In this article, we study the self-weight consolidation behavior of kaolinite suspensions with different concentrations in deionized water using nuclear magnetic resonance (NMR). NMR enables the direct assessment of density distributions and pore size within the consolidating suspensions. The results show that electrochemical conditions (pH and ionic strength), arising from ion leaching from the kaolinite, influence the consolidation dynamics, in agreement with previous studies. The evolution of the density profile over time is interpreted using a large-strain consolidation model based on the Gibson–Merckelbach formulation. The model is implemented in both Eulerian and Lagrangian frameworks, allowing a comparison between these two approaches. A key observation from the NMR measurements is that the solid volume fraction reaches a maximum value at the base of the column. This behavior is not captured by the classical Merckelbach–Kranenburg constitutive model, highlighting its limitations in highly compacted regimes. To account for this effect, a simple modification based on a reduction in permeability is introduced. This modification can be interpreted as a hydraulic limitation, as it leads to vanishing fluid fluxes and prevents further densification. The comparison between experimental and numerical results shows that this approach improves the agreement with the measured density profiles. In addition, the model captures the main trends of the pore size distribution measured by NMR, although some discrepancies remain in magnitude. Overall, the combined experimental–numerical approach provides new insight into the applicability and limitations of Gibson–Merckelbach consolidation models for fine-grained suspensions.

This paper proposes a new technique for the 3D identification of clay particle orientations using images obtained from FIB-SEM observations. The method is based on a three-dimensional reconstruction that combines the Focused Ion Beam abrasion technique and Scanning Electron Microscopy, applied to kaolinitic clay selected for this study. The clay was first subjected to one-dimensional compression up to a given stress level, after which microstructural observations were performed using a post-mortem approach. A novel methodology using appropriate image processing was established for this purpose, allowing for a precise treatment of the obtained FIB-SEM images. The proposed methodology first involved removing “curtain effects” and “charging artefact”, which are specific types of noise commonly associated with FIB-SEM images. Two methods were employed to address this issue and were compared to evaluate their effectiveness: the first method was based on Fourier Transformation and Total Variational Reconstruction, while the second used a stochastic approach formulated as a convex optimization problem. Subsequently, a machine learning technique was integrated to enhance the segmentation process of the images. The final stage of the methodology involved creating a 3D model by reconstructing the clay particles in their spatial configuration. This paper aims to demonstrate how the proposed 3D observation method enables the quantification of the structural organization of clay particles in space in relation to mechanical loading.

This study presents a method to determine surface relaxivity in soft sediments by combining one-dimensional Nuclear Magnetic Resonance (NMR) imaging with particle size and shape estimates. In order to determine the surface relaxivity up to now often methods like Mercury Intrusion Porosimetry or Brunauer–Emmett–Teller (BET) are used which where drying steps are involved which can alter material properties during analysis, particularly in highly deformable materials, making these techniques unreliable for soft soils. By combining NMR relaxometry and estimates of particle sizes and shapes of a soft soil, this new approach provides accurate, non-invasive surface relaxivity measurements. This method is demonstrated on kaolinite, glass beads, and natural soils, showing that this method supports detailed assessment of pore size distributions in soft sediments, benefiting geotechnical and environmental research where soil stability is critical.

Dewatering, which is the process of separating (colloidal) suspended particles from a solvent (usually water), is used in many engineering applications (sanitary engineering, dredging engineering…). Key questions associated with dewatering in the context of the reuse of dredged sediment are (1) what is the process kinetics, (2) how can these processes be optimized and (3) can the dewatered sludge be reused and for which application? Dewatering and consolidation are functions of the suspended particles’ size and type, and their solvent-mediated interaction. In this presentation, some examples will be given about the dewatering of suspensions and slurries as found in engineering applications. The presentation will focus on the behaviour of mineral clay suspensions (kaolinite, montmorillonite, illite…) composed of particles of different particle sizes. We will show that, depending on the particle size distribution and solvent properties, the system is either undergoing a slow sedimentation dominated by thermodynamic forces or a rapid sedimentation dominated by gravity. The sedimentation is followed in time using NMR and inferential image analysis, and the particles are characterized by size, density and electrokinetic charge. We show that the time evolution of the sedimentation behaviour can be modelled using an advection-diffusion equation. The advective term is a function of gravity, whereas the diffusion term represents either a hard-sphere repulsion or an effective stress, depending on whether thermodynamic forces dominate the system. We show that after solving this advection-diffusion equation numerically, the results based on the theory of Gibson does match the experimental data collected from NMR in the phase of slow kinetics. For the early stages of settling and consolidation, where the system kinetics are fast, we show that the data are contaminated by artifacts due to the limited time of signal acquisition imposed by the NMR method. We show that is possible to overcome those limitations by either sacrificing some information related to particle’s sizes using the NMR or by combining the NMR method with excess pore pressure measurements along the height of the settling columns.