Thermal and mechanical energy storage is pivotal for the effective exploitation of renewable energy sources, thus fostering the transition to a sustainable economy. Hydrogen-based systems are among the most promising solutions for electrical energy storage. However, several technical and economic barriers (e.g., high costs, low energy and power density, advanced material requirements) still hinder the diffusion of such solutions. Similarly, the realization of latent heat storages through phase change materials is particularly attractive because it provides high energy density in addition to allowing for the storage of the heat of fusion at a (nearly) constant temperature. In this paper, we posit the challenge to couple a metal hydride H canister with a latent heat storage, in order to improve the overall power density and realize a passive control of the system temperature. A highly flexible numerical solver based on a hybrid Lattice Boltzmann Phase-Field (LB-PF) algorithm is developed to assist the design of the hybrid PCM-MH tank by studying the melting and solidification processes of paraffin-like materials. The present approach is used to model the storage of the heat released by the hydride during the H loading process in a phase change material (PCM). The results in terms of Nusselt numbers are used to design an enhanced metal-hydride storage for H-based energy systems, relevant for a reliable and cost-effective "Hydrogen Economy". The application of the developed numerical model to the case study demonstrates the feasibility of the posited design. Specifically, the phase change material application significantly increases the heat flux at the metal hydride surface, thus improving the overall system power density.

Understanding the fluid-structure interaction is crucial for an optimal design and manufacturing of soft mesoscale materials. Multi-core emulsions are a class of soft fluids assembled from cluster configurations of deformable oil-water double droplets (cores), often employed as building-blocks for the realisation of devices of interest in bio-technology, such as drug-delivery, tissue engineering and regenerative medicine. Here, we study the physics of multi-core emulsions flowing in microfluidic channels and report numerical evidence of a surprisingly rich variety of driven non-equilibrium states (NES), whose formation is caused by a dipolar fluid vortex triggered by the sheared structure of the flow carrier within the microchannel. The observed dynamic regimes range from long-lived NES at low core-area fraction, characterised by a planetary-like motion of the internal drops, to short-lived ones at high core-area fraction, in which a pre-chaotic motion results from multi-body collisions of inner drops, as combined with self-consistent hydrodynamic interactions. The onset of pre-chaotic behavior is marked by transitions of the cores from one vortex to another, a process that we interpret as manifestations of the system to maximize its entropy by filling voids, as they arise dynamically within the capsule.

This work presents a microscale approach for simulating the dielectrophoresis assembly of polarizable particles under an external electric field. The model is shown to capture interesting dynamical and topological features, such as the formation of chains of particles and their incipient aggregation into hierarchical structures. A quantitative characterization in terms of the number and size of these structures is also discussed. This computational model could represent a viable numerical tool to study the mechanical properties of particle-based hierarchical materials and suggest new strategies for enhancing their design and manufacture. This article is part of the theme issue 'Progress in mesoscale methods for fluid dynamics simulation'.

One of the most distinctive hallmarks of many-body systems far from equilibrium is the spontaneous emergence of order under conditions where disorder would be plausibly expected. Here, we report on the self-transition between ordered and disordered emulsions in divergent microfluidic channels, i.e., from monodisperse assemblies to heterogeneous polydisperse foamlike structures, and back again to ordered ones. The transition is driven by the nonlinear competition between viscous dissipation and surface tension forces as controlled by the device geometry, particularly the aperture angle of the divergent microfluidic channel. An unexpected route back to order is observed in the regime of large opening angles, where a trend towards increasing disorder would be intuitively expected.

We present a deep learning-based object detection and object tracking algorithm to study droplet motion in dense microfluidic emulsions. The deep learning procedure is shown to correctly predict the droplets' shape and track their motion at competitive rates as compared to standard clustering algorithms, even in the presence of significant deformations. The deep learning technique and tool developed in this work could be used for the general study of the dynamics of biological agents in fluid systems, such as moving cells and self-propelled microorganisms in complex biological flows. This article is part of the theme issue 'Progress in mesoscale methods for fluid dynamics simulation'.

