Switchable tribology of ferroelectrics.

Switchable tribological properties of ferroelectrics offer an alternative route to visualize and control ferroelectric domains. Here, we observe the switchable friction and wear behavior of ferroelectrics using a nanoscale scanning probe-down domains have lower friction coefficients and show slower wear rates than up domains and can be used as smart masks. This asymmetry is enabled by flexoelectrically coupled polarization in the up and down domains under a sufficiently high contact force. Moreover, we determine that this polarization-sensitive tribological asymmetry is widely applicable across various ferroelectrics with different chemical compositions and crystalline symmetry. Finally, using this switchable tribology and multi-pass patterning with a domain-based dynamic smart mask, we demonstrate three-dimensional nanostructuring exploiting the asymmetric wear rates of up and down domains, which can, furthermore, be scaled up to technologically relevant (mm-cm) size. These findings demonstrate that ferroelectrics are electrically tunable tribological materials at the nanoscale for versatile applications.

Smooth velocity fields for tracking climate change.

Describing the spatial velocity of climate change is essential to assessing the challenge of natural and human systems to follow its pace by adapting or migrating sufficiently fast. We propose a fully-determined approach, "MATCH", to calculate a realistic and continuous velocity field of any climate parameter, without the need for ad hoc assumptions. We apply this approach to the displacement of isotherms predicted by global and regional climate models between 1950 and 2100 under the IPCC-AR5 RCP 8.5 emission scenario, and show that it provides detailed velocity patterns especially at the regional scale. This method thus favors comparisons between models as well as the analysis of regional or local features. Furthermore, the trajectories obtained using the MATCH approach are less sensitive to inter-annual fluctuations and therefore allow us to introduce a trajectory regularity index, offering a quantitative perspective on the discussion of climate sinks and sources.

Correlative imaging of ferroelectric domain walls.

The wealth of properties in functional materials at the nanoscale has attracted tremendous interest over the last decades, spurring the development of ever more precise and ingenious characterization techniques. In ferroelectrics, for instance, scanning probe microscopy based techniques have been used in conjunction with advanced optical methods to probe the structure and properties of nanoscale domain walls, revealing complex behaviours such as chirality, electronic conduction or localised modulation of mechanical response. However, due to the different nature of the characterization methods, only limited and indirect correlation has been achieved between them, even when the same spatial areas were probed. Here, we propose a fast and unbiased analysis method for heterogeneous spatial data sets, enabling quantitative correlative multi-technique studies of functional materials. The method, based on a combination of data stacking, distortion correction, and machine learning, enables a precise mesoscale analysis. When applied to a data set containing scanning probe microscopy piezoresponse and second harmonic generation polarimetry measurements, our workflow reveals behaviours that could not be seen by usual manual analysis, and the origin of which is only explainable by using the quantitative correlation between the two data sets.

Hystorian: A processing tool for scanning probe microscopy and other n-dimensional datasets.

Research in materials science increasingly depends on the correlation of information from multiple characterisation techniques, acquired in ever larger datasets. Efficient methods of processing and storing these complex datasets are therefore crucial. Reliably keeping track of data processing is also essential to conform with the goals of open science. Here, we introduce Hystorian, a generic materials science data analysis Python package built at its core to improve the traceability, reproducibility, and archival ability of data processing. Proprietary data formats are converted into open hierarchical data format (HDF5) files, with both datasets and subsequent workflows automatically stored into a single location, thus allowing easy management of multiple data types. At present, Hystorian provides a basic scanning probe microscopy and x-ray diffraction analysis toolkit, and is readily extensible to suit user needs. It is also able to wrap over any existing processing functions, making it easy to append in an extant workflow.

Roughness and dynamics of proliferating cell fronts as a probe of cell-cell interactions.

Juxtacellular interactions play an essential but still not fully understood role in both normal tissue development and tumour invasion. Using proliferating cell fronts as a model system, we explore the effects of cell-cell interactions on the geometry and dynamics of these one-dimensional biological interfaces. We observe two distinct scaling regimes of the steady state roughness of in-vitro propagating Rat1 fibroblast cell fronts, suggesting different hierarchies of interactions at sub-cell lengthscales and at a lengthscale of 2-10 cells. Pharmacological modulation significantly affects the proliferation speed of the cell fronts, and those modulators that promote cell mobility or division also lead to the most rapid evolution of cell front roughness. By comparing our experimental observations to numerical simulations of elastic cell fronts with purely short-range interactions, we demonstrate that the interactions at few-cell lengthscales play a key role. Our methodology provides a simple framework to measure and characterise the biological effects of such interactions, and could be useful in tumour phenotyping.

Local Probe Comparison of Ferroelectric Switching Event Statistics in the Creep and Depinning Regimes in Pb(Zr_{0.2}Ti_{0.8})O_{3} Thin Films.

Ferroelectric materials provide a useful model system to explore the jerky, highly nonlinear dynamics of elastic interfaces in disordered media. The distribution of nanoscale switching event sizes is studied in two Pb(Zr_{0.2}Ti_{0.8})O_{3} thin films with different disorder landscapes using piezoresponse force microscopy. While the switching event statistics show the expected power-law scaling, significant variations in the value of the scaling exponent τ are seen, possibly as a consequence of the different intrinsic disorder landscapes in the samples and of further alterations under high tip bias applied during domain writing. Importantly, higher exponent values (1.98-2.87) are observed when crackling statistics are acquired only for events occurring in the creep regime. The exponents are systematically lowered when all events across both creep and depinning regimes are considered-the first time such a distinction is made in studies of ferroelectric materials. These results show that distinguishing the two regimes is of crucial importance, significantly affecting the exponent value and potentially leading to incorrect assignment of universality class.

