Z-contrast Imaging Research Articles

Ultrahigh Performance in Lead-Free Piezoceramics Utilizing a Relaxor Slush Polar State with Multiphase Coexistence.

Owing to growing environmental concerns, the development of lead-free piezoelectrics with comparable performance to the benchmark Pb(Zr,Ti)O3 (PZT) becomes of great urgency. However, a further enhancement of lead-free piezoelectrics based on existing strategies has reached a bottleneck. Here we achieve a slush polar state with multiphase coexistence in lead-free potassium-sodium niobate (KNN) piezoceramics, which shows a novel relaxor behavior, i.e., frequency dispersion at the transition between different ferroelectric phases. It is very different from the conventional relaxor behavior which occurs at the paraelectric-ferroelectric phase transition. We obtain an ultrahigh piezoelectric coefficient (d33) of 650 ± 20 pC/N, the largest value of nontextured KNN-based ceramics, outperforming that of the commercialized PZT-5H. Atomic-resolution polarization mapping by Z-contrast imaging from different orientations reveals the entire material to comprise polar nanoregions with multiphase coexistence, which is again very different from conventional ferroelectric relaxors which have polar domains within a nonpolar matrix. Theoretical simulations validate the significantly decreased energy barrier and polarization anisotropy, which is facilitated by the high-density domain boundaries with easy polarization rotation bridging the multiphase-coexisting nanodomains. This work demonstrates a new strategy for designing lead-free piezoelectrics with further enhanced performance, which should also be applicable to other functional materials requiring a slush (flexible) state with respect to external stimulus.

Direct Observation of Heavy Metals and Impurities in Minerals Using Z-contrast Imaging

Direct Observation of Heavy Metals and Impurities in Minerals Using Z-contrast Imaging

Ab initio determination of atomic structure of Zn-Zr precipitates in a Mg-Nd-Zn-Zr alloy.

The atomic structure of nanometre-sized Zn-Zr precipitates in a Mg alloy is determined by combining tilt series of micro-beam electron diffraction with atomic resolution Z-contrast imaging. The stoichiometry of the Zn-Zr precipitates is Zn2Zr3 with a primitive tetragonal structure (space group P42/mnm, a = b = 0.761 nm, c = 0.682 nm). There are 20 atoms in the unit cell of tetragonal Zn2Zr3, comprising 12 Zr atoms at the 4d, 4f, 4g positions and eight Zn atoms at the 8j positions.

Pushing the limits of electrostatic adsorption: charge enhanced dry impregnation of SBA-15

Abstract Charge enhanced dry impregnation (CEDI) is a method to synthesize supported metal nanoparticles which combines the simplicity of incipient wetness impregnation with the small particle size obtained from electrostatic adsorption of metal precursors onto the oxide support. We have explored the utility of CEDI by applying it to a difficult to impregnate support – a largely one dimensional porous SBA-15 silica. Monometallic (Pt, Pd, Co, Ni, and Cu) catalysts at multiple metal loadings (1–20 wt%) as well as their bimetallic pairs were supported on mesoporous SBA-15 and characterized by high sensitivity powder XRD and in select formulations, with aberration-corrected z-contrast STEM imaging. CEDI applied to SBA-15 without washing is more effective than dry impregnation (DI) of SBA-15. Compared to amorphous silica, CEDI of SBA-15 without washing gives larger particles at lower metal loadings, while at higher metal loadings, the pores of the SBA-15 help render the particle size smaller than amorphous silica. CEDI without washing of SBA-15 with nitrate salts gives somewhat smaller particles than CEDI with chloride salts. CEDI with washing to remove residual counterions of the metal salt typically gives nanoparticles smaller than 2 nm. The smallest particles are always obtained when the counterion is removed by washing, or when a hydroxide salt is employed; ultrasmall particles are obtained without washing in this case.

Copper-Arsenic Nanoparticles in Hematite: Fingerprinting Fluid-Mineral Interaction