We numerically study the dynamics of a polydisperse double emulsion under a symmetric shear flow. We show that both dispersity and shear rate crucially affect the behavior of the innermost drops and of the surrounding shell. While at low/moderate values of shear rates, the inner drops rotate periodically around a common center of mass triggered by the fluid vortex formed within the emulsion generally regardless of their polydispersity; at higher values, such dynamics occurs only at increasing polydispersity, since monodisperse drops are found to align along the shear flow and become approximately motionless at late times. Our simulations also suggest that increasing polydispersity favors close-range contacts among cores and persistent collisions, while hindering shape deformations of the external droplet. A quantitative evaluation of these effects is also provided.

We numerically study the translocation dynamics of double emulsion drops with multiple close-packed inner droplets within constrictions. Such liquid architectures, which we refer to as HIPdEs (high-internal phase double emulsions), consist of a ternary fluid, in which monodisperse droplets are encapsulated within a larger drop in turn immersed in a bulk fluid. Extensive two-dimensional lattice Boltzmann simulations show that if the area fraction of the internal drops is close to the packing fraction limit of hard spheres and the height of the channel is much smaller than the typical size of the emulsion, the crossing yields permanent shape deformations persistent over long periods of time. Morphological changes and rheological response are quantitatively assessed in terms of the structure of the velocity field, circularity of the emulsion, and rate of energy dissipated by viscous forces. Our results may be used to improve the design of soft mesoscale porous materials, which employ HIPdEs as templates for tissue engineering applications.

The state-of-the-art deep learning-based object recognition YOLO algorithm and object tracking DeepSORT algorithm are combined to analyze digital images from fluid dynamic simulations of multi-core emulsions and soft flowing crystals and to track moving droplets within these complex flows. The YOLO network was trained to recognize the droplets with synthetically prepared data, thereby bypassing the labor-intensive data acquisition process. In both applications, the trained YOLO + DeepSORT procedure performs with high accuracy on the real data from the fluid simulations, with low error levels in the inferred trajectories of the droplets and independently computed ground truth. Moreover, using commonly used desktop GPUs, the developed application is capable of analyzing data at speeds that exceed the typical image acquisition rates of digital cameras (30 fps), opening the interesting prospect of realizing a low-cost and practical tool to study systems with many moving objects, mostly but not exclusively, biological ones. Besides its practical applications, the procedure presented here marks the first step towards the automatic extraction of effective equations of motion of many-body soft flowing systems.

The rheology of pressure-driven flows of two-dimensional dense monodisperse emulsions in neutral wetting microchannels is investigated by means of mesoscopic lattice Boltzmann simulations, capable of handling large collections of droplets, in the order of several hundreds. The simulations reveal that the fluidization of the emulsion proceeds through a sequence of discrete steps, characterized by yielding events whereby layers of droplets start rolling over each other, thus leading to sudden drops of the relative effective viscosity. It is shown that such discrete fluidization is robust against loss of confinement, namely it persists also in the regime of small ratios of the droplet diameter over the microchannel width. We also develop a simple phenomenological model which predicts a linear relation between the relative effective viscosity of the emulsion and the product of the confinement parameter (global size of the device over droplet radius) and the viscosity ratio between the disperse and continuous phases. The model shows excellent agreement with the numerical simulations. The present work offers new insights to enable the design of microfluidic scaffolds for tissue engineering applications and paves the way to detailed rheological studies of soft-glassy materials in complex geometries.

The code is designed to exploit parallel computing platforms, taking advantage also of the recent AVX-512 instruction set. We focus on LBsoft structure, functionality, parallel implementation, performance and availability, so as to facilitate the access to this computational tool to the research community in the field. We present LBsoft, an open-source software developed mainly to simulate the hydro-dynamics of colloidal systems based on the concurrent coupling between lattice Boltzmann methods for the fluid and discrete particle dynamics for the colloids. Such coupling has been developed before, but, to the best of our knowledge, no detailed discussion of the programming issues to be faced in order to attain efficient implementation on parallel architectures, has ever been presented to date. In this paper, we describe in detail the underlying multi-scale models, their coupling procedure, along side with a description of the relevant input variables, to facilitate third-parties usage.