Better, Faster, and Less Biased Machine Learning: Electromechanical Switching in Ferroelectric Thin Films.

Machine-learning techniques are more and more often applied to the analysis of complex behaviors in materials research. Frequently used to identify fundamental behaviors within large and multidimensional datasets, these techniques are strictly based on mathematical models. Thus, without inherent physical or chemical meaning or constraints, they are prone to biased interpretation. The interpretability of machine-learning results in materials science, specifically materials' functionalities, can be vastly improved through physical insights and careful data handling. The use of techniques such as dimensional stacking can provide the much needed physical and chemical constraints, while proper understanding of the assumptions imposed by model parameters can help avoid overinterpretation. These concepts are illustrated by application to recently reported ferroelectric switching experiments in PbZr0.2 Ti0.8 O3 thin films. Through systematic analysis and introduction of physical constraints, it is argued that the behaviors present are not necessarily due to exotic mechanisms previously suggested, but rather well described by classical ferroelectric switching superimposed by non-ferroelectric phenomena, such as electrochemical deformation, electrostatic interactions, and/or charge injection.

Surface charged species and electrochemistry of ferroelectric thin films.

The combination of scanning probe microscopy and ambient pressure X-ray photoelectron spectroscopy opens up new perspectives for the study of combined surface chemical, electrochemical and electromechanical properties at the nanoscale, providing both nanoscale resolution of physical information and the chemical sensitivity required to identify surface species and bulk ionic composition. In this work, we determine the nature and evolution over time of surface chemical species obtained after water-mediated redox reactions on Pb(Zr0.2,Ti0.8)O3 thin films with opposite as-grown polarization states. Starting with intrinsically different surface chemical composition on the oppositely polarized films (as a result of their ferroelectric-dominated interaction with environmental water), we identify the reversible and irreversible electrochemical reactions under an external electric field, distinguishing switching and charging events. We find that while reversible ionic displacements upon polarization switching dominate screening in the bulk of the sample, polarization dependent irreversible redox reactions determine surface chemical composition, which reveals itself as a characteristic fingerprint of the ferroelectric polarization switching history.

Non-Ising and chiral ferroelectric domain walls revealed by nonlinear optical microscopy.

The properties of ferroelectric domain walls can significantly differ from those of their parent material. Elucidating their internal structure is essential for the design of advanced devices exploiting nanoscale ferroicity and such localized functional properties. Here, we probe the internal structure of 180° ferroelectric domain walls in lead zirconate titanate (PZT) thin films and lithium tantalate bulk crystals by means of second-harmonic generation microscopy. In both systems, we detect a pronounced second-harmonic signal at the walls. Local polarimetry analysis of this signal combined with numerical modelling reveals the existence of a planar polarization within the walls, with Néel and Bloch-like configurations in PZT and lithium tantalate, respectively. Moreover, we find domain wall chirality reversal at line defects crossing lithium tantalate crystals. Our results demonstrate a clear deviation from the ideal Ising configuration that is traditionally expected in uniaxial ferroelectrics, corroborating recent theoretical predictions of a more complex, often chiral structure.

Computer vision distortion correction of scanning probe microscopy images.

Since its inception, scanning probe microscopy (SPM) has established itself as the tool of choice for probing surfaces and functionalities at the nanoscale. Although recent developments in the instrumentation have greatly improved the metrological aspects of SPM, it is still plagued by the drifts and nonlinearities of the piezoelectric actuators underlying the precise nanoscale motion. In this work, we present an innovative computer-vision-based distortion correction algorithm for offline processing of functional SPM measurements, allowing two images to be directly overlaid with minimal error - thus correlating position with time evolution and local functionality. To demonstrate its versatility, the algorithm is applied to two very different systems. First, we show the tracking of polarisation switching in an epitaxial Pb(Zr0.2Ti0.8)O3 thin film during high-speed continuous scanning under applied tip bias. Thanks to the precise time-location-polarisation correlation we can extract the regions of domain nucleation and track the motion of domain walls until the merging of the latter in avalanche-like events. Secondly, the morphology of surface folds and wrinkles in graphene deposited on a PET substrate is probed as a function of applied strain, allowing the relaxation of individual wrinkles to be tracked.

Identification of a strong contamination source for graphene in vacuum systems.

To minimize parasitic doping effects caused by uncontrolled material adsorption, graphene is often investigated under vacuum. Here we report an entirely unexpected phenomenon occurring in vacuum systems, namely strong n-doping of graphene due to chemical species generated by common ion high-vacuum gauges. The effect-reversible upon exposing graphene to air-is significant, as doping rates can largely exceed 10(12) cm(-2) h(-1), depending on pressure and the relative position of the gauge and the graphene device. It is important to be aware of this phenomenon, as its basic manifestation can be mistakenly interpreted as vacuum-induced desorption of p-dopants.

Conduction at domain walls in insulating Pb(Zr0.2 Ti0.8)O3 thin films.

Domain wall conduction in insulating Pb(Zr(0.2) Ti(0.8))O(3) thin films is demonstrated. The observed electrical conduction currents can be clearly differentiated from displacement currents associated with ferroelectric polarization switching. The domain wall conduction, nonlinear and highly asymmetric due to the specific local probe measurement geometry, shows thermal activation at high temperatures, and high stability over time.