Magnetic resonance imaging measurements evidence weak dispersion in homogeneous porous media

Understanding the Interactions of Nanoparticles and Dissolved Organic Matter at the Molecular Level by 1H 2D Multi-Exponential Transverse Relaxation NMR Spectroscopy

The interaction between humic acid (HA) and engineered nanoparticles (NPs) is critical in environmental sciences, especially for understanding the behavior of NPs in natural waters. This study employs 1H 2D Multi-Exponential Transverse Relaxation (METR) NMR spectroscopy to examine the molecular-level interactions between Pahokee Peat humic acid (HA) and carboxyl-functionalized iron oxide nanoparticles (NPCOs). First, 1H 2D METR NMR spectroscopy allowed not only the identification of HA in terms of its chemical composition but also the separation of molecules with the same chemical shift values but different rates of molecular tumbling. Then, using solutions with varying NPCO concentrations (0, 10, 40, and 100 μM), we observed significant changes in the T2 relaxation times of HA components, indicating interactions between HA and NPCO. Analysis showed the biggest effect on two chemical shift regions, corresponding to lipids and carbohydrates, revealing that smaller molecules within these regions exhibit the most significant changes in T2 values upon the addition of NPCO. This suggests that these molecules are the initial sites of interaction, with the entire HA system being affected at higher NPCO concentrations. These findings highlight the utility of METR NMR spectroscopy in studying complex environmental mixtures and provide insights into the behavior of HA and NPs, essential for understanding the fate of NPs in the environment.

3D pore-scale characterization of colloid aggregation and retention by confocal microscopy: Effects of fluid structure and ionic strength

Understanding the mechanisms of colloid transport and retention as well as the spatial distribution of colloids in porous media is an important topic for contamination transport and remediation in subsurface environments. Utilizing advanced three-dimensional visualization experiments, we effectively capture the intricate distribution characteristics of colloids in the 3D pore space and quantify the size of colloid clusters that aggregate at fluid-fluid interfaces and solid surfaces during two-phase flow. Our experimental results reveal the influence of pore-scale events, such as Haines jumps and pinch-off, on colloid retention. Our results also indicate that large drainage rates can facilitate colloid retention on solid surfaces, especially under the condition of high ionic strength. This can be attributed to the migration of colloids from the fluid-fluid interface to the solid surface, propelled by transients in the local fluid structure. The findings reveal a synergistic effect of the ionic strength and hydrodynamic conditions on colloid transport and retention during two-phase flow and provide important insights for predicting the fate and transport of contaminants in soil and groundwater environments involving multiple fluid phases.

Nonuniqueness of hydrodynamic dispersion revealed using fast 4D synchrotron x-ray imaging

Experimental and field studies reported a significant discrepancy between the cleanup and contamination time scales, while its cause is not yet addressed. Using high-resolution fast synchrotron x-ray computed tomography, we characterized the solute transport in a fully saturated sand packing for both contamination and cleanup processes at similar hydrodynamic conditions. The discrepancy in the time scales has been demonstrated by the nonuniqueness of hydrodynamic dispersion coefficient versus injection rate (Péclet number). Observations show that in the mixed advection-diffusion regime, the hydrodynamic dispersion coefficient of cleanup is significantly larger than that of the contamination process. This nonuniqueness has been attributed to the concentration-dependent diffusion coefficient during the cocurrent and countercurrent advection and diffusion, present in contamination and cleanup processes. The new findings enhance our fundamental understanding of transport processes and improve our capability to estimate the transport time scales of chemicals or pollution in geological and engineering systems.

Multi-exponential Transverse Relaxation Times Estimation from Magnetic Resonance Images under Rician Noise and Spatial Regularization

Relaxation signal inside each voxel of magnetic resonance images (MRI) is commonly fitted by a multi-exponential decay curve. The estimation of a discrete multi-component relaxation model parameters from magnitude MRI data is a challenging nonlinear inverse problem since it should be conducted on the entire image voxels under non-Gaussian noise statistics. This paper proposes an efficient algorithm allowing the joint estimation of relaxation time values and their amplitudes using different criteria taking into account a Rician noise model, combined with a spatial regularization accounting for low spatial variability of relaxation time constants and amplitudes between neighboring voxels. The Rician noise hypothesis is accounted for either by an adapted nonlinear least squares algorithm applied to a corrected least squares criterion or by a majorization-minimization approach applied to the maximum likelihood criterion. In order to solve the resulting large-scale non-negativity constrained optimization problem with a reduced numerical complexity and computing time, an optimization algorithm based on a majorization approach ensuring separability of variables between voxels is proposed. The minimization is carried out iteratively using an adapted Levenberg-Marquardt algorithm that ensures convergence by imposing a sufficient decrease of the objective function and the non-negativity of the parameters. The importance of the regularization alongside the Rician noise incorporation is shown both visually and numerically on a simulated phantom and on magnitude MRI images acquired on fruit samples.