We present a mechanistic model of drug release from a multiple emulsion into an external surrounding fluid. We consider a single multilayer droplet where the drug kinetics are described by a pure diffusive process through different liquid shells. The multilayer problem is described by a system of diffusion equations coupled via interlayer conditions imposing continuity of drug concentration and flux. Mass resistance is imposed at the outer boundary through the application of a surfactant at the external surface of the droplet. The two-dimensional problem is solved numerically by finite volume discretization. Concentration profiles and drug release curves are presented for three typical round-shaped (circle, ellipse, and bullet) droplets and the dependency of the solution on the mass transfer coefficient at the surface analyzed. The main result shows a reduced release time for an increased elongation of the droplets.

We numerically investigate the rheological response of a noncoalescing multiple emulsion under a symmetric shear flow. We find that the dynamics significantly depends on the magnitude of the shear rate and on the number of the encapsulated droplets, two key parameters whose control is fundamental to accurately select the resulting nonequiibrium steady states. The double emulsion, for instance, attains a static steady state in which the external droplet stretches under flow and achieves an elliptical shape (closely resembling the one observed in a sheared isolated fluid droplet), while the internal one remains essentially unaffected. Novel nonequiibrium steady states arise in a multiple emulsion. Under low/moderate shear rates, for instance, the encapsulated droplets display a nontrivial planetarylike motion that considerably affects the shape of the external droplet. Some features of this dynamic behavior are partially captured by the Taylor deformation parameter and the stress tensor. Besides a theoretical interest on its own, our results can potentially stimulate further experiments, as most of the predictions could be tested in the lab by monitoring droplets' shapes and position over time. Published under license by AIP Publishing.

We present an extension of the multiparticle collision dynamics method for flows with complex interfaces, including supramolecular near-contact interactions mimicking the effect of surfactants. The new method is demonstrated for the case of (i) short range repulsion of droplets in close contact, (ii) arrested phase separation, and (iii) different pattern formation during spinodal decomposition of binary mixtures.

Bicontinuous interfacially jammed emulsion gels ("bijels") represent a new class of soft materials made of a densely packed monolayer of solid particles sequestered at the interface of a bicontinuous fluid. Their mechanical properties are relevant to many applications, such as catalysis, energy conversion, soft robotics, and scaffolds for tissue engineering. While their stationary bulk properties have been covered in depth, much less is known about their behavior in the presence of an external shear. In this paper, we numerically study the dynamics of a bijel confined within a three-dimensional rectangular domain and subject to a symmetric shear flow sufficiently intense to break the material. Extensive numerical simulations reveal that the shear flow generally promotes the detachment of a sizable amount of particles from the fluid interface and their accumulation in the bulk. Fluid interfaces undergo large stretching and deformations along the flow direction, an effect that reduces their capability of entrapping particles. These results are supported by a series of quantitative indicators such as (i) curvature of the fluid interface, (ii) spatial distribution of the colloidal particles, and (iii) fluid flow structure within the microchannel. (c) 2020 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

We provide a brief survey of our current developments in the simulation-based design of novel families of mesoscale porous materials using computational kinetic theory. Prospective applications on exascale computers are also briefly discussed and commented on, with reference to two specific examples of soft mesoscale materials: microfluid crystals and bi-continuous jels.

We numerically study the dynamic behavior under a symmetric shear flow of selected examples of concentrated phase emulsions with multicore morphology confined within a microfluidic channel. A variety of nonequilibrium steady states is reported. Under low shear rates, the emulsion is found to exhibit a solidlike behavior, in which cores display a periodic planetarylike motion with approximately equal angular velocity. At higher shear rates, two steady states emerge, one in which all inner cores align along the flow and become essentially motionless and a further one in which some cores accumulate near the outer interface and produce a dynamical elliptical-shaped ring chain, reminiscent of a treadmillinglike structure, while others occupy the center of the emulsion. A quantitative description in terms of the (i) motion of the cores, (ii) rate of deformation of the emulsion, and (iii) structure of the fluid flow within the channel is also provided.

