A Methodology for Robust Multislice Ptychography.

While multislice electron ptychography can provide thermal vibration limited resolution and structural information in 3D, it relies on properly selecting many intertwined acquisition and computational parameters. Here, we outline a methodology for selecting acquisition parameters to enable robust ptychographic reconstructions. We develop two physically informed metrics, areal oversampling and Ronchigram magnification, to describe the selection of these parameters in multislice ptychography. Through simulations, we comprehensively evaluate the validity of these two metrics over a broad range of conditions and show that they accurately guide reconstruction success. Further, we validate these conclusions with experimental ptychographic data and demonstrate close agreement between trends in simulated and experimental data. Using these metrics, we achieve experimental multislice reconstructions at a scan step of 2.1Å/px, enabling large field-of-view, data-efficient reconstructions. These experimental design principles enable the routine and robust use of multislice ptychography for 3D characterization of materials at the atomic scale.

Clamping enables enhanced electromechanical responses in antiferroelectric thin films.

Thin-film materials with large electromechanical responses are fundamental enablers of next-generation micro-/nano-electromechanical applications. Conventional electromechanical materials (for example, ferroelectrics and relaxors), however, exhibit severely degraded responses when scaled down to submicrometre-thick films due to substrate constraints (clamping). This limitation is overcome, and substantial electromechanical responses in antiferroelectric thin films are achieved through an unconventional coupling of the field-induced antiferroelectric-to-ferroelectric phase transition and the substrate constraints. A detilting of the oxygen octahedra and lattice-volume expansion in all dimensions are observed commensurate with the phase transition using operando electron microscopy, such that the in-plane clamping further enhances the out-of-plane expansion, as rationalized using first-principles calculations. In turn, a non-traditional thickness scaling is realized wherein an electromechanical strain (1.7%) is produced from a model antiferroelectric PbZrO3 film that is just 100 nm thick. The high performance and understanding of the mechanism provide a promising pathway to develop high-performance micro-/nano-electromechanical systems.

Modeling Temperature-Dependent Electron Thermal Diffuse Scattering via Machine-Learned Interatomic Potentials and Path-Integral Molecular Dynamics.

Electron thermal diffuse scattering is shown to be sensitive to subtle changes in atomic vibrations and shows promise in assessing lattice dynamics at nanometer resolution. Here, we demonstrate that machine-learned interatomic potentials (MLIPs) and path-integral molecular dynamics can accurately capture the potential energy landscape and lattice dynamics needed to describe electron thermal diffuse scattering. Using SrTiO_{3} as a test bed at cryogenic and room temperatures, we compare electron thermal diffuse scattering simulations using different approximations to incorporate thermal motion. Only when the simulations are based on quantum mechanically accurate MLIPs in combination with path-integral molecular dynamics that include nuclear quantum effects is there excellent agreement with experiments.

Tunable Artificial Relaxor Behavior in [BaTiO_{3}]_{m}/[BaZrO_{3}]_{n} Superlattices.

[BaTiO_{3}]_{m}/[BaZrO_{3}]_{n} (m, n=4-12) superlattices are used to demonstrate the fabrication and deterministic control of an artificial relaxor. X-ray diffraction and atomic-resolution imaging studies confirm the production of high-quality heterostructures. With decreasing BaTiO_{3} layer thickness, dielectric measurements reveal systematically lower dielectric-maximum temperatures, while hysteresis loops and third-harmonic nonlinearity studies suggest a transition from ferroelectriclike to relaxorlike behavior driven by tuning the random-field strength. This system provides a novel platform for studying the size effect and interaction length scale of the nanoscale-polar structures in relaxors.

Machine Learning-Enabled Superior Energy Storage in Ferroelectric Films with a Slush-Like Polar State.

