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We developed quantitative fimA genotype assays and applied them in a pilot study investigating the fimbrial genotype distribution of Porphyromonas gingivalis in European subjects with or without chronic periodontitis. P. gingivalis was found in 71% and 9% of the samples from patients and healthy subjects, respectively. Enumeration of total P. gingivalis cell numbers by polymerase chain reaction and immunofluorescence showed excellent correspondence (r=0.964). 73% of positive samples contained multiple fimA genotypes, but generally one genotype predominated by one to three orders of magnitude. Genotype II predominated in 60% of the samples. Genotype IV occurred with similar prevalence (73%) as genotype II but predominated in only 20% of the samples. Genotypes I, III and V were of much lower prevalence and cell densities of the latter two remained sparse. Our results suggest marked differences among the fimA genotypes’ ability to colonize host sites with high cell numbers. [Copyright &y& Elsevier]

To prevent texture defects in powder-based processes, the sintering time needs to be adjusted such that a certain amount of coalescence is achieved. However, predicting the required sintering time is extremely challenging to assess in materials such as polymers because the kinetics exhibit both elastic and viscous characteristics when undergoing deformation. The present work introduces a computational approach to model the viscoelastic effect in the sintering of particles. The model contains three stages, three different mechanisms driven by adhesive inter-surface forces and surface tension, which describes the non-linear sintering behaviour. Experimental data from the binary coalescence of Polystyrene (PS), Polyamide (PA) 12 and PEEK 450PF particles are employed to calibrate the contact model, as implemented in MercuryDPM, an open-source software package. Using machine learning-based Bayesian calibration, good agreement is obtained between the experimental data and the numerical results. The findings will be used in future studies to predict densification rates in powder-based processes.

Granular matter, particulate matter and granular materials are generic terms to refer to systems composed of many macroscopic bodies (grains or particles) where the contact interaction (which is non-conservative) plays a crucial role in the behavior of the system. This contrasts with other systems (e.g., atomic or molecular systems) where the constituent bodies (e.g., atoms or molecules) interact via conservative forces. The non-conservative contact interactions come from inelastic collisions (due to plastic deformation, sound or heat production) and also from friction. This makes the study of granular matter a major challenge to scientists and the handling/storage/processing of granular materials a major challenge to engineers. Particulate matter covers a very broad range of systems, from those formed by fine particles (powders) to those formed by large rocks (derbis), from soft bodies (cotton balls) to hard grains (glass beads), from those we eat (muesli) to those we play with (beach sand), from those used to build our houses (cement) to those used to grow our crops (soil). Needless to say, any new knowledge in this area has a tremendous potential to impact our lives and our economy. Powders & Grains is a conference held every four years to bring together researchers working both in fundamental aspects of granular matter and in technological applications. This volume collects the 195 papers presented during the 2021 edition of P&G, which provide an excellent overview of the current state-of-the-art in granular matter and new trends with contributions form six continents.

The question of how soft granular matter, or dense amorphous systems, re-arrange their microstructure under isotropic compression and de-compression, at different strain rates, will be answered by particle simulations of frictionless model systems in a periodic three-dimensional cuboid. Starting compression below jamming, the systems experience the well known jamming transition, with characteristic evolutions of the state variables elastic energy, elastic stress, coordination number, and elastic moduli. For large strain rates, kinetic energy comes into play and the evolution is more dynamic. In contrast, at extremely slow deformation, the system relaxes to hyper-elastic states, with well-defined elastic moduli, in static equilibrium between irreversible (plastic) re-arrangement events, discrete in time. Small, finite strains explore those reversible (elastic) states, before larger strains push the system into new states, by irreversible, sudden re-arrangements of the micro-structure.

In partially wet granular beds, liquid migrates between particles due to collisions and contacts. This, in turn, influences the flow behaviour of the granular bed. We investigate liquid redistribution in moving monodisperse particles in a rotating drum using Discrete Element Method (DEM) simulations. For weak capillary forces, liquid re-distribution, induced by the continuous flow of particles, leads to concentration of the liquid in the core of the bed, where the flow is quasi-static. High capillary forces reduce the surface flow speed and granular temperature. This decreases liquid bridges rupturing in the flowing layer, allowing the liquid to remain in the outer region of the bed.

Poroelasticity theory predicts wave velocities in a saturated porous medium through a coupling between the bulk deformation of the solid skeleton and porous fluid flow. The challenge emerges below the characteristic wavelengths at which hydrodynamic interactions between grains and pore fluid become important. We investigate the pressure and volume fraction dependence of compressional- and shear-wave velocities in fluid-saturated, random, isotropic, frictional granular packings. The lattice Boltzmann method (LBM) and discrete element method (DEM) are two-way coupled to capture the particle-pore fluid interactions; an acoustic source is implemented to insert a traveling wave from the fluid reservoir to the saturated medium. We extract wave velocities from the acoustic branches in the wavenumber-frequency space, for a range of confining pressures and volume fractions. For random isotropic granular media the pressure-wave velocity data collapse on a single curve when scaled properly by the volume fraction.

When a mechanical wave travels through a medium, its intensity diminishes with distance. The research focuses on the energy transfer with distance as well as across different wavenumbers, as the mechanical wave propagates. The diffusive characteristic of energy propagation has been discussed for one-dimensional chains composed of random, pre-stressed soft and stiff particles interacting through Hertzian repulsive forces, which can be solved analytically after linearization. The effect of soft-stiff ratio (disorder in property) on energy transfer across wavenumbers is examined using a standing sinusoidal wave initial condition (with a specific wavenumber). From the total energy signals in wavenumber space, as function of time, it is observed that stronger disorder leads to more rapid loss of energy of the signal and faster transfer of energy to other wavenumbers.

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