The Deformation of an Elastic Substrate by a Three-Phase Contact Line

Young's classic analysis of the equilibrium of a three-phase contact line ignores the out-of-plane component of the liquid-vapor surface tension. While it has long been appreciated that this unresolved force must be balanced by elastic deformation of the solid substrate, a definitive analysis has remained elusive because conventional idealizations of the substrate imply a divergence of stress at the contact line. While a number of theories of have been presented to cut off the divergence, none of them have provided reasonable agreement with experimental data. We measure surface and bulk deformation of a thin elastic film near a three-phase contact line using fluorescence confocal microscopy. The out-of-plane deformation is well fit by a linear elastic theory incorporating an out-of-plane restoring force due to the surface tension of the gel. This theory predicts that the deformation profile near the contact line is scale-free and independent of the substrate elastic modulus.Comment: 4 pages, 3 figure

Scaling of Traction Forces with Size of Cohesive Cell Colonies

To understand how the mechanical properties of tissues emerge from interactions of multiple cells, we measure traction stresses of cohesive colonies of 1-27 cells adherent to soft substrates. We find that traction stresses are generally localized at the periphery of the colony and the total traction force scales with the colony radius. For large colony sizes, the scaling appears to approach linear, suggesting the emergence of an apparent surface tension of order 1E-3 N/m. A simple model of the cell colony as a contractile elastic medium coupled to the substrate captures the spatial distribution of traction forces and the scaling of traction forces with the colony size.Comment: 5 pages, 3 figure

Microstructural Transformations And Kinetics Of High-Temperature Heterogeneous Gasless Reactions By High-Speed X-Ray Phase-Contrast Imaging

Heterogeneous gasless reactive systems, including high-energy density metal-nonmetal compositions, have seen increasing study due to their various applications. However, owing to their high reaction temperature, short reaction time, and small scale of heterogeneity, investigation of their reaction mechanisms and kinetics is very difficult. In this study, microstructural changes and the kinetics of product layer growth in the W-Si system was investigated using a high-speed x-ray phase-contrast imaging technique. Using the Advanced Photon Source of Argonne National Laboratory, this method allowed direct imaging of irreversible reactions in the W-Si reactive system at frame rates up to 36 000 frames per second with 4-microsecond exposure and spatial resolution of 1micrometerser. Details of the Si melt and reactions between W and Si, that are unable to be viewed with visible-light imaging, were revealed. These include processes such as the initiation of nucleated melting and other physical phenomena that provide insight into the mixing of reactants and subsequent reaction. Through the use of this imaging technique and future optimization in the imaging process, a model for accurately identifying kinetics of chemical reactions, both spatially and temporally, is also proposed

Elucidation of Relaxation Dynamics Beyond Equilibrium Through AI-informed X-ray Photon Correlation Spectroscopy

Understanding and interpreting dynamics of functional materials \textit{in situ} is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales, however spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work we have developed an unsupervised deep learning (DL) framework for automated classification and interpretation of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system behavior. We demonstrate how this method can be used to rapidly explore large datasets to identify samples of interest, and we apply this approach to directly correlate bulk properties of a model system to microscopic dynamics. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery

Hydrodynamic Coupling of Two Brownian Spheres to a Planar Surface

We describe direct imaging measurements of the collective and relative diffusion of two colloidal spheres near a flat plate. The bounding surface modifies the spheres' dynamics, even at separations of tens of radii. This behavior is captured by a stokeslet analysis of fluid flow driven by the spheres' and wall's no-slip boundary conditions. In particular, this analysis reveals surprising asymmetry in the normal modes for pair diffusion near a flat surface.Comment: 4 pages, 4 figure

Reconstructing extreme AMOC events through nudging of the ocean surface: a perfect model approach

While the Atlantic Meridional Overturning Circulation (AMOC) is thought to be a crucial component of the North Atlantic climate, past changes in its strength are challenging to quantify, and only limited information is available. In this study, we use a perfect model approach with the IPSL-CM5A-LR model to assess the performance of several surface nudging techniques in reconstructing the variability of the AMOC. Special attention is given to the reproducibility of an extreme positive AMOC peak from a preindustrial control simulation. Nudging includes standard relaxation techniques towards the sea surface temperature and salinity anomalies of this target control simulation, and/or the prescription of the wind-stress fields. Surface nudging approaches using standard fixed restoring terms succeed in reproducing most of the target AMOC variability, including the timing of the extreme event, but systematically underestimate its amplitude. A detailed analysis of the AMOC variability mechanisms reveals that the underestimation of the extreme AMOC maximum comes from a deficit in the formation of the dense water masses in the main convection region, located south of Iceland in the model. This issue is largely corrected after introducing a novel surface nudging approach, which uses a varying restoring coefficient that is proportional to the simulated mixed layer depth, which, in essence, keeps the restoring time scale constant. This new technique substantially improves water mass transformation in the regions of convection, and in particular, the formation of the densest waters, which are key for the representation of the AMOC extreme. It is therefore a promising strategy that may help to better constrain the AMOC variability and other ocean features in the models. As this restoring technique only uses surface data, for which better and longer observations are available, it opens up opportunities for improved reconstructions of the AMOC over the last few decades