Heterogeneities in structure and polarization have been employed to enhance the energy storage properties of ferroelectric films. The presence of nonpolar phases, however, weakens the net polarization. Here, we achieve a slush-like polar state with fine domains of different ferroelectric polar phases by narrowing the large combinatorial space of likely candidates using machine learning methods. The formation of the slush-like polar state at the nanoscale in cation-doped BaTiO3 films is simulated by phase field simulation and confirmed by aberration-corrected scanning transmission electron microscopy. The large polarization and the delayed polarization saturation lead to greatly enhanced energy density of 80 J/cm3 and transfer efficiency of 85% over a wide temperature range. Such a data-driven design recipe for a slush-like polar state is generally applicable to quickly optimize functionalities of ferroelectric materials.

Tuning Surface Acidity of Mixed Conducting Electrodes: Recovery of Si-Induced Degradation of Oxygen Exchange Rate and Area Specific Resistance.

Metal oxides are an important class of functional materials, and for many applications, ranging from solid oxide fuel/electrolysis cells, oxygen permeation membranes, and oxygen storage materials to gas sensors (semiconducting and electrolytic) and catalysts, the interaction between the surface and oxygen in the gas phase is central. Ubiquitous Si-impurities are known to impede this interaction, commonly attributed to the formation of glassy blocking layers on the surface. Here, the surface oxygen exchange coefficient (kchem ) is examined for Pr0.1 Ce0.9 O2-δ (PCO), a model mixed ionic electronic conductor, via electrical conductivity relaxation measurements, and the area-specific resistance (ASR) by electrochemical impedance spectroscopy. It is demonstrated that even low silica levels, introduced by infiltration, depress kchem by a factor 4000, while the ASR increases 40-fold and we attribute this to its acidity relative to that of PCO. The ability to fully regenerate the poisoned surface by the subsequent addition of basic Ca- or Li-species is further shown. This ability to not only recover Si-poisoned surfaces by tuning the relative surface acidity of an oxide surface, but subsequently outperform the pre-poisoned response, promises to extend the operating life of materials and devices for which the catalytic oxygen/solid interface reaction is central.

A comparison of molecular dynamics potentials used to account for thermal diffuse scattering in multislice simulations.

Here we investigate electron scattering simulations with thermal displacements incorporated using molecular dynamics potentials. Specifically, we explore the sensitivity of electron scattering to the phonon band structure, or more explicitly interatomic forces. Silicon serves as the model material where we introduce thermal atomic displacements via empirical and machine-learned molecular dynamics interatomic potentials and compare them to finite-temperature density functional theory interatomic forces. We demonstrate that when molecular dynamics potentials do not sufficiently reproduce the correct phonon band structure, significant errors in the simulated diffraction and image intensities can occur. Moreover, for Si, we find that multislice simulations using machine-learned interatomic potentials are more accurate than empirical ones. In addition to the selected atomic potential, we demonstrate that the sensitivity to the phonon band structure also depends on the crystal zone axis, which can be used to enhance sensitivity to thermal displacements. Finally, we provide a sensitivity analysis with angle-resolved scanning transmission electron microscopy (STEM) to enhance image sensitivity to the details of the phonon band structure.

Correlating local chemical and structural order using Geographic Information Systems-based spatial statistics.

Analysis of nanoscale short-range chemical and/or structural order via (scanning) transmission electron microscopy (S/TEM) imaging is fundamentally limited by projection of the three dimensional sample, which averages informational along the beam direction. Extracting statistically significant spatial correlations between the structure and chemistry determined from these two-dimensional datasets thus remains challenging. Here, we apply methods commonly used in Geographic Information Systems (GIS) to determine the spatial correlation between measures of local chemistry and structure from atomic-resolution STEM imaging of a compositionally complex relaxor, Pb(Mg1/3Nb2/3)O3 (PMN). The approach is used to determine the type of ordering present and to quantify the spatial variation of chemical order, oxygen octahedral distortions, and oxygen octahedral tilts. The extent of autocorrelation and inter-feature correlation among these short-range ordered regions are then evaluated through a spatial covariance analysis, showing correlation as a function of distance. The results demonstrate that integrating GIS tools for analyzing microscopy datasets can serve to unravel subtle relationships among chemical and structural features in complex materials that can be hidden when ignoring their spatial distributions.

Towards Augmented Microscopy with Reinforcement Learning-Enhanced Workflows.

