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Electron backscatter diffraction (EBSD) is a powerful tool for determining the orientations of near-surface grains in engineering materials. However, many ceramics present challenges for routine EBSD data collection and indexing due to small grain sizes, high crack densities, beam and charge sensitivities, low crystal symmetries, and pseudo-symmetric pattern variants. Micro-cracked monoclinic hafnia, tetragonal hafnon, and hafnia/hafnon composites exhibit all such features, and are used in the present work to show the efficacy of a novel workflow based on a direct detecting EBSD sensor and a state-of-the-art pattern indexing approach. At 5 and 10 keV primary beam energies (where beam-induced damage and surface charge accumulation are minimal), the direct electron detector produces superior diffraction patterns with 10x lower doses compared to a phosphor-coupled indirect detector. Further, pseudo-symmetric variant-related indexing errors from a Hough-based approach (which account for at least 4%-14% of map areas) are easily resolved by dictionary indexing. In short, the workflow unlocks fundamentally new opportunities to characterize materials historically unsuited for EBSD. 

Abstract Electron counting can be performed algorithmically for monolithic active pixel sensor direct electron detectors to eliminate readout noise and Landau noise arising from the variability in the amount of deposited energy for each electron. Errors in existing counting algorithms include mistakenly counting a multielectron strike as a single electron event, and inaccurately locating the incident position of the electron due to lateral spread of deposited energy and dark noise. Here, we report a supervised deep learning (DL) approach based on Faster region-based convolutional neural network (R-CNN) to recognize single electron events at varying electron doses and voltages. The DL approach shows high accuracy according to the near-ideal modulation transfer function (MTF) and detector quantum efficiency for sparse images. It predicts, on average, 0.47 pixel deviation from the incident positions for 200 kV electrons versus 0.59 pixel using the conventional counting method. The DL approach also shows better robustness against coincidence loss as the electron dose increases, maintaining the MTF at half Nyquist frequency above 0.83 as the electron density increases to 0.06 e−/pixel. Thus, the DL model extends the advantages of counting analysis to higher dose rates than conventional methods. 

Abstract A domain wall‐enabled memristor is created, in thin film lithium niobate capacitors, which shows up to twelve orders of magnitude variation in resistance. Such dramatic changes are caused by the injection of strongly inclined conducting ferroelectric domain walls, which provide conduits for current flow between electrodes. Varying the magnitude of the applied electric‐field pulse, used to induce switching, alters the extent to which polarization reversal occurs; this systematically changes the density of the injected conducting domain walls in the ferroelectric layer and hence the resistivity of the capacitor structure as a whole. Hundreds of distinct conductance states can be produced, with current maxima achieved around the coercive voltage, where domain wall density is greatest, and minima associated with the almost fully switched ferroelectric (few domain walls). Significantly, this “domain wall memristor” demonstrates a plasticity effect: when a succession of voltage pulses of constant magnitude is applied, the resistance changes. Resistance plasticity opens the way for the domain wall memristor to be considered for artificial synapse applications in neuromorphic circuits. 

Abstract Domain wall nanoelectronics is a rapidly evolving field, which explores the diverse electronic properties of the ferroelectric domain walls for application in low‐dimensional electronic systems. One of the most prominent features of the ferroelectric domain walls is their electrical conductivity. Here, using a combination of scanning probe and scanning transmission electron microscopy, the mechanism of the tunable conducting behavior of the domain walls in the sub‐micrometer thick films of the technologically important ferroelectric LiNbO₃is explored. It is found that the electric bias generates stable domains with strongly inclined domain boundaries with the inclination angle reaching 20° with respect to the polar axis. The head‐to‐head domain boundaries exhibit high conductance, which can be modulated by application of the sub‐coercive voltage. Electron microscopy visualization of the electrically written domains and piezoresponse force microscopy imaging of the very same domains reveals that the gradual and reversible transition between the conducting and insulating states of the domain walls results from the electrically induced wall bending near the sample surface. The observed modulation of the wall conductance is corroborated by the phase‐field modeling. The results open a possibility for exploiting the conducting domain walls as the electrically controllable functional elements in the multilevel logic nanoelectronics devices.