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Stimulation with ultrafast light pulses can realize and manipulate states of matter with emergent structural, electronic and magnetic phenomena. However, these non-equilibrium phases are often transient and the challenge is to stabilize them as persistent states. Here, we show that atomic-scale PbTiO3/SrTiO3 superlattices, counterpoising strain and polarization states in alternate layers, are converted by sub-picosecond optical pulses to a supercrystal phase. This phase persists indefinitely under ambient conditions, has not been created via equilibrium routes, and can be erased by heating. X-ray scattering and microscopy show this unusual phase consists of a coherent three-dimensional structure with polar, strain and charge-ordering periodicities of up to 30 nm. By adjusting only dielectric properties, the phase-field model describes this emergent phase as a photo-induced charge-stabilized supercrystal formed from a two-phase equilibrium state. Our results demonstrate opportunities for light-activated pathways to thermally inaccessible and emergent metastable states.

Ferroelectric domain walls have continued to attract widespread attention due to both the novelty of the phenomena observed and the ability to reliably pattern them in nanoscale dimensions. However, the conductivity mechanisms remain in debate, particularly around nominally uncharged walls. Here, we posit a conduction mechanism relying on field-modification effect from polarization re-orientation and the structure of the reverse-domain nucleus. Through conductive atomic force microscopy measurements on an ultra-thin (001) BiFeO 3 thin film, in combination with phase-field simulations, we show that the field-induced twisted domain nucleus formed at domain walls results in local-field enhancement around the region of the atomic force microscope tip. In conjunction with slight barrier lowering, these two effects are sufficient to explain the observed emission current distribution. These results suggest that different electronic properties at domain walls are not necessary to observe localized enhancement in domain wall currents.

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.

X-ray diffraction imaging is rapidly emerging as a powerful technique by which one can capture the local structure of crystalline materials at the nano- and meso-scale. Here, we present investigations of the dynamic structure of epitaxial monodomain BiFeO 3 thin-films using a novel full-field Bragg diffraction imaging modality. By taking advantage of the depth penetration of hard X-rays and their exquisite sensitivity to the atomic structure, we imaged in situ and in operando, the electric field-driven structural responses of buried BiFeO 3 epitaxial thin-films in micro-capacitor devices, with sub-100 nm lateral resolution. These imaging investigations were carried out at acquisition frame rates that reached up to 20 Hz and data transfer rates of 40 MB/s, while accessing diffraction contrast that is sensitive to the entire three-dimensional unit cell configuration. We mined these large datasets for material responses by employing matrix decomposition techniques, such as independent component analysis. We found that this statistical approach allows the extraction of the salient physical properties of the ferroelectric response of the material, such as coercive fields and transient spatiotemporal modulations in their piezoelectric response, and also facilitates their decoupling from extrinsic sources that are instrument specific.

Scanning probe microscopy (SPM) techniques have opened the door to nanoscience and nanotechnology by enabling imaging and manipulation of the structure and functionality of matter at nanometer and atomic scales. Here, we analyze the scientific discovery process in SPM by following the information flow from the tip-surface junction, to knowledge adoption by the wider scientific community. We further discuss the challenges and opportunities offered by merging SPM with advanced data mining, visual analytics, and knowledge discovery technologies.

We present a novel methodology based on machine learning to extract lattice variations in crystalline materials, at the nanoscale, from an x-ray Bragg diffraction-based imaging technique. By employing a full-field microscopy setup, we capture real space images of materials, with imaging contrast determined solely by the x-ray diffracted signal. The data sets that emanate from this imaging technique are a hybrid of real space information (image spatial support) and reciprocal lattice space information (image contrast), and are intrinsically multidimensional (5D). By a judicious application of established unsupervised machine learning techniques and multivariate analysis to this multidimensional data cube, we show how to extract features that can be ascribed physical interpretations in terms of common structural distortions, such as lattice tilts and dislocation arrays. We demonstrate this 'big data' approach to x-ray diffraction microscopy by identifying structural defects present in an epitaxial ferroelectric thin-film of lead zirconate titanate.