Metal nanoparticles (NP) in minerals are an emerging field of research. Development of advanced analytical techniques such as Z-contrast imaging and mapping using high-angle annular dark field scanning transmission electron microscopy (HAADF STEM) allows unparalleled insights at the nanoscale. Moreover, the technique provides a link between micron-scale textures and chemical patterns if the sample is extracted in situ from a location of petrogenetic interest. Here we use HAADF STEM imaging and energy-dispersive X-ray spectrometry (EDX) mapping/spot analysis on focused ion beam prepared foils to characterise atypical Cu-As-zoned and weave-twinned hematite from the Olympic Dam deposit, South Australia. We aim to determine the role of solid-solution versus the presence of discrete included NPs in the observed zoning and to understand Cu-As-enrichment processes. Relative to the grain surface, the Cu-As bands extend in depth as (sub)vertical trails of opposite orientation, with Si-bearing hematite NP inclusions on one side and coarser cavities (up to hundreds of nm) on the other. The latter host Cu and Cu-As NPs, contain mappable K, Cl, and C, and display internal voids with rounded morphologies. Aside from STEM-EDX mapping, the agglomeration of native copper NPs was also assessed by high-resolution imaging. Collectively, such characteristics, corroborated with the geometrical outlines and negative crystal shapes of the cavities, infer that these are opened fluid inclusions with NPs attached to inclusion walls. Hematite along the trails features distinct nanoscale domains with lattice defects (twins, 2-fold superstructuring) relative to hematite outside the trails, indicating this is a nanoprecipitate formed during replacement processes, i.e., coupled dissolution and reprecipitation reactions (CDRR). Transient porosity intrinsically developed during CDRR can trap fluids and metals. Needle-shaped and platelet Cu-As NPs are also observed along (sub)horizontal bands along which Si, Al and K is traceable along the margins. The same signature is depicted along nm-wide planes crosscutting at 60° and offsetting (012)-twins in weave-twinned hematite. High-resolution imaging shows linear and planar defects, kink deformation along the twin planes, misorientation and lattice dilation around duplexes of Si-Al-K-planes. Such defects are evidence of strain, induced during fluid percolation along channels that become wider and host sericite platelets, as well as Cl-K-bearing inclusions, comparable with those from the Cu-As-zoned hematite, although without metal NPs. The Cu-As-bands mapped in hematite correspond to discrete NPs formed during interaction with fluids that changed in composition from alkali-silicic to Cl- and metal-bearing brines, and to fluid rates that evolved from slow infiltration to erratic inflow controlled by fault-valve mechanism pumping. This explains the presence of Cu-As NPs hosted either along Si-Al-K-planes (fluid supersaturation), or in fluid inclusions (phase separation during depressurisation) as well as the common signatures observed in hematite with variable degrees of fluid-mineral interaction. The invoked fluids are typical of hydrolytic alteration and the fluid pumping mechanism is feasible via fault (re)activation. Using a nanoscale approach, we show that fluid-mineral interaction can be fingerprinted at the (atomic) scale at which element exchange occurs.

A New Approach To Quantify the Ordering State of Protodolomite Using XRD, TEM, and Z-Contrast Imaging

A New Approach To Quantify the Ordering State of Protodolomite Using XRD, TEM, and Z-Contrast Imaging

Deep Learning for Defects Analysis and Atomic-resolution Imaging of Battery Materials

The primary objective of this work is to utilize machine learning techniques, in particular a deep learning method, to explore structural details of various components of Li batteries. Layered oxide cathodes (e.g., NMC, LCO) have been known as the bottleneck of Li-ion batteries and multiple degradation mechanisms such as, irreversible phase transition, transition metal (e.g., Ni, Mn) migration, metal dissolution, surface decomposition and oxygen release have been realized as main contributors to the capacity decay of such cathode materials. Transition metal migration, which is regarded as the displacement of transition metal cations to Li vacancies during charge process, has been detected by advanced aberration corrected scanning transmission electron microscopy (AC-STEM). The AC-STEM z-contrast imaging allows for distinguishing transition metals from lighter species such as O and Li atoms with sub-angstrom spatial resolution. Nonetheless, this method cannot quantify the fraction of migrated transition metals to measure and compare the extent of degradation among various samples. This challenge has significantly obstructed the research and advancement of layered oxide cathodes and Li-ion batteries. The other area of interest is noble metal nanometer clusters (NCs), which play a crucial role in variety of battery types (e.g., Li-oxygen batteries). The position of atoms and the structure of NCs governs the unique size-dependent functionalities and hence their applications towards the desired electrochemical properties and mechanics. Thus, it is of imperative importance to evaluate NCs structures and atomic column heights for more profound understanding of their structure-properties relation. Employing AC-STEM and HRTEM the structure of these NCs could be evaluated. However, the determination of the atomic column heights is challenging due to uncertainty of microscope parameters and a noise in experimental data. To overcome these challenges in both of the applications of atomic resolution imaging as described above, we have developed a deep learning algorithm based upon the convolutional neural network (CNN). This work extends and improves the previously developed CNN1 by integrating predictive capabilities toward the detection of atomic column heights in complex NCs independent of noise and defocus in experimental measurements. In addition, an improved algorithm for vacancy detections in NMC cathodes is developed and applied. In both the cases (Li vacancies in NMC and atomic column height detection in NCs), the CNN is trained and labeled on 10000 HRTEM images obtained using the Atomic Simulation Environment2 and the QSTEM3 code. The artificial creation of the train data is beneficial for the training of the CNN, since it contains the absolute reliable ground truth against which labels are assigned. For atomic column heights evaluation two different methods of column heights prediction are proposed, resulting in alternative labeling of the computer-generated training data. Consequently, such a trained model is applied towards the detection of atomic column heights in experimentally measured NCs. A good prediction is obtained enabling fast and reliable analysis of variety of experimental measurements. In the case of Li vacancies identification, the model is able to find complex vacancy positions in the experimentally measured NMC layered structures allowing to analyze Li/Ni interaction. Consequently, the results of this combined spectroscopic and deep learning techniques can be used in density functional theory (DFT) to calculate the magnetic frustration in NMC structures. The developed CNN is based upon a U-Net architecture, which has some drawbacks comparing to inception networks such as GoogLeNet. Hence, we have also adapted inception type networks and compared them against a U-Net type. To summarize, in addition to improving the fidelity of the CNN model, the present study allows for a mechanistic interpretation of the origin of capacity fade of layered oxide cathodes as well as detection of atomic column heights in NCs for better structure-properties relation identification.

