The role of thermodiffusion in transpiration.

Plant leaf temperatures can differ from ambient air temperatures. A temperature gradient in a gas mixture gives rise to a phenomenon known as thermodiffusion, which operates in addition to ordinary diffusion. Whilst transpiration is generally understood to be driven solely by the ordinary diffusion of water vapour along a concentration gradient, we consider the implications of thermodiffusion for transpiration. We develop a new modelling framework that introduces the effects of thermodiffusion on the transpiration rate, E. By applying this framework, we quantify the proportion of E attributable to thermodiffusion for a set of physiological and environmental conditions, varied over a wide range. Thermodiffusion is found to be most significant (in some cases > 30% of E) when a leaf-to-air temperature difference coincides with a relatively small water vapour concentration difference across the boundary layer; a boundary layer conductance that is large as compared to the stomatal conductance; or a relatively low transpiration rate. Thermodiffusion also alters the conditions required for the onset of reverse transpiration, and the rate at which this water vapour uptake occurs.

Classifying grains using behaviour-informed machine learning.

Sorting granular materials such as ores, coffee beans, cereals, gravels and pills is essential for applications in mineral processing, agriculture and waste recycling. Existing sorting methods are based on the detection of contrast in grain properties including size, colour, density and chemical composition. However, many grain properties cannot be directly detected in-situ, which significantly impairs sorting efficacy. We show here that a simple neural network can infer contrast in a wide range of grain properties by detecting patterns in their observable kinematics. These properties include grain size, density, stiffness, friction, dissipation and adhesion. This method of classification based on behaviour can significantly widen the range of granular materials that can be sorted. It can similarly be applied to enhance the sorting of other particulate materials including cells and droplets in microfluidic devices.

Shear-induced diffusion in dense granular fluids.

Granular materials are comprised of solid, athermal grains. Whilst immune to thermal motion, these grains move and diffuse when they undergo shear deformation. Here we introduce this process of shear-induced diffusion with a focus on dense flows. The goal is to present the established scaling laws for continuum diffusivity and to relate them to the micro-mechanisms of a granular random walk. We then suggest how this knowledge may help advance our understanding of granular rheology and diffusion in other soft-materials.

Inertial Force Transmission in Dense Granular Flows.

Dense granular flows are well described by several continuum models; however, their internal dynamics remain elusive. This study explores the contact force distributions in simulated steady and homogenous shear flows. The results demonstrate the existence of high magnitude contact forces in faster flows with stiffer grains. A proposed physical mechanism explains this rate-dependent force transmission. This analysis establishes a relation between contact forces and grain velocities, providing an entry point to unify a range of continuum models derived from either contact forces or grain velocity.

Viscosity of cohesive granular flows.

Cohesive granular materials such as wet sand, snow, and powders can flow like a viscous liquid. However, the elementary mechanisms of momentum transport in such athermal particulate fluids are elusive. As a result, existing models for cohesive granular viscosity remain phenomenological and debated. Here we use discrete element simulations of plane shear flows to measure the viscosity of cohesive granular materials, while tuning the intensity of inter-particle adhesion. We establish that two adhesion-related, dimensionless numbers control their viscosity. These numbers compare the force and energy required to break a bond to the characteristic stress and kinetic energy in the flow. This progresses the commonly accepted view that only one dimensionless number could control the effect of adhesion. The resulting scaling law captures strong, non-Newtonian variations in viscosity, unifying several existing viscosity models. We then directly link these variations in viscosity to adhesion-induced modifications in the flow micro-structure and contact network. This analysis reveals the existence of two modes of momentum transport, involving either grain micro-acceleration or balanced contact forces, and shows that adhesion only affects the latter. This advances our understanding of rheological models for granular materials and other soft materials such as emulsions and suspensions, which may also involve inter-particle adhesive forces.

Mobility in immersed granular materials upon cyclic loading.

We study the mobility of objects embedded in an immersed granular packing and subjected to cyclic loadings. With this aim, we conducted uplift experiments whereby a horizontal plate is embedded in the packing and subjected to a vertical cyclic force oscillating between zero and a maximum amplitude. Tests performed at different cyclic force frequencies and amplitudes evidence the development of three mobility regimes whereby the plate stays virtually immobile, moves up steadily, or slowly creeps upwards. Results show that steady plate uplift can occur at lower force magnitudes when the frequency is increased. We propose an interpretation of this frequency-weakening behavior based on force relaxation experiments and on the analysis of the mobility response of theoretical viscoelastoplastic mechanical analog. These results and analysis point out inherent differences in mobility response between steady and cyclic loadings in immersed granular materials.

Two mechanisms of momentum transfer in granular flows.

This Rapid Communication highlights the physical processes at the origin of the constitutive law of dense granular flows. In simulated plane shear flows, we present a micro-mechanical expression for the phenomenological friction law µ(I). The expression highlights two distinct pathways for momentum transport-through either balanced contact forces or grain micro-acceleration. We show that these two rate-dependent processes control and explain the friction law. This understanding may help advance rheological models for granular materials and other soft materials such as emulsions and suspensions.

Architectural Design of 3D Printed Scaffolds Controls the Volume and Functionality of Newly Formed Bone.

The successful regeneration of functional bone tissue in critical-size defects remains a significant clinical challenge. To address this challenge, synthetic bone scaffolds are widely developed, but remarkably few are translated to the clinic due to poor performance in vivo. Here, it is demonstrated how architectural design of 3D printed scaffolds can improve in vivo outcomes. Ceramic scaffolds with different pore sizes and permeabilities, but with similar porosity and interconnectivity, are implanted in rabbit calvaria for 12 weeks, and then the explants are harvested for microcomputed tomography evaluation of the volume and functionality of newly formed bone. The results indicate that scaffold pores should be larger than 390 µm with an upper limit of 590 µm to enhance bone formation. It is also demonstrated that a bimodal pore topology-alternating large and small pores-enhances the volume and functionality of new bone substantially. Moreover, bone formation results indicate that stiffness of new bone is highly influenced by the scaffold's permeability in the direction concerned. This study demonstrates that manipulating pore size and permeability in a 3D printed scaffold architecture provides a useful strategy for enhancing bone regeneration outcomes.

Vortices Enhance Diffusion in Dense Granular Flows.

This Letter introduces unexpected diffusion properties in dense granular flows and shows that they result from the development of partially jammed clusters of grains, or granular vortices. Transverse diffusion coefficients D and average vortex sizes ℓ are systematically measured in simulated plane shear flows at differing inertial numbers I revealing (i) a strong deviation from the expected scaling D∝d^{2}γ[over ˙] involving the grain size d and shear rate γ[over ˙] and (ii) an increase in average vortex size ℓ at low I, following ℓ∝dI^{-1/2} but limited by the system size. A general scaling D∝ℓdγ[over ˙] is introduced that captures all the measurements and highlights the key role of vortex size. This leads to establishing a scaling for the diffusivity in dense granular flow as D∝d^{2}sqrt[γ[over ˙]/t_{i}] involving the geometric average of shear time 1/γ[over ˙] and inertial time t_{i} as the relevant time scale. Analysis of grain trajectories is further evidence that this diffusion process arises from a vortex-driven random walk.