic level and secondary growth are highly desired to maximize the functionality of a promising electronic device. The ceramic nature of complex oxides and the demand for accurate and long-range-ordered stoichiometry face severe challenges. Here, the transport and magnetic properties of the La0.7Ca0.3MnO3 (LCMO) secondary growth on single-crystal freestanding SrTiO3 (STO) membranes are demonstrated. It has been experimentally found that on an only 10 nm thick STO membrane, the LCMO can offer a bulk-like Curie temperature (TC) of 253 K and negative magnetoresistance of -64%, with a weak dependence on the thickness. The resurrected conductivity and ferromagnetism in LCMO confirm the advantages of secondary growth, which benefits from the excellent flexibility and transferability. Additionally, this study explores the integration strategy of complex oxides with other functional materials.

Depth-Resolved Phase Analysis of Expanded Austenite Formed in Austenitic Stainless Steel

Expanded austenite γN formed after nitrogen insertion into austenitic stainless steel and CoCr alloys is known as a hard and very wear resistant phase. Nevertheless, no single composition and lattice expansion can describe this phase with nitrogen in solid solution. Using in situ X-ray diffraction (XRD) during ion beam sputtering of expanded austenite allows a detailed depth-dependent phase analysis, correlated with the nitrogen depth profiles obtained by time-of-flight secondary ion mass spectrometry (ToF-SIMS) or glow discharge optical emission spectroscopy (GDOES). Additionally, in-plane XRD measurements at selected depths were performed for strain analysis. Surprisingly, an anomalous peak splitting for the (200) expanded peak was observed for some samples during nitriding and sputter etching, indicating a layered structure only for {200} oriented grains. The strain analysis as a function of depth and orientation of scattering vector (parallel/perpendicular to the surface) is inconclusive.

Surface termination and stoichiometry of LaAlO3(001) surface studied by HRTEM

As an important topic of condensed matter physics, metal oxide surfaces often exhibit exotic properties such as high catalytic activity, enhanced ferroelectricity and electronic phase transition, originating from the different local symmetry with respect to the bulk. As the structure determination of oxide surfaces presents challenges to conventional surface science techniques like scanning tunneling microscopy, aberration-corrected transmission electron microscopy (TEM) has been increasingly used to solve structures of oxide surfaces. In this work, the (001) surface of LaAlO₃, one of the most used components of oxide heterostructures, has been investigated. Our TEM experiments and extensive image simulations show that the La-O terminated LaAlO₃(001) surface undergoes significant reconstructions, forming La vacancies on the surface layer. Energetically, the LaAlO₃(001) surface is stable with the reconstructed La-O termination in a wide range of oxygen chemical potentials. Polarity compensation, reduced density of states at the Fermi level and bond enhancement of subsurface oxygen anions all contribute to the stabilization of the reconstructed surface.

Sub-lattice of Jahn-Teller centers in hexaferrite crystal

A novel type of sub-lattice of the Jahn-Teller (JT) centers was arranged in Ti-doped barium hexaferrite BaFe₁₂O₁₉. In the un-doped crystal all iron ions, sitting in five different crystallographic positions, are Fe³⁺ in the high-spin configuration (S = 5/2) and have a non-degenerate ground state. We show that the electron-donor Ti substitution converts the ions to Fe²⁺ predominantly in tetrahedral coordination, resulting in doubly-degenerate states subject to the [Formula: see text] problem of the JT effect. The arranged JT complexes, Fe²⁺O₄, their adiabatic potential energy, non-linear and quantum dynamics, have been studied by means of ultrasound and terahertz-infrared spectroscopies. The JT complexes are sensitive to external stress and applied magnetic field. For that reason, the properties of the doped crystal can be controlled by the amount and state of the JT complexes.

Learning from Imperfections: Predicting Structure and Thermodynamics from Atomic Imaging of Fluctuations

In materials characterization, traditionally a single experimental sample is used to derive information about a single point in the composition space, while the imperfections, impurities, and stochastic details of material structure are deemed irrelevant or complicating factors in the analysis. Here we demonstrate that atomic-scale studies of a single nominal composition can provide information about microstructures and thermodynamic response over a finite area of chemical space. Using the principles of statistical inference, we develop a framework for incorporating structural fluctuations into statistical mechanical models and use it to solve the inverse problem of deriving effective interatomic interactions responsible for elemental segregation in a La_5/8Ca_3/8MnO₃ thin film. The results are further analyzed by a variational autoencoder to detect anomalous behavior in the composition phase diagram. This study provides a framework for creating generative models from a combination of multiple experimental data and provides direct insight into the driving forces for cation segregation in manganites.

