Periodicity-Doubling Cascades: Direct Observation in Ferroelastic Materials

The Effect of Chemical Environment and Temperature on the Domain Structure of Free-Standing BaTiO3 via In Situ STEM

Ferroelectrics, due to their polar nature and reversible switching, can be used to dynamically control surface chemistry for catalysis, chemical switching, and other applications such as water splitting. However, this is a complex phenomenon where ferroelectric domain orientation and switching are intimately linked to surface charges. In this work, the temperature-induced domain behavior of ferroelectric-ferroelastic domains in free-standing BaTiO3 films under different gas environments, including vacuum and oxygen-rich, is studied by in situ scanning transmission electron microscopy (STEM). An automated pathway to statistically disentangle and detect domain structure transformations using deep autoencoders, providing a pathway towards real-time analysis is also established. These results show a clear difference in the temperature at which phase transition occurs and the domain behavior between various environments, with a peculiar domain reconfiguration at low temperatures, from a-c to a-a at ≈60 °C. The vacuum environment exhibits a rich domain structure, while under the oxidizing environment, the domain structure is largely suppressed. The direct visualization provided by in situ gas and heating STEM allows to investigate the influence of external variables such as gas, pressure, and temperature, on oxide surfaces in a dynamic manner, providing invaluable insights into the intricate surface-screening mechanisms in ferroelectrics.

Toward a formal theory for computing machines made out of whatever physics offers

Approaching limitations of digital computing technologies have spurred research in neuromorphic and other unconventional approaches to computing. Here we argue that if we want to engineer unconventional computing systems in a systematic way, we need guidance from a formal theory that is different from the classical symbolic-algorithmic Turing machine theory. We propose a general strategy for developing such a theory, and within that general view, a specific approach that we call fluent computing. In contrast to Turing, who modeled computing processes from a top-down perspective as symbolic reasoning, we adopt the scientific paradigm of physics and model physical computing systems bottom-up by formalizing what can ultimately be measured in a physical computing system. This leads to an understanding of computing as the structuring of processes, while classical models of computing systems describe the processing of structures.

Integrated world modeling theory expanded: Implications for the future of consciousness

Integrated world modeling theory (IWMT) is a synthetic theory of consciousness that uses the free energy principle and active inference (FEP-AI) framework to combine insights from integrated information theory (IIT) and global neuronal workspace theory (GNWT). Here, I first review philosophical principles and neural systems contributing to IWMT's integrative perspective. I then go on to describe predictive processing models of brains and their connections to machine learning architectures, with particular emphasis on autoencoders (perceptual and active inference), turbo-codes (establishment of shared latent spaces for multi-modal integration and inferential synergy), and graph neural networks (spatial and somatic modeling and control). Future directions for IIT and GNWT are considered by exploring ways in which modules and workspaces may be evaluated as both complexes of integrated information and arenas for iterated Bayesian model selection. Based on these considerations, I suggest novel ways in which integrated information might be estimated using concepts from probabilistic graphical models, flow networks, and game theory. Mechanistic and computational principles are also considered with respect to the ongoing debate between IIT and GNWT regarding the physical substrates of different kinds of conscious and unconscious phenomena. I further explore how these ideas might relate to the "Bayesian blur problem," or how it is that a seemingly discrete experience can be generated from probabilistic modeling, with some consideration of analogies from quantum mechanics as potentially revealing different varieties of inferential dynamics. I go on to describe potential means of addressing critiques of causal structure theories based on network unfolding, and the seeming absurdity of conscious expander graphs (without cybernetic symbol grounding). Finally, I discuss future directions for work centered on attentional selection and the evolutionary origins of consciousness as facilitated "unlimited associative learning." While not quite solving the Hard problem, this article expands on IWMT as a unifying model of consciousness and the potential future evolution of minds.

Avalanche criticality in LaAlO[Formula: see text] and the effect of aspect ratio

Ferroic domain dynamics, as a function of external stimuli, can be collectively described as scale-invariant avalanches characterised by a critical exponent that are sensitive to the complexity of the domain microstructure. The understanding and manipulation of these avalanches lies at the heart of developing novel applications such as neuromorphic computing. Here we combine in situ heating optical observations and mean-field analysis to investigate the collective domain behaviour in pure-ferroelastic lanthanum aluminate (LaAlO[Formula: see text]) as a function of aspect ratio, the ratio of sample length to width, where the movement of the domains is predominantly driven by thermal stresses via thermal expansion/contraction during heat cycling. Our observations demonstrate that the aspect ratio induces (1) distinctive domain microstructures at room temperature, (2) a deviation of dynamical behaviour at high temperatures and (3) critical exponent mixing in the higher aspect ratio samples that accompanies this behaviour. While the critical exponents of each aspect ratio fall within mean-field predicted values, we highlight the effect that the aspect ratio has in inducing exponent mixing. Hence, furthering our understanding towards tuning and controlling avalanches which is crucial for fundamental and applied research.

