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Register a new userPredictability as a probe of manifest and latent physics: The case of atomic scale structural, chemical, and polarization behaviors in multiferroic Sm-doped BiFeO3
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The predictability of a certain effect or phenomenon is often equated with the knowledge of relevant physical laws, typically understood as a functional or numerically derived relationship between the observations and known states of the system. Correspondingly, observations inconsistent with prior knowledge can be used to derive new knowledge on the nature of the system or indicate the presence of yet unknown mechanisms. Here we explore the applicability of Gaussian Processes (GP) to establish predictability and uncertainty of local behaviors from multimodal observations, providing an alternative to this classical paradigm. Using atomic-resolution Scanning Transmission Electron Microscopy (STEM) of multiferroic Sm-doped BiFeO3 across a broad composition range, we directly visualize the atomic structure and structural, physical, and chemical order parameter fields for the material. GP regression is used to establish the predictability of the local polarization field from different groups of parameters, including the adjacent polarization values and several combinations of physical and chemical descriptors, including lattice parameters, column intensities, etc. We observe that certain elements of microstructure including charged and uncharged domain walls and interfaces with the substrate are best predicted with specific combinations of descriptors, and this predictability and their associated uncertainties are consistent across the composition series. The associated generative physical mechanisms are discussed. We argue that predictability and uncertainty in observational data offers a new pathway to probe the physics of condensed matter systems from multimodal local observations.
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Recent works have shown that the domain walls of room-temperature multiferroic BiFeO3 (BFO) thin films can display distinct and promising functionalities. It is thus important to understand the mechanisms underlying domain formation in these films. High-resolution x-ray diffraction and piezo-force microscopy, combined with first-principles simulations, have allowed us to characterize both the atomic and domain structure of BFO films grown under compressive strain on (001)-SrTiO3, as a function of thickness. We derive a twining model that describes the experimental observations and explains why the 71o domain walls are the ones commonly observed in these films. This understanding provides us with a new degree of freedom to control the structure and, thus, the properties of BiFeO3 thin films.
We report X-ray structural studies of the metal-insulator phase transition in bismuth ferrite, BiFeO3, both as a function of temperature and of pressure (931 oC at atmospheric pressure and ca. 45 GPa at ambient temperature). Based on the experimental results, we argue that the metallic gamma-phase is not rhombohedral but is instead the same cubic Pm3m structure whether obtained via high temperature or high pressure, that the MI transition is second order or very nearly so, that this is a band-type transition due to semi-metal band overlap in the cubic phase and not a Mott transition, and that it is primarily structural and not an S=5/2 to S=1/2 high-spin/low-spin electronic transition. Our data are compatible with the orthorhombic Pbnm structure for the beta-phase determined definitively by the neutron scattering study of Arnold et al .[Phys. Rev. Lett. 2009]; the details of this beta-phase had also been controversial, with a remarkable collection of five crystal classes (cubic, tetragonal, orthorhombic, monoclinic, and rhombohedral!) all claimed in recent publications.
We have investigated heteroepitaxial films of Sm-doped BiFeO3 with a Sm-concentration near a morphotropic phase boundary. Our high-resolution synchrotron X-ray diffraction, carried out in a temperature range of 25C to 700C, reveals substantial phase coexistence as one changes temperature to crossover from a low-temperature PbZrO3-like phase to a high-temperature orthorhombic phase. We also examine changes due to strain for films greater or less than the critical thickness for misfit dislocation formation. Particularly, we note that thicker films exhibit a substantial volume collapse associated with the structural transition that is suppressed in strained thin films.
Multiferroic BiFeO3 ceramics have been doped with Ca. The smaller ionic size of Ca compared with Bi means that doping acts as a proxy for hydrostatic pressure, at a rate of 1%Ca=0.3GPa. It is also found that the magnetic Neel temperature (TNeel) increases as Ca concentration increases, at a rate of 0.66K per 1%Ca (molar). Based on the effect of chemical pressure on TNeel, we argue that applying hydrostatic pressure to pure BiFeO3 can be expected to increase its magnetic transition temperature at a rate around ~2.2K/GPa. The results also suggest that pressure (chemical or hydrostatic) could be used to bring the ferroelectric critical temperature, Tc, and the magnetic TNeel closer together, thereby enhancing magnetoelectric coupling, provided that electrical conductivity can be kept sufficiently low.
Recent advances in scanning transmission electron and scanning tunneling microscopies allow researchers to measure materials structural and electronic properties, such as atomic displacements and charge density modulations, at an Angstrom scale in real space. At the same time, the ability to quickly acquire large, high-resolution datasets has created a challenge for rapid physics-based analysis of images that typically contain several hundreds to several thousand atomic units. Here we demonstrate a universal deep-learning based framework for locating and characterizing atomic species in the lattice, which can be applied to different types of atomically resolved measurements on different materials. Specifically, by inspecting and categorizing features in the output layer of a convolutional neural network, we are able to detect structural and electronic anomalies associated with the presence of point defects in a tungsten disulfide monolayer, non-uniformity of the charge density distribution around specific lattice sites on the surface of strongly correlated oxides, and transition between different structural states of buckybowl molecules. We further extended our method towards tracking, from one image frame to another, minute distortions in the geometric shape of individual Si dumbbells in a 3-dimensional Si sample, which are associated with a motion of lattice defects and impurities. Due the applicability of our framework to both scanning tunneling microscopy and scanning transmission electron microscopy measurements, it can provide a fast and straightforward way towards creating a unified database of defect-property relationships from experimental data for each material.
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