Spectroscopic signatures of edge states in hexagonal boron nitride

We use Z-contrast imaging and atomically resolved electron energy-loss spectroscopy on an aberration-corrected scanning transmission electron microscope to investigate the local electronic states of boron atoms at different edge structures in monolayer and bilayer h-BN. We find that edges with bonding unsaturated sp2 boron atoms have a unique spectroscopic signature with a prominent pre-peak at ∼ 190.2 eV in the B K-edge fine structure. First-principles calculations reveal that the observed pre-peak arises from excitations to the in-plane lowest-energy empty sp2 boron dangling bonds at the B-terminated edge. This spectroscopic signature can serve as a fingerprint to explore new edge structures in h-BN.

New insights into nanostructure and geochemistry of bioapatite in REE-rich deep-sea sediments: LA-ICP-MS, TEM, and Z-contrast imaging studies

Rare earth elements (REE) and yttrium (Y), termed as REY, are recently found to be extremely enriched in some pelagic sediments, which could be an important resource for REY in the future. However, their enrichment mechanism remains controversial. Because biogenetic apatite is one of the most important REY carriers in REY-rich deep-sea sediment, it is critical to identify its mineralogical and geochemical characteristics by using combined methods of in situ chemical analysis and atomic resolution chemical imaging.Scanning electron microscope and transmission electron microscopy studies reveal that bioapatite fossils mainly consist of aligned hydroxyapatite nano-plates. Laser ablation-inductively coupled plasma-mass spectrometry analyses show that the REY are not uniformly distributed within the studied bioapatite fossils. Concentration profiles from the measurements and modeling analyses indicate that the major REY should be incorporated into the bioapatite fossil from seawater as well as the pore water during the early stage of diagenesis. Z-contrast imaging results reveal the following two possible coupled substitutions in the apatite: REE3+ + Na+ ↔ 2Ca2+ and/or REE3+ + Si4+ ↔ Ca2+ + P5+, which is distinguished from those ion-absorption-type REE deposits on land. Our study indicates that bioapatite fossils are prone to undergo alteration during diagenesis, and thus cautious examination should be taken when applying REE signal of bioapatite as a proxy for palaeo-ocean environmental reconstruction.

Corrigendum to: Twinned/untwinned catalytic gold nanoparticles identified by applying a convolutional neural network to their Hough transformed Z-contrast images.

In this article, we demonstrate that a convolutional neural network (CNN) can be effectively used to determine the presence of twins in the atomic resolution scanning transmission electron microscopy (STEM) images of catalytic Au nanoparticles. In particular, the CNN screening of Hough transformed images resulted in significantly higher accuracy rates as compared to those obtained by applying this technique to the raw STEM images. The proposed method can be utilized for evaluating the statistical twining fraction of Au nanoparticles that strongly affects their catalytic activity.

Phonon Spectroscopy at Atomic Resolution.