The interface between minerals and aqueous solutions hosts globally important biogeochemical processes such as the growth and dissolution of carbonate minerals. Understanding such processes requires spatially and temporally resolved observations and experimental controls that precisely manipulate the interfacial thermodynamic state. Using the intense radiation fields of a focused synchrotron x-ray beam, we drove dissolution at the calcite/water interface and simultaneously probed the dynamics of the propagating reaction fronts using surface x-ray microscopy. Evolving surface structures were controlled by the time-dependent solution composition, as characterized by a kinetic reaction model. At extreme disequilibria, we observed the onset of reaction front instabilities with velocities of > 30 nanometers per second. These instabilities serve as a signature of transport-limited dissolution of calcite under extreme disequilibrium., (Copyright © 2015, American Association for the Advancement of Science.)

Novel X-ray imaging of structural domains in a ferroelectric epitaxial thin film using diffraction contrast is presented. The full-field hard X-ray microscope uses the surface scattering signal, in a reflectivity or diffraction experiment, to spatially resolve the local structure with 70 nm lateral spatial resolution and sub-nanometer height sensitivity. Sub-second X-ray exposures can be used to acquire a 14 µm × 14 µm image with an effective pixel size of 20 nm on the sample. The optical configuration and various engineering considerations that are necessary to achieve optimal imaging resolution and contrast in this type of microscopy are discussed.

We present X-ray reflectivity and interfacial tension measurements of the electrified liquid/liquid interface between two immiscible electrolyte solutions for the purpose of understanding the dependence of interfacial ion distributions on the applied electric potential difference across the interface. The aqueous phase contains alkali-metal chlorides, including LiCl, NaCl, RbCl, or CsCl, and the organic phase is a 1,2-dichloroethane solution of bis(triphenylphosphor anylidene) ammonium tetrakis(pentafluorophenyl)borate (BTPPATPFB). Selected data for a subset of electric potential differences are analyzed to determine the potentials of mean force for Li(+), Rb(+), Cs(+), BTPPA(+), and TPFB(-). These potentials of mean force are then used to analyze both X-ray reflectivity and interfacial tension data measured over a wide range of electric potential differences. Comparison of X-ray reflectivity data for strongly hydrated alkali-metal ions (Li(+) and Na(+)), for which ion pairing to TPFB(-) ions across the interface is not expected, to data for weakly hydrated alkali-metal ions (Rb(+) and Cs(+)) indicates that the Gibbs energy of adsorption due to ion pairing at the interface must be small (<1 k(B)T per ion pair) for both the CsCl and RbCl samples. This paper demonstrates the applicability of the Poisson-Boltzmann potential of mean force approach to the analysis of X-ray reflectivity measurements that probe the nanoscale ion distribution and the consequences of these underlying distributions for thermodynamic studies, such as interfacial tension measurements, that yield quantities related to the integrated ion distribution.

Ion distributions play a central role in various settings-from biology, where they mediate the electrostatic interactions between charged biomolecules in solution, to energy storage devices, where they influence the charging properties of supercapacitors. These distributions are determined by interactions dictated by the chemical properties of the ions and their environment as well as the long-range nature of the electrostatic force. Recent theoretical and computational studies have explored the role of correlations between ions, which have been suggested to underlie a number of counterintuitive results, such as like-charge attraction. However, the interdependency between ion correlations and other interactions that ions experience in solution complicates the connection between physical models of ion correlations and the experimental investigation of ion distributions. We exploit the properties of the liquid/liquid interface to vary the coupling strength of ion-ion correlations from weak to strong while monitoring their influence on ion distributions at the nanometer scale with X-ray reflectivity and the macroscopic scale with interfacial tension measurements. These data are in agreement with the predictions of a parameter-free density functional theory that includes ion-ion correlations and ion-solvent interactions over the entire range of experimentally tunable correlation coupling strengths (from 0.8 to 3.7). This study provides evidence for a sharply defined electrical double layer for large coupling strengths in contrast to the diffuse distributions predicted by mean field theory, thereby confirming a common prediction of many ion correlation models. The reported findings represent a significant advance in elucidating the nature and role of ion correlations in charged soft matter.

X-ray reflectivity studies demonstrate the condensation of a monovalent ion at the electrified interface between electrolyte solutions of water and 1,2-dichloroethane. Predictions of the ion distributions by standard Poisson-Boltzmann (Gouy-Chapman) theory are inconsistent with these data at higher applied interfacial electric potentials. Calculations from a Poisson-Boltzmann equation that incorporates a nonmonotonic ion-specific potential of mean force are in good agreement with the data.