We investigate a trapping mechanism for passive Brownian particles based on mixtures with self-propelled dipolar colloids. Active dipoles, whose magnetic moment is oriented perpendicularly to their propulsion direction, spontaneously form dynamic chains that collapse into clusters through dipole-dipole interactions. These transient structures efficiently capture nearby passive particles, forming dense phases at relatively low global packing fractions. Using Brownian dynamics simulations, we analyze how the capture efficiency depends on the Péclet number (Pe) and dipolar interaction strength (λ). We demonstrate that an external magnetic field, applied briefly to align the active dipoles, significantly enhances trapping efficiency, with capture fractions exceeding 50% under optimal conditions. Our results reveal a nontrivial competition between activity and dipolar forces, governed by the ratio λ/Pe, and offer insights into designing self-organized trapping strategies for passive colloids.

Assemblies of magnetic beads, also called magnetostructures, exhibit interesting mechanical properties, adapting orientations of the dipoles to minimize the dipolar energy. A ring made of N spherical magnetic beads behaves like an elastic annulus. This elastic-like property is due to the dipolar nature of the particles. When submitted to gravity and as a function of its size, the initial circular shape of a magnetic ring is seen to experience flattening. This capsule-like shape appears when the number N of magnets reaches a critical point scaling with the Bond number N_{f}∝Bo^{-1/3}. When the number of magnets increases more and more, the ring starts to buckle and a flat object appears at a second critical point N_{z}∝Bo^{-1}+b. There, a zipping state corresponding to the attraction of two opposite sides is formed. We propose a theoretical approach to capture these scaling laws in agreement with experimental data. All shapes are also numerically obtained in a discrete element model confirming our findings.

Once granular materials flow, particles charge because of the triboelectric effect. When particles touch each other, charges are exchanged during contact whether they are made of the same material or not. Surprisingly, when different sizes of particles are mixed together, large particles tend to charge positively while small particles charge negatively. If the particles are relatively small (typically smaller than a millimeter), the electrostatic interaction between the particles becomes significant and leads to aggregation or sticking on the surface of the container holding them. Studying those effects is challenging as the mechanisms that govern the triboelectric effect are not fully understood yet. We show that the patch model (or mosaic model) is suitable to reproduce numerically the flow of triboelectrically charged granular materials as the specific charging of bi-disperse granular materials can be retrieved. We investigate the influence of charging on the cohesion of granular materials and highlight the relevant parameters related to the patch model that influence cohesion. Our results shed new light on the mechanisms of the triboelectric effect as well as on how the charging of granular materials influences cohesion using numerical simulations.

Granular fluids, as defined by a collection of moving solid particles, is a paradigm of a dissipative system out of equilibrium. Inelastic collisions between particles is the source of dissipation, and is the origin of a transition from a gas to a liquidlike state. This transition can be triggered by an increase of the solid fraction. Moreover, in compartmentalized systems, this condensation is driving the entire granular fluid into a Maxwell demon phenomenon, localizing most of the grains into a specific compartment. Classical approaches fail to capture these phenomena, thus motivating many experimental and numerical works. Herein, we demonstrate that the Onsager variational principle is able to predict accurately the coexistence of gas-liquid states in granular systems, opening ways to model other phenomena observed in such dissipative systems like segregation or the jamming transition.

The out-of-equilibrium aggregation of dipolar particles, such as magnetized beads, leads to the formation of large structures composed of chains, loops, and eventually ribbons. In the present study, we focus on the evolution of these different substructures in a two-dimensional system confined within progressively shrinking environments. Using numerical simulations, we identify structural events as a function of the packing fraction. At low density, a percolation threshold p 0.15 is evidenced, where chainlike structures merge into a single large aggregate with significant voids. This gel-like structure then densifies as increases. At large values, crystallites of both square and hexagonal order phase appear, but they are far from extending over the whole system.

Neodymium spherical magnets are inexpensive objects that demonstrate how dipolar particles self-assemble into various structures ranging from 1D chains to 3D crystals. Assemblies of these magnets are nicknamed magnetostructures and this paper focuses on a variety called magnetotubes, which are some curved square lattices forming cylinders. We experimentally and numerically observe that such magnetotubes can self-buckle, above a critical aspect ratio. In fact, the underlying dipolar ordering of such structures is found to exhibit a collective reorganization, altering the mechanical stability of the entire system. We identify the conditions in which these phenomena occur, and we emphasize that metastable states coexist. This suggests that a wide variety of magnetostructures, including chains and magnetocrystals, may collapse due to the coexistence of multiple ground states and global reorientation of dipoles.

We present a numerical study of the collective behavior of self-propelled particles for which dipolar interactions are considered. These are obtained by introducing pointlike magnetic dipoles in the particles. Various dynamical regimes are found depending on three major parameters: the density of particles, the ratio Γ defined as the competition between kinetic energy and potential magnetic energy, as well as the orientation of the magnetic dipoles inherent to the particles. Patterns such as chains, vortices, flocks, and strips have been obtained.