Interplay of domain structure and phase transitions: theory, experiment and functionality

Domain walls and phase boundaries are fundamental ingredients of ferroelectrics and strongly influence their functional properties. Although both interfaces have been studied for decades, often only a phenomenological macroscopic understanding has been established. The recent developments in experiments and theory allow to address the relevant time and length scales and revisit nucleation, phase propagation and the coupling of domains and phase transitions. This review attempts to specify regularities of domain formation and evolution at ferroelectric transitions and give an overview on unusual polar topological structures that appear as transient states and at the nanoscale. We survey the benefits, validity, and limitations of experimental tools as well as simulation methods to study phase and domain interfaces. We focus on the recent success of these tools in joint scale-bridging studies to solve long lasting puzzles in the field and give an outlook on recent trends in superlattices.

Dynamic Tilting of Ferroelectric Domain Walls Caused by Optically Induced Electronic Screening

Optical excitation perturbs the balance of phenomena selecting the tilt orientation of domain walls within ferroelectric thin films. The high carrier density induced in a low-strain BaTiO_{3} thin film by an above-band-gap ultrafast optical pulse changes the tilt angle that 90° a/c domain walls form with respect to the substrate-film interface. The dynamics of the changes are apparent in time-resolved synchrotron x-ray scattering studies of the domain diffuse scattering. Tilting occurs at 298 K, a temperature at which the a/b and a/c domain phases coexist but is absent at 343 K in the better ordered single-phase a/c regime. Phase coexistence at 298 K leads to increased domain-wall charge density, and thus a larger screening effect than in the single-phase regime. The screening mechanism points to new directions for the manipulation of nanoscale ferroelectricity.

The mechanism driving a solid-solid phase transition in a biomacromolecular crystal

Solid-solid phase transitions (SSPTs) occur between distinguishable crystalline forms. Because of their importance in application and theory in materials science and condensed-matter physics, SSPTs have been studied most extensively in metallic alloys, inorganic salts and small organic molecular crystals, but much less so in biomacromolecular crystals. In general, the mechanisms of SSPTs at the atomic and molecular levels are not well understood. Here, the ordered molecular rearrangements in biomacromolecular crystals of the adenine riboswitch aptamer are described using real-time serial crystallography and solution atomic force microscopy. Large, ligand-induced conformational changes drive the initial phase transition from the apo unit cell (AUC) to the trans unit cell 1 (TUC1). During this transition, coaxial stacking of P1 duplexes becomes the dominant packing interface, whereas P2-P2 interactions are almost completely disrupted, resulting in 'floating' layers of molecules. The coupling points in TUC1 and their local conformational flexibility allow the molecules to reorganize to achieve the more densely packed and energetically favorable bound unit cell (BUC). This study thus reveals the interplay between the conformational changes and the crystal phases - the underlying mechanism that drives the phase transition. Using polarized video microscopy to monitor SSPTs in small crystals at high ligand concentration, the time window during which the major conformational changes take place was identified, and the in crystallo kinetics have been simulated. Together, these results provide the spatiotemporal information necessary for informing time-resolved crystallography experiments. Moreover, this study illustrates a practical approach to characterization of SSPTs in transparent crystals.

An unprecedented hexagonal double perovskite organic-inorganic hybrid ferroelastic material: (piperidinium)2[KBiCl6]

An unprecedented A2MIMIIIX6-type double perovskite adopting a fully hexagonal BaNiO3-type structure, (piperidinium)2[KBiCl6], undergoes a 2/mF1[combining macron] ferroelastic phase transition at 285 K with a spontaneous strain of 0.0615, arising from the order-disorder transition of organic cations together with the synchronous displacement of inorganic chains.

Formation and manipulation of domain walls with 2 nm domain periodicity in BaTiO3 without contact electrodes

Interfaces at the two-dimensional limit in oxide materials exhibit a wide span of functionality that differs significantly from the bulk behavior. Among such interfaces, domain walls in ferroelectrics draw special attention because they can be moved deterministically with external voltage, while they remain at place after voltage removal, paving the way to novel neuromorphic and low-power data-processing technologies. Ferroic domains arise to release strain, which depends on material thickness, following Kittel's scaling law. Hence, a major hurdle is to reduce the device footprint for a given thickness, i.e., to form and move high-density domain walls. Here, we used transmission electron microscopy to produce domain walls with periodicity as high as 2 nm without the use of contact electrodes, while observing their formation and dynamics in situ in BaTiO3. Large-area coverage of the engineered domain walls was demonstrated. The domain-wall density was found to increase with increasing effective stress, until arriving at a saturation value that reflects 150-fold effective stress enhancement. Exceeding this value resulted in strain release by domain rotation. In addition to revealing this multiscale strain-releasing mechanism, we offer a device design that allows controllable switching of domain-walls with 2 nm periodicity, reflecting a potential 144 Tb per inch2 neuromorphic network.