A microdestructive method using dye-coated-probe to visualize capillary, diffusion and evaporation zones in porous materials

The vaporization plane, a narrow zone of subsurface evaporation often present in porous rocks, separates the region where water flows due to capillary forces from the dry zone where moisture moves in gas phase only. The knowledge of its depth and geometry is critical for estimating water flux in rock-atmosphere interphase, for understanding moisture distribution and for localization of damaging salt crystallization. Yet, an easy-to-use method applicable in the exterior has been missing. This strongly limits interpretation of moisture-related measurements as moisture content differences in the above-mentioned zones are often immeasurable by currently used field techniques. We have introduced a new micro-destructive method to measure the vaporization plane depth using an instrument consisting of a rod, adhesive, and dye powder, reacting with moisture, that is inserted into porous materials in 2 mm diameter holes. We tested different rods, adhesives, and dyes, and the best combination of these has been used in >500 experiments to determine the vaporization plane depth in porous rocks and building materials. The knowledge of vaporization plane depth enables more reliably to interpret the moisture and suction data obtained from numerous existing techniques. This new uranine-probe method should be thus of interest to many scientific disciplines: evaporation, unsaturated hydrology, weathering, or geobiology.

Self-Limited Accumulation of Colloids in Porous Media

We present local direct imaging of the progressive adsorption of colloidal particles inside a 3D model porous medium. By varying the interparticle electrostatic interactions, we observe a large range of particle deposition regimes, from a single layer of particles at the surface of the medium to multiple layers and eventually clogging of the system. We derive the complete deposition dynamics and show that colloid accumulation is a self-limited mechanism towards a deposited fraction associated with a balance between the particle interactions and the imposed flow rate. These trends are explained and predicted using a simple probability model considering the particle adsorption energy and the variation of the drag energy with evolving porosity. This constitutes a direct validation of speculated particle transport mechanisms, and a further understanding of accumulation mechanisms.

Particle-Size-Exclusion Clogging Regimes in Porous Media

From observations of the progressive deposition of noncolloidal particles by geometrical exclusion effects inside a 3D model porous medium, we get a complete dynamic view of particle deposits over a full range of regimes from transport over a long distance to clogging and caking. We show that clogging essentially occurs in the form of an accumulation of elements in pore size clusters, which ultimately constitute regions avoided by the flow. The clusters are dispersed in the medium, and their concentration (number per volume) decreases with the distance from the entrance; caking is associated with the final stage of this effect (for a critical cluster concentration at the entrance). A simple probabilistic model, taking into account the impact of clogging on particle transport, allows us to quantitatively predict all these trends up to a large cluster concentration, based on a single parameter: the clogging probability, which is a function of the confinement ratio. This opens the route towards a unification of the different fields of particle transport, clogging, caking, and filtration.

Novel Experimental-Modeling Approach for Characterizing Perfluorinated Surfactants in Soils

Soil contamination is still poorly understood and modeled in part because of the difficulties of looking inside the "black box" constituted by soils. Here, we investigated the application of a recently developed ¹H NMR technique to ¹⁹F NMR relaxometry experiments and utilized the results as inputs for an existing model. This novel approach yields ¹⁹F T₂ NMR relaxation values of any fluorinated contaminant, which are among the most dangerous contaminants, allowing us to noninvasively and directly monitor their fate in soils. Using this protocol, we quantified the amount of a fluorinated xenobiotic (heptafluorobutyric acid, HFBA) in three different environments in soil aggregate packings and monitored contaminant exchange dynamics between these compartments. A model computing HFBA partition dynamics between different soil compartments showed that these three environments corresponded to HFBA in solution (i) between and (ii) inside the soil aggregates and (iii) to HFBA adsorbed to (or strongly interacting with) the soil constituents. In addition to providing a straightforward way of determining the sorption kinetics of any fluorinated contaminant, this work also highlights the strengths of a combined experimental-modeling approach to unambiguously understand experimental data and more generally to study contaminant fate in soils.