Granular multiparticle ensembles are of interest from fundamental statistical viewpoints as well as for the understanding of collective processes in industry and in nature. Extraction of physical data from optical observations of three-dimensional (3D) granular ensembles poses considerable problems. Particle-based tracking is possible only at low volume fractions, not in clusters. We apply shadow-based and feature-tracking methods to analyze the dynamics of granular gases in a container with vibrating side walls under microgravity. In order to validate the reliability of these optical analysis methods, we perform numerical simulations of ensembles similar to the experiment. The simulation output is graphically rendered to mimic the experimentally obtained images. We validate the output of the optical analysis methods on the basis of this ground truth information. This approach provides insight in two interconnected problems: the confirmation of the accuracy of the simulations and the test of the applicability of the visual analysis. The proposed approach can be used for further investigations of dynamical properties of such media, including the granular Leidenfrost effect, granular cooling, and gas-clustering transitions.

We experimentally investigate the effect of the grain shape on the flow of granular material. The grain shape is modified to highlight the effect of grain circularity on granular flow in a 2D rotating drum. Using a laser cutter, we create particles with decreasing circularity. We observe that the effect of grain shape depends on the rotation speed of the drum. For high rotation speed, granular flow is influenced by the packing’s dilatancy whereas, at low rotation speed, packing fraction seems to influence flowing dynamics. We link these two measurements to grain shape in order to explain its effect on granular flow.

Powder flowability is a critical parameter for additive manufacturing techniques involving powders. In order to obtain thin and homogenous powder layers, a compromise between grain size and flowability has to be found. Unfortunately, when the grain size decreases, the cohesiveness increases and the flowability decreases. Too often, both the powder spreadability assessment and the optimization of printing parameters are costly empiric processes. In this paper, we describe an original method associating GranuDrum powder flow characterization instrument and DEM numerical simulations to asses the process-ability of powders and to optimize printing parameters like recoater speed, layer thickness or recoater geometry. The powder characterization allows to calibrate the simulation parameters and in particular to quantify the inter-grain cohesiveness. Then, the recoating process is simulated with the calibrated simulations to predict the behaviour of the powder inside the printer. In parallel, the results are validated by testing the powder in a printer equipped with an in-situ powder layer homogeneity tester based on image analysis.

The flow of cohesive granular materials in a two-dimensional rotating drum is investigated using discrete element method simulations. Contacts between particles are modeled based on the widely used model of the spring-dashpot and Coulomb's friction law. A simplified model of intermediate range attraction between grains (i.e., cohesion) has been used in order to reproduce the flow of electrostatic or wet granular materials. Granular flow is generated by means of a rotating drum and the effect of the rotation speed, the friction between the grains, and the cohesion are studied. Significantly different flow behaviors are observed when cohesion is added. Plug flow appears in the rotating drum for a wide range of rotation speeds when cohesion becomes sufficiently strong. We propose a measurement of surface flow fluctuations to quantify the strength of cohesion, inspired by the previous observation of plug flow. Then, we make use of the results to include the effect of cohesion into a theoretical flow model. A good agreement is obtained between theory and numerical measurements of the granular bed's dynamic angle of repose, which allows us to propose a method for estimating the microscopic cohesion between grains based on the measurement of surface fluctuations.

Granular flow is a complex process depending on a large set of parameters such as grain morphology, surface friction, flow geometry, stress field and cohesion (e.g. attractive interaction between grains). The latter arises from the presence of humidity, electrostatic charges and Van der Waals forces within the grains that lead, among other effects, to the appearance of surface flow fluctuations also called avalanches. Those surface fluctuations produce an intermittent granular flow and determine the processability of a powder in many application. In order to link the flow fluctuations and the cohesion between grains, we reproduced numerically with a DEM model the flow of cohesive granular materials in a 2D rotating drum. A simplified cohesive interaction between circular grains has been implemented and the granular flow has been analyzed through the flowing angle and the interface fluctuations. The numerical results are compared with experimental results obtained with GranuDrum instrument and a set of silicon carbide grains with different grain sizes and therefore different cohesiveness. The motivation behind this study is to determine to what extent a simplified model can reproduce a complex flow. The similarities between numerical and experimental results and also the discrepancies are discussed. This comparison gives a fundamental background to the cohesive index parameter measured with GranuDrum instrument from the interface fluctuations. Finally, we show that comparing the flow inside a rotating drum obtained numerically and experimentally is a practical way to calibrate a set of parameters before the simulation of a complex process.