Here, we report a case study implementation of reinforcement learning (RL) to automate operations in the scanning transmission electron microscopy workflow. To do so, we design a virtual, prototypical RL environment to test and develop a network to autonomously align the electron beam position without prior knowledge. Using this simulator, we evaluate the impact of environment design and algorithm hyperparameters on alignment accuracy and learning convergence, showing robust convergence across a wide hyperparameter space. Additionally, we deploy a successful model on the microscope to validate the approach and demonstrate the value of designing appropriate virtual environments. Consistent with simulated results, the on-microscope RL model achieves convergence to the goal alignment after minimal training. Overall, the results highlight that by taking advantage of RL, microscope operations can be automated without the need for extensive algorithm design, taking another step toward augmenting electron microscopy with machine learning methods.

Strong and Localized Luminescence from Interface Bubbles Between Stacked hBN Multilayers.

Extraordinary optoelectronic properties of van der Waals (vdW) heterostructures can be tuned via strain caused by mechanical deformation. Here, we demonstrate strong and localized luminescence in the ultraviolet region from interface bubbles between stacked multilayers of hexagonal boron nitride (hBN). Compared to bubbles in stacked monolayers, bubbles formed by stacking vdW multilayers show distinct mechanical behavior. We use this behavior to elucidate radius- and thickness-dependent bubble geometry and the resulting strain across the bubble, from which we establish the thickness-dependent bending rigidity of hBN multilayers. We then utilize the polymeric material confined within the bubbles to modify the bubble geometry under electron beam irradiation, resulting in strong luminescence and formation of optical standing waves. Our results open a route to design and modulate microscopic-scale optical cavities via strain engineering in vdW materials, which we suggest will be relevant to both fundamental mechanical studies and optoelectronic applications.

Exsolution-Driven Surface Transformation in the Host Oxide.

Exsolution synthesizes self-assembled metal nanoparticle catalysts via phase precipitation. An overlooked aspect in this method thus far is how exsolution affects the host oxide surface chemistry and structure. Such information is critical as the oxide itself can also contribute to the overall catalytic activity. Combining X-ray and electron probes, we investigated the surface transformation of thin-film SrTi0.65Fe0.35O3 during Fe0 exsolution. We found that exsolution generates a highly Fe-deficient near-surface layer of about 2 nm thick. Moreover, the originally single-crystalline oxide near-surface region became partially polycrystalline after exsolution. Such drastic transformations at the surface of the oxide are important because the exsolution-induced nonstoichiometry and grain boundaries can alter the oxide ion transport and oxygen exchange kinetics and, hence, the catalytic activity toward water splitting or hydrogen oxidation reactions. These findings highlight the need to consider the exsolved oxide surface, in addition to the metal nanoparticles, in designing the exsolved nanocatalysts.

Nanotwinning-assisted dynamic recrystallization at high strains and strain rates.

Grain refinement is a widely sought-after feature of many metal production processes and frequently involves a process of recrystallization. Some processing methods use very high strain rates and high strains to refine the grain structure into the nanocrystalline regime. However, grain refinement processes are not clear in these extreme conditions, which are hard to study systematically. Here, we access those extreme conditions of strain and strain rate using single copper microparticle impact events with a laser-induced particle impact tester. Using a combined dictionary-indexing electron backscatter diffraction and scanning transmission electron microscopy approach for postmortem characterization of impact sites, we systematically explore increasing strain levels and observe a recrystallization process that is facilitated by nanotwinning, which we term nanotwinning-assisted dynamic recrystallization. It achieves much finer grain sizes than established modes of recrystallization and therefore provides a pathway to the finest nanocrystalline grain sizes through extreme straining processes.

Entropy Landscaping of High-Entropy Carbides.