Feature extraction via similarity search: application to atom finding and denoising in electron and scanning probe microscopy imaging

We develop an algorithm for feature extraction based on structural similarity and demonstrate its application for atom and pattern finding in high-resolution electron and scanning probe microscopy images. The use of the combined local identifiers formed from an image subset and appended Fourier, or other transform, allows tuning selectivity to specific patterns based on the nature of the recognition task. The proposed algorithm is implemented in Pycroscopy, a community-driven scientific data analysis package, and is accessible through an interactive Jupyter notebook available on GitHub.

Quasiparticle Interference on Cubic Perovskite Oxide Surfaces

We report the observation of coherent surface states on cubic perovskite oxide SrVO_{3}(001) thin films through spectroscopic-imaging scanning tunneling microscopy. A direct link between the observed quasiparticle interference patterns and the formation of a d_{xy}-derived surface state is supported by first-principles calculations. We show that the apical oxygens on the topmost VO_{2} plane play a critical role in controlling the coherent surface state via modulating orbital state.

Effect of Surface Morphology and Magnetic Impurities on the Electronic Structure in Cobalt-Doped BaFe2As2 Superconductors

Combined scanning tunneling microscopy, spectroscopy, and local barrier height (LBH) studies show that low-temperature-cleaved optimally doped Ba(Fe_1-xCo_x)₂As₂ crystals with x = 0.06, with T_c = 22 K, have complicated morphologies. Although the cleavage surface and hence the morphologies are variable, the superconducting gap maps show the same gap widths and nanometer size inhomogeneities irrelevant to the morphology. Based on the spectroscopy and LBH maps, the bright patches and dark stripes in the morphologies are identified as Ba- and As-dominated surface terminations, respectively. Magnetic impurities, possibly due to Co or Fe atoms, are believed to create local in-gap state and, in addition, suppress the superconducting coherence peaks. This study will clarify the confusion on the cleavage surface terminations of the Fe-based superconductors and its relation with the electronic structures.

Atomistic study of the alloying behavior of crystalline SnSe1−xSx

The alloying behavior of crystalline SnSe_1−xS_x was investigated at the atomic level by combining STM experiments and DFT calculations.

Identifying local structural states in atomic imaging by computer vision

The availability of atomically resolved imaging modalities enables an unprecedented view into the local structural states of materials, which manifest themselves by deviations from the fundamental assumptions of periodicity and symmetry. Consequently, approaches that aim to extract these local structural states from atomic imaging data with minimal assumptions regarding the average crystallographic configuration of a material are indispensable to advances in structural and chemical investigations of materials. Here, we present an approach to identify and classify local structural states that is rooted in computer vision. This approach introduces a definition of a structural state that is composed of both local and nonlocal information extracted from atomically resolved images, and is wholly untethered from the familiar concepts of symmetry and periodicity. Instead, this approach relies on computer vision techniques such as feature detection, and concepts such as scale invariance. We present the fundamental aspects of local structural state extraction and classification by application to simulated scanning transmission electron microscopy images, and analyze the robustness of this approach in the presence of common instrumental factors such as noise, limited spatial resolution, and weak contrast. Finally, we apply this computer vision-based approach for the unsupervised detection and classification of local structural states in an experimental electron micrograph of a complex oxides interface, and a scanning tunneling micrograph of a defect-engineered multilayer graphene surface.

Identification of phases, symmetries and defects through local crystallography

Advances in electron and probe microscopies allow 10 pm or higher precision in measurements of atomic positions. This level of fidelity is sufficient to correlate the length (and hence energy) of bonds, as well as bond angles to functional properties of materials. Traditionally, this relied on mapping locally measured parameters to macroscopic variables, for example, average unit cell. This description effectively ignores the information contained in the microscopic degrees of freedom available in a high-resolution image. Here we introduce an approach for local analysis of material structure based on statistical analysis of individual atomic neighbourhoods. Clustering and multivariate algorithms such as principal component analysis explore the connectivity of lattice and bond structure, as well as identify minute structural distortions, thus allowing for chemical description and identification of phases. This analysis lays the framework for building image genomes and structure–property libraries, based on conjoining structural and spectral realms through local atomic behaviour.

High-resolution microscopy methods provide a rich source of information, and allow highly precise measurements of atomic coordinates. Here, the authors report a method for quantitative analysis of material structures using multivariate statistical analysis to identify and distinguish various phases, defects and symmetries.