Advances in source monochromation in transmission electron microscopy have opened up new possibilities for investigations of condensed matter using the phonon-loss sector of the energy-loss spectrum. Here, we explore the spatial variations of the spectrum as an atomic-sized probe is scanned across a thin flake of hexagonal boron nitride. We demonstrate that phonon spectral mapping of atomic structure is possible. These results are consistent with a model for the quantum excitation of phonons and confirm that Z-contrast imaging is based on inelastic scattering associated with phonon excitation.

Hot Deformation and Dynamic Recrystallization in Titanium Aluminide

The hot workability of gamma titanium aluminide alloy, Ti-48Al-2V-2Nb, was assessed in the cast condition through a series of compression tests conducted over a range of temperatures (1000 to 1175 °C) and at the strain rate of 10 S-1. The mechanism of dynamics recrystallization has been investigated from SEM Z-contrast images and from the Electron backscattered diffraction EBSD as well. It has been observed that volume fraction of the recrystallized grains increases with increasing the deformation temperature. The major volume fraction of the recrystallized grains was observed in the shear band which was forming at an angle 45 ̊ with respect to the compression direction. The mechanism of breaking of the laths and the region of the dynamic recrystallization were also investigated from the SEM Z-contrast image and EBSD. The dynamic recrystallization occurred in the region of the broken laths and shear bands. The breaking of the laths was because of the kinking of the lamellae. The shear band, kinked lamellae and dynamic recrystallized region where all investigated simultaneously.

Annealing induced structural alternations in yttria partially stabilized zirconia

Annealing-induced microstructural changes in yttria partially stabilized zirconia (YSZ) have been investigated by scanning transmission electron microscopy combined with computer simulation. It is shown that the high-temperature annealing results in the formation of voids in YSZ and structural ordering in the surrounding area of the voids. Atomic-scale Z-contrast imaging shows one-dimensional distortion of the cation sub-lattice by alternate arrangement of narrow and wide (100) planes of the cation sub-lattice along the [100] direction of the cubic ZrO2 structure. Such distortion of the cation sub-lattice is attributed to the 1/4[001] displacement of the oxygen atoms in the (100) plane, which is confirmed experimentally by annual bright field imaging along with the density-functional theory and computer simulations of the atomic-scale Z-contrast imaging and electron diffraction.

Experimental and DFT characterization of η′ nano-phase and its interfaces in Al[sbnd]Zn[sbnd]Mg[sbnd]Cu alloys

The structures and energetics of η′ nano-phase and its interfaces in a peak-aged AlZnMgCu alloy were thoroughly investigated, using the combination of aberration corrected HAADF-STEM imaging and first-principles calculations. The most feasible atomic structure of η′, along with the solute substitution in η′, were calculated and compared with the atom resolution Z-contrast images. The interface phase diagram of η′/Al was constructed as a function of the excess chemical potential of Zn, to determine the equilibrium interface structures. Solute segregation to these interfaces was further calculated, and the results were adopted to interpret the experimental Z-contrast images. Finally, all the bulk and interface results were integrated to predict the solute partition in the matrix and further its potential impacts on interface properties, and based on which, a new strategy was proposed for future optimal design of AlZnMgCu alloys.

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.

Twinned/untwinned catalytic gold nanoparticles identified by applying a convolutional neural network to their Hough transformed Z-contrast images.

In this article, we demonstrate that a convolutional neural network (CNN) can be effectively used to determine the presence of twins in the atomic resolution scanning transmission electron microscopy (STEM) images of catalytic Au nanoparticles. In particular, the CNN screening of Hough transformed images resulted in significantly higher accuracy rates as compared to those obtained by applying this technique to the raw STEM images. The proposed method can be utilized for evaluating the statistical twining fraction of Au nanoparticles that strongly affects their catalytic activity.

Progress and prospects of aberration-corrected STEM for functional materials

Aberration-corrected scanning transmission electron microscopy (STEM) provides real space imaging and spectroscopy at atomic resolution with a new level of sensitivity to structure, bonding, elemental valence and even dynamics. It has developed into the most powerful characterization and even fabrication platform for all materials, especially for functional materials with complex structural features that dynamically respond to external fields. Several representative examples of functional materials are shown, including piezoelectric and photoelectric materials, functional oxide interfaces, metal–organic framework (MOF)-derived transition metal oxide/phosphide catalysts and two-dimensional (2D) materials. In piezoelectric systems, atomic-resolution polarization mapping by Z-contrast imaging shows the intimate coexistence of two ferroelectric phases inside nanodomains. Quantitative STEM imaging and EELS spectroscopy reveal the underlying mechanism of the exotic coupling between polarization and charge at a functional oxide interface. Under the low-voltage STEM, defects in 2D materials are clearly visible, for example novel edges and single atom dopants. The dynamic behavior of single atoms in vacancies of monolayer MoS2 is shown to highlight the electron-beam induced nanofabrication ability of aberration-corrected STEM. Thanks to the rapid development of segmented/pixelated detectors, differential phase contrast and 4D STEM techniques are promising for the near future, providing more opportunities to understand the link between structure and functionality.

