Identification and analysis of 3D pores in packed particulate materials

We took the classic 'guess the number of beans in a jar game' and amplified the research question. Rather than estimate the quantity of particles in the jar, we sought to characterize the spaces between them. Here we present an approach for delineating the pockets of empty space (three-dimensional pores) between packed particles, which are hotspots for activity in applications and natural phenomena that deal with particulate materials. We utilize techniques from graph theory to exploit information about particle configuration that allows us to locate important spatial landmarks within the void space. These landmarks are the basis for our pore segmentation, where we consider both interior pores as well as entrance and exit pores into and out of the structure. Our method is robust for particles of varying size, form, stiffness and configuration, which allows us to study and compare three-dimensional pores across a range of packed particle types. We report striking relationships between particles and pores that are described mathematically, and we offer a visual library of pore types. With a meaningful discretization of void space, we demonstrate that packed particles can be understood not by their solid space, but by their empty space.

A data-driven framework for permeability prediction of natural porous rocks via microstructural characterization and pore-scale simulation

Understanding the microstructure-property relationships of porous media is of great practical significance, based on which macroscopic physical properties can be directly derived from measurable microstructural informatics. However, establishing reliable microstructure-property mappings in an explicit manner is difficult, due to the intricacy, stochasticity, and heterogeneity of porous microstructures. In this paper, a data-driven computational framework is presented to investigate the inherent microstructure-permeability linkage for natural porous rocks, where multiple techniques are integrated together, including microscopy imaging, stochastic reconstruction, microstructural characterization, pore-scale simulation, feature selection, and data-driven modeling. A large number of 3D digital rocks with a wide porosity range are acquired from microscopy imaging and stochastic reconstruction techniques. A broad variety of morphological descriptors are used to quantitatively characterize pore microstructures from different perspectives, and they compose the raw feature pool for feature selection. High-fidelity lattice Boltzmann simulations are conducted to resolve fluid flow passing through porous media, from which reliable permeability references are obtained. The optimal feature set that best represents permeability is identified through a performance-oriented feature selection process, upon which a cost-effective surrogate model is rapidly fitted to approximate the microstructure-permeability mapping via data-driven modeling. This surrogate model exhibits great advantages over empirical/analytical formulas in terms of prediction accuracy and generalization capacity, which can predict reliable permeability values spanning four orders of magnitude. Besides, feature selection also greatly enhances the interpretability of the data-driven prediction model, from which new insights into the mechanism of how microstructural characteristics determine intrinsic permeability are obtained.

Hydrodynamics induce superdiffusive jumps of passive tracers along critical paths of random networks and colloidal gels

We present a numerical study on the effect of hydrodynamic interactions (HI) on the diffusion of inert point tracer particles in several fixed random structures. As expected, the diffusion is hampered by the extra hydrodynamic friction introduced by the obstacle network. However, a non-trivial effect due to HI appears in the analysis of the van-Hove displacement probability close to the percolation threshold, where tracers diffuse through critical fractal paths. We show that the tracer dynamics can be split up into short and long jumps, the latter being ruled by either exponential or Gaussian van Hove distribution tails. While at short time HI slow down the tracer diffusion, at long times, hydrodynamic interactions with the obstacles increase the probability of longer jumps, which circumvent the traps of the labyrinth more easily. Notably, the relation between the anomalous diffusion exponent and the fractal dimension of the critical (intricate) paths is greater than one, which implies that the long-time (long-jump) diffusion is mildly superdiffuse. A possible reason for such a hastening of the diffusion along the network corridors is the hydrodynamically induced mobility anisotropy, which favours displacements parallel to the walls, an effect which has already been experimentally observed in collagen gels.

Correlating Ionic Conductivity and Microstructure in Polyelectrolyte Hydrogels for Bioelectronic Devices

Hydrogels have become the material of choice in bioelectronic devices because their high-water content leads to efficient ion transport and a conformal interface with biological tissue. While the morphology of hydrogels has been thoroughly studied, systematical studies on their ionic conductivity is less common. Here, we present an easy-to-implement strategy to characterize the ionic conductivity of a series of polyelectrolyte hydrogels with different amounts of monomer and crosslinker and correlate their ionic conductivity with microstructure. Higher monomer increases the ionic conductivity of the polyelectrolyte hydrogel due to the increased charge carrier density, but also leads to excessive swelling that may cause device failure upon integration with bioelectronic devices. Increasing the amount of crosslinker can reduce the swelling ratio by increasing the crosslinking density and reducing the mesh size of the hydrogel, which cuts down the ionic conductivity. Further investigation on the porosity and tortuosity of the swollen hydrogels correlates the microstructure with the ionic conductivity. These results are generalizable for various polyelectrolyte hydrogel systems with other ions as the charge carrier and provide a facile guidance to design polyelectrolyte hydrogel with desired ionic conductivity and microstructure for applications in bioelectronic devices. This article is protected by copyright. All rights reserved.

Combining State of the Art Opensource and Proprietary Machine Learning Technologies to Build a Data Analysis Pipeline for Gasoline Particulate Filters using X-ray Microscopy, Focused Ion Beam-Scanning Electron Microscopy and Transmission Electron Microscopy

The performance of a particulate filter is determined by multi-scale properties that span the macro, meso and atomic scale. Traditionally, the primary role of a GPF is to reduce solid particles and liquid droplets. At the macroscale, transport of gas through a filter’s channels and interconnecting pores act as main transport