The entropy landscape of high-entropy carbides can be used to understand and predict their structure, properties, and stability. Using first principles calculations, the individual and temperature-dependent contributions of vibrational, electronic, and configurational entropies are analyzed, and compare them qualitatively to the enthalpies of mixing. As an experimental complement, high-entropy carbide thin films are synthesized with high power impulse magnetron sputtering to assess structure and properties. All compositions can be stabilized in the single-phase state despite finite positive, and in some cases substantial, enthalpies of mixing. Density functional theory calculations reveal that configurational entropy dominates the free energy landscape and compensates for the enthalpic penalty, whereas the vibrational and electronic entropies offer negligible contributions. The calculations predict that in many compositions, the single-phase state becomes stable at extremely high temperatures (>3000 K). Consequently, rapid quenching rates are needed to preserve solubility at room temperature and facilitate physical characterization. Physical vapor deposition provides this experimental validation opportunity. The computation/experimental data set generated in this work identifies "valence electron concentration" as an effective descriptor to predict structural and thermodynamic properties of multicomponent carbides and educate new formulation selections.

Red Bean Pod Derived Heterostructure Carbon Decorated with Hollow Mixed Transition Metals as a Bifunctional Catalyst in Zn-Air Batteries.

Design and synthesis of low-cost and efficient bifunctional catalysts for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) in Zn-air batteries are essential and challenging. We report a facile method to synthesize heterostructure carbon consisting of graphitic and amorphous carbon derived from the agricultural waste of red bean pods. The heterostructure carbon possesses a large surface area of 625.5 m2 g-1 , showing ORR onset potential of 0.89 V vs. RHE and OER overpotential of 470 mV at 5 mA cm-2 . Introducing hollow FeCo nanoparticles and nitrogen dopant improves the bifunctional catalytic activity of the carbon, delivering ORR onset potential of 0.93 V vs. RHE and OER overpotential of 360 mV. Electron energy-loss spectroscopy (EELS) O K-edge map suggests the presence of localized oxygen on the FeCo nanoparticles, suggesting the oxidation of the nanoparticles. Zn-air battery with these carbon-based catalysts exhibits a peak power density as high as 116.2 mW cm-2 and stable cycling performance over 210 discharge/charge cycles. This work contributes to the advancement of bifunctional oxygen electrocatalysts while converting agricultural waste into value-added material.

An antisite defect mechanism for room temperature ferroelectricity in orthoferrites.

Single-phase multiferroic materials that allow the coexistence of ferroelectric and magnetic ordering above room temperature are highly desirable, motivating an ongoing search for mechanisms for unconventional ferroelectricity in magnetic oxides. Here, we report an antisite defect mechanism for room temperature ferroelectricity in epitaxial thin films of yttrium orthoferrite, YFeO3, a perovskite-structured canted antiferromagnet. A combination of piezoresponse force microscopy, atomically resolved elemental mapping with aberration corrected scanning transmission electron microscopy and density functional theory calculations reveals that the presence of YFe antisite defects facilitates a non-centrosymmetric distortion promoting ferroelectricity. This mechanism is predicted to work analogously for other rare earth orthoferrites, with a dependence of the polarization on the radius of the rare earth cation. Our work uncovers the distinctive role of antisite defects in providing a mechanism for ferroelectricity in a range of magnetic orthoferrites and further augments the functionality of this family of complex oxides for multiferroic applications.

Direct imaging and electronic structure modulation of moiré superlattices at the 2D/3D interface.

The atomic structure at the interface between two-dimensional (2D) and three-dimensional (3D) materials influences properties such as contact resistance, photo-response, and high-frequency electrical performance. Moiré engineering is yet to be utilized for tailoring this 2D/3D interface, despite its success in enabling correlated physics at 2D/2D interfaces. Using epitaxially aligned MoS2/Au{111} as a model system, we demonstrate the use of advanced scanning transmission electron microscopy (STEM) combined with a geometric convolution technique in imaging the crystallographic 32 Å moiré pattern at the 2D/3D interface. This moiré period is often hidden in conventional electron microscopy, where the Au structure is seen in projection. We show, via ab initio electronic structure calculations, that charge density is modulated according to the moiré period, illustrating the potential for (opto-)electronic moiré engineering at the 2D/3D interface. Our work presents a general pathway to directly image periodic modulation at interfaces using this combination of emerging microscopy techniques.