We study experimentally the dynamical behavior of few large tracer particles placed in a quasi-2D granular ``gas'' made of many small beads in a low-gravity environment. Multiple inelastic collisions transfer momentum from the uniaxially driven gas to the tracers whose velocity distributions are studied through particle tracking. Analyzing these distributions for an increasing system density reveals that translational energy equipartition is reached at the onset of the gas-liquid granular transition corresponding to the emergence of local clusters. The dynamics of a few tracer particles thus appears as a simple and accurate tool to detect this transition. A model is proposed for describing accurately the formation of local heterogeneities.

Mixing granular particles of di erent sizes is a common way of increasing the packing fraction. Recently, a model predicting the packing fraction, taking into account the inhomogeneity of the mixed small and large particles, has been proposed by S. Pillitteri et al. Under certain conditions, this model can be simpli ed and analytical solutions can be found. We present here these solutions, compared to experimental data, and the physical interpretation they can bring.

We perform three-dimensional particle-based simulations of confined, vibrated, and magnetizable beads to study the effect of cell geometry on pattern selection. For quasi-two-dimensional systems, we reproduce previously observed macroscopic patterns such as hexagonal crystals and labyrinthine structures. For systems at the crossover from two to three dimensions, labyrinthine branches shorten and are replaced by triplets of beads forming upright triangles which self-organize into a herringbone pattern. This transition is associated with increases in both translational and orientational orders.

For reaching high packing fractions, grains of various sizes are often mixed together allowing the small grains to fill the voids created by the large ones. However, in most cases, granular segregation occurs leading to lower packing fractions. We performed a wide set of experiments with different binary granular systems, proving that two main parameters are respectively the volume fraction f of small beads and the grain size ratio α. In addition, we show how granular segregation affects the global packing fraction. We propose a model with a strong dependency on α that takes into account possible granular segregation. Our model is in good agreement with both earlier experimental and simulation data.

For a few decades, the influence of a magnetic field on the aggregation process of superparamagnetic colloids has been well known on short time scale. However, the accurate study of the equilibrium state is still challenging on some aspects. On the numerical aspect, current simulations have only access to a restricted set of experimental conditions due to the computational cost of long-range interactions in many-body systems. In the present paper, we numerically explore a new range of parameters thanks to sped up numerical simulations validated by a recent experimental and numerical study. We first show that our simulations reproduce results from previous study in well-established conditions. Then we show that unexpectedly long chains are observed for higher volume fractions and intermediate fields. We also present theoretical developments taking into account the interaction between the chains which are able to reproduce the data that we obtained with our simulations. We finally confirm this model thanks to experimental data.

Binary granular mixtures are known to show various packing arrangements depending on both fractions and size ratios of their components. While the final packing fraction can be estimated by geometrical arguments, the dynamics of the pile submitted to gentle vibrations towards a dense state is seen to be highly size ratio dependent. We observe experimentally a diverging compaction characteristic time close to a critical size ratio, such that the grain mobility in the packing is the lowest close to the percolation threshold, when small particles can pass through the voids left by the large ones. Moreover, we evidence a fast compaction dynamics regime when the grain size ratio is large enough.

Asteroids and other Small Solar System Bodies (SSSBs) are of high general and scientific interest in many aspects. The origin, formation, and evolution of our Solar System (and other planetary systems) can be better understood by analysing the constitution and physical properties of small bodies in the Solar System. Currently, two space missions (Hayabusa2, OSIRIS-REx) have recently arrived at their respective targets and will bring a sample of the asteroids back to Earth. Other small body missions have also been selected by, or proposed to, space agencies. The threat posed to our planet by near-Earth objects (NEOs) is also considered at the international level, and this has prompted dedicated research on possible mitigation techniques. The DART mission, for example, will test the kinetic impact technique. Even ideas for industrial exploitation have risen during the last years. Lastly, the origin of water and life on Earth appears to be connected to asteroids. Hence, future space mission projects will undoubtedly target some asteroids or other SSSBs. In all these cases and research topics, specific knowledge of the structure and mechanical behaviour of the surface as well as the bulk of those celestial bodies is crucial. In contrast to large telluric planets and dwarf planets, a large proportion of such small bodies is believed to consist of gravitational aggregates ('rubble piles') with no—or low—internal cohesion, with varying macro-porosity and surface properties (from smooth regolith covered terrain, to very rough collection of boulders), and varying topography (craters, depressions, ridges). Bodies with such structure can sustain some plastic deformation without being disrupted in contrast to the classical visco-elastic models that are generally valid for planets, dwarf planets, and large satellites. These SSSBs are hence better described through granular mechanics theories, which have been a subject of intense theoretical, experimental, and numerical research over the last four decades. This being the case, it has been necessary to use the theoretical, numerical and experimental tools developed within soil mechanics, granular dynamics, celestial mechanics, chemistry, condensed matter physics, planetary and computer sciences, to name the main ones, in order to understand the data collected and analysed by observational astronomy (visible, thermal, and radio), and different space missions. In this paper, we present a review of the multi-disciplinary research carried out by these different scientific communities in an effort to study SSSBs.