Recent numerical analyses to optimize the design of microfluidic devices for more effective entrapment or segregation of surrogate circulating tumor cells (CTCs) from healthy cells have been reported in the literature without concurrently accommodating the non-Newtonian nature of the body fluid and the non-uniform geometric shapes of the CTCs. Through a series of two-dimensional proof-of-concept simulations with increased levels of complexity (e.g., number of particles, inline obstacles), we investigated the validity of the assumptions of the Newtonian fluid behavior for pseudoplastic fluids and the circular particle shape for different-shaped particles (DSPs) in the context of microfluidics-facilitated shape-based segregation of particles. Simulations with a single DSP revealed that even in the absence of internal geometric complexities of a microfluidics channel, the aforementioned assumptions led to 0.11-0.21W (W is the channel length) errors in lateral displacements of DSPs, up to 3-20% errors in their velocities, and 3-5% errors in their travel times. When these assumptions were applied in simulations involving multiple DSPs in inertial microfluidics with inline obstacles, errors in the lateral displacements of DSPs were as high as 0.78W and in their travel times up to 23% , which led to different (un)symmetric flow and segregation patterns of DSPs. Thus, the fluid type and particle shape should be included in numerical models and experiments to assess the performance of microfluidics for targeted cell (e.g., CTCs) harvesting.

We present an analytical derivation of the transport coefficients of a relativistic gas in (2 + 1) dimensions for both Chapman-Enskog (CE) asymptotics and Grad's expansion methods. We further develop a systematic calibration method, connecting the relaxation time of relativistic kinetic theory to the transport parameters of the associated dissipative hydrodynamic equations. Comparison of our analytical results and numerical simulations shows that the CE method correctly captures dissipative effects, while Grad's method does not, in agreement with previous analyses performed in the (3 + 1)-dimensional case. These results provide a solid basis for accurately calibrated computational studies of relativistic dissipative flows.

Motility behavior of an engineered chemosensory particle (ECP) in fluidic environments is driven by its responses to chemical stimuli. One of the challenges to understanding such behaviors lies in tracking changes in chemical signal gradients of chemoattractants and ECP-fluid dynamics as the fluid is continuously disturbed by ECP motion. To address this challenge, we introduce a new multiscale numerical model to simulate chemotactic swimming of an ECP in confined fluidic environments by accounting for motility-induced disturbances in spatiotemporal chemoattractant distributions. The model accommodates advective-diffusive transport of unmixed chemoattractants, ECP-fluid hydrodynamics at the ECP-fluid interface, and spatiotemporal disturbances in the chemoattractant concentrations due to particle motion. Demonstrative simulations are presented with an ECP, mimicking Escherichia coli (E. coli) chemotaxis, released into initially quiescent fluids with different source configurations of the chemoattractants N-methyl-L-aspartate and L-serine. Simulations demonstrate that initial distributions and temporal evolution of chemoattractants and their release modes (instantaneous vs. continuous, point source vs. distributed) dictate time histories of chemotactic motility of an ECP. Chemotactic motility is shown to be largely determined by spatiotemporal variation in chemoattractant concentration gradients due to transient disturbances imposed by ECP-fluid hydrodynamics, an observation not captured in previous numerical studies that relied on static chemoattractant concentration fields.

In this paper, we develop a three-dimensional multiple-relaxation-time lattice Boltzmann method (MRT-LBM) based on a set of non-orthogonal basis vectors. Compared with the classical MRT-LBM based on a set of orthogonal basis vectors, the present non-orthogonal MRT-LBM simplifies the transformation between the discrete velocity space and the moment space and exhibits better portability across different lattices. The proposed method is then extended to multiphase flows at large density ratio with tunable surface tension, and its numerical stability and accuracy are well demonstrated by some benchmark cases. Using the proposed method, a practical case of a fuel droplet impacting on a dry surface at high Reynolds and Weber numbers is simulated and the evolution of the spreading film diameter agrees well with the experimental data. Furthermore, another realistic case of a droplet impacting on a super-hydrophobic wall with a cylindrical obstacle is reproduced, which confirms the experimental finding of Liu et al. ["Symmetry breaking in drop bouncing on curved surfaces," Nat. Commun. 6, 10034 (2015)] that the contact time is minimized when the cylinder radius is comparable with the droplet radius.