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Hierarchical assemblies of ferroelectric nanodomains, so-called super-domains, can exhibit exotic morphologies that lead to distinct behaviours. Controlling these super-domains reliably is critical for realizing states with desired functional properties. Here we reveal the super-switching mechanism by using a biased atomic force microscopy tip, that is, the switching of the in-plane super-domains, of a model ferroelectric Pb0.6Sr0.4TiO3. We demonstrate that the writing process is dominated by a super-domain nucleation and stabilization process. A complex scanning-probe trajectory enables on-demand formation of intricate centre-divergent, centre-convergent and flux-closure polar structures. Correlative piezoresponse force microscopy and optical spectroscopy confirm the topological nature and tunability of the emergent structures. The precise and versatile nanolithography in a ferroic material and the stability of the generated structures, also validated by phase-field modelling, suggests potential for reliable multi-state nanodevice architectures and, thereby, an alternative route for the creation of tunable topological structures for applications in neuromorphic circuits. 

Controlled fabrication of nanopores in 2D materials offer the means to create robust membranes needed for ion transport and nanofiltration. Techniques for creating nanopores have relied upon either plasma etching or direct irradiation; however, aberration‐corrected scanning transmission electron microscopy (STEM) offers the advantage of combining a sub‐Å sized electron beam for atomic manipulation along with atomic resolution imaging. Here, a method for automated nanopore fabrication is utilized with real‐time atomic visualization to enhance the mechanistic understanding of beam‐induced transformations. Additionally, an electron beam simulation technique, Electron‐Beam Simulator (E‐BeamSim) is developed to observe the atomic movements and interactions resulting from electron beam irradiation. Using the MXene Ti₃C₂T_x, the influence of temperature on nanopore fabrication is explored by tracking atomic transformations and find that at room temperature the electron beam irradiation induces random displacement and results in titanium pileups at the nanopore edge, which is confirmed by E‐BeamSim. At elevated temperatures, after removal of the surface functional groups and with the increased mobility of atoms results in atomic transformations that lead to the selective removal of atoms layer by layer. This work can lead to the development of defect engineering techniques within functionalized MXene layers and other 2D materials.

 

With the advent of increasingly elaborate experimental techniques in physics, chemistry and materials sciences, measured data are becoming bigger and more complex. The observables are typically a function of several stimuli resulting in multidimensional data sets spanning a range of experimental parameters. As an example, a common approach to study ferroelectric switching is to observe effects of applied electric field, but switching can also be enacted by pressure and is influenced by strain fields, material composition, temperature, time, etc. Moreover, the parameters are usually interdependent, so that their decoupling toward univariate measurements or analysis may not be straightforward. On the other hand, both explicit and hidden parameters provide an opportunity to gain deeper insight into the measured properties, provided there exists a well-defined path to capture and analyze such data. Here, we introduce a new, two-dimensional approach to represent hysteretic response of a material system to applied electric field. Utilizing ferroelectric polarization as a model hysteretic property, we demonstrate how explicit consideration of electromechanical response to two rather than one control voltages enables significantly more transparent and robust interpretation of observed hysteresis, such as differentiating between charge trapping and ferroelectricity. Furthermore, we demonstrate how the new data representation readily fits into a variety of machine-learning methodologies, from unsupervised classification of the origins of hysteretic response via linear clustering algorithms to neural-network-based inference of the sample temperature based on the specific morphology of hysteresis. 

A helium gas field ion source has been demonstrated to be capable of realizing higher milling resolution relative to liquid gallium ion sources. One drawback, however, is that the helium ion mass is prohibitively low for reasonable sputtering rates of bulk materials, requiring a dosage that may lead to significant subsurface damage. Manipulation of suspended graphene is, therefore, a logical application for He+ milling. We demonstrate that competitive ion beam-induced deposition from residual carbonaceous contamination can be thermally mitigated via a pulsed laser-assisted He+ milling. By optimizing pulsed laser power density, frequency, and pulse width, we reduce the carbonaceous byproducts and mill graphene gaps down to sub 10 nm in highly complex kiragami patterns. 

Metal halide perovskites (MHPs) have attracted broad research interest due to their outstanding optoelectronic performance. This performance has been attributed in part to the presence of polarization in these materials. However, the precise effects of chemical environment and strain condition on the polar states in MHPs have largely been missing. It is revealed for the first time that chemical gradient is directly coupled with strain gradient in CH₃NH₃PbI₃. This strain–chemical gradient induces an electric polarization that can potentially affect charge carrier dynamics. Furthermore, it is unveiled that this electric polarization—unlike ferroelectricity that only exists in noncentrosymmetric materials—can be present in both tetragonal and cubic phases of CH₃NH₃PbI₃. This suggests that the strain–chemical gradient induced polarization is a more convincing explanation of the outstanding photovoltaic properties of MHPs than the hotly debated ferroelectric polarization. Finally, a mechanism of how this polarization impacts photovoltaic action is proposed, which offers insightful advances in the development of MHPs.

 

Given the remarkable performance of hybrid organic–inorganic perovskites (HOIPs) in solar cells, light emitters, and photodetectors, the quest to advance the fundamental understanding of the photophysical properties in this class of materials remains highly relevant. Recently, the discovery of ferroic twin domains in HOIPs has renewed the debate of the ferroic effects on optoelectric processes. This work explores the interaction between light and ferroic twin domains in CH₃NH₃PbI₃. Due to strain and chemical inhomogeneities, photogenerated electrons and holes show a preferential motion in the ferroelastic twin domains. Density functional theory (DFT) shows that electrons and holes result in lattice expansion in CH₃NH₃PbI₃differently. Hence, light generates strain in the ferroelastic domains due to preferential photocarrier motion, leading to a screening of strain variation. X‐ray diffraction studies verify the DFT simulations and reveal that the photoinduced strain is light intensity dependent, and the photoexcitation is a prerequisite of inducing strain by light. This work extends the fundamental understanding of light‐ferroic interaction and offers guidance for developing functional devices.

 

Many energy conversion, sensing, and microelectronic applications based on ferroic materials are determined by the domain structure evolution under applied stimuli. New hyperspectral, multidimensional spectroscopic techniques now probe dynamic responses at relevant length and time scales to provide an understanding of how these nanoscale domain structures impact macroscopic properties. Such approaches, however, remain limited in use because of the difficulties that exist in extracting and visualizing scientific insights from these complex datasets. Using multidimensional band‐excitation scanning probe spectroscopy and adapting tools from both computer vision and machine learning, an automated workflow is developed to featurize, detect, and classify signatures of ferroelectric/ferroelastic switching processes in complex ferroelectric domain structures. This approach enables the identification and nanoscale visualization of varied modes of response and a pathway to statistically meaningful quantification of the differences between those modes. Among other things, the importance of domain geometry is spatially visualized for enhancing nanoscale electromechanical energy conversion.