Atomic structure and migration dynamics of MoS2/LixMoS2 interface

The performance of alkali-metal-ion batteries largely depends on the migration behavior of alkali metal ions in the electrodes. Probing the atomic structure of the reaction interface and the dynamic process during ion transport in the electrodes will help better understand the underlying electrochemical mechanisms and inspire rational electrode designs. In this study, by combining in situ transmission electron microscopy (TEM) and aberration-corrected scanning TEM (STEM), we track the reversible lithium ion transport in MoS2 nanostructures to reveal the atomic structure and dynamic behaviors of the reaction interface. We find that lithium ions insertion triggers complex phase transformations. Three different phases co-exist at the interface: a pristine 2H phase, a 1T phase with a shrank lattice constant of − 3.3% ( ± 2.3%), and a distorted 1T phase (called 1Tˊ phase) with an expanded lattice constant of 5.5% ( ± 2.5%). The atomically resolved Z-contrast image shows that the expanded 1Tˊ phase has distorted Mo arrangements. Furthermore, the lithium ions migration causes defects at the reaction front, and the diffusion on the surface is faster than that inside, forming a core-shell structure at the reaction interface. The diffusivity of lithium ions is directly measured to be ~1000–30,000 nm2/s, which is significantly higher than that of sodium insertion (~10–20 nm2/s). The atomic-scale observations of lithium-ion-migration-induced complex structural evolutions would help understand the properties of MoS2 nanostructures and shed light on the design of alkali-metal-ion batteries with general transition-metal dichalcogenide electrodes.

Concurrent La and A-Site Vacancy Doping Modulates the Thermoelectric Response of SrTiO3: Experimental and Computational Evidence.

To help understand the factors controlling the performance of one of the most promising n-type oxide thermoelectric SrTiO3, we need to explore structural control at the atomic level. In Sr1-xLa2x/3TiO3 ceramics (0.0 ≤ x ≤ 0.9), we determined that the thermal conductivity can be reduced and controlled through an interplay of La-substitution and A-site vacancies and the formation of a layered structure. The decrease in thermal conductivity with La and A-site vacancy substitution dominates the trend in the overall thermoelectric response. The maximum dimensionless figure of merit is 0.27 at 1070 K for composition x = 0.50 where half of the A-sites are occupied with La and vacancies. Atomic resolution Z-contrast imaging and atomic scale chemical analysis show that as the La content increases, A-site vacancies initially distribute randomly (x < 0.3), then cluster (x ≈ 0.5), and finally form layers (x = 0.9). The layering is accompanied by a structural phase transformation from cubic to orthorhombic and the formation of 90° rotational twins and antiphase boundaries, leading to the formation of localized supercells. The distribution of La and A-site vacancies contributes to a nonuniform distribution of atomic scale features. This combination induces temperature stable behavior in the material and reduces thermal conductivity, an important route to enhancement of the thermoelectric performance. A computational study confirmed that the thermal conductivity of SrTiO3 is lowered by the introduction of La and A-site vacancies as shown by the experiments. The modeling supports that a critical mass of A-site vacancies is needed to reduce thermal conductivity and that the arrangement of La, Sr, and A-site vacancies has a significant impact on thermal conductivity only at high La concentration.

Strategy for reliable strain measurement in InAs/GaAs materials from high-resolution Z-contrast STEM images

Geometric phase analysis (GPA), a fast and simple Fourier space method for strain analysis, can give useful information on accumulated strain and defect propagation in multiple layers of semiconductors, including quantum dot materials. In this work, GPA has been applied to high resolution Z-contrast scanning transmission electron microscopy (STEM) images. Strain maps determined from different g vectors of these images are compared to each other, in order to analyze and assess the GPA technique in terms of accuracy. The SmartAlign tool has been used to improve the STEM image quality getting more reliable results. Strain maps from template matching as a real space approach are compared with strain maps from GPA, and it is discussed that a real space analysis is a better approach than GPA for aberration corrected STEM images.