Gravity Governs Shear Localization in Confined Dense Granular Flows.

The prediction of flow profiles of slowly sheared granular materials is a major geophysical and industrial challenge. Understanding the role of gravity is particularly important for future planetary exploration in varying gravitational environments. Using the principle of minimization of energy dissipation, and combining experiments and variational analysis, we disentangle the contributions of the gravitational acceleration, confining pressure, and layer thickness on shear strain localization induced by moving fault boundaries at the bottom of a granular layer.

Machine learning characterization of structural defects in amorphous packings of dimers and ellipses.

Structural defects within amorphous packings of symmetric particles can be characterized using a machine learning approach that incorporates structure functions of radial distances and angular arrangement. This yields a scalar field, softness, that correlates with the probability that a particle is about to be rearranged. However, when particle shapes are elongated, as in the case of dimers and ellipses, we find that the standard structure functions produce imprecise softness measurements.

Anisotropic particles strengthen granular pillars under compression.

We probe the effects of particle shape on the global and local behavior of a two-dimensional granular pillar, acting as a proxy for a disordered solid, under uniaxial compression. This geometry allows for direct measurement of global material response, as well as tracking of all individual particle trajectories. In general, drawing connections between local structure and local dynamics can be challenging in amorphous materials due to lower precision of atomic positions, so this study aims to elucidate such connections.

Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity.

The application of 2-photon laser scanning microscopy (TPLSM) techniques to measure the dynamics of cellular calcium signals in populations of neurons is an extremely powerful technique for characterizing neural activity within the central nervous system. The use of TPLSM on awake and behaving subjects promises new insights into how neural circuit elements cooperatively interact to form sensory perceptions and generate behavior. A major challenge in imaging such preparations is unavoidable animal and tissue movement, which leads to shifts in the imaging location (jitter).

Consequences of anomalous diffusion in disordered systems under cyclic forcing.

We study the particle scale response of a 2D frictionless disk system to bulk forcing via cyclic shear with reversal amplitude γ_{r}. We find a subdiffusive γ_{r}-dependent regime, which is consistent with models of anomalous diffusion with scale-invariant cage dynamics, and a crossover to diffusive grain motion at high γ_{r}. Analysis of local displacements of a particle relative to its cage of neighbors reveals a key distinction from thermal systems.

Suppression and emergence of granular segregation under cyclic shear.

While convective flows are implicated in many granular segregation processes, the associated particle-scale rearrangements are not well understood. A three-dimensional bidisperse mixture segregates under steady shear, but the cyclically driven system either remains mixed or segregates slowly. Individual grain motion shows no signs of particle-scale segregation dynamics that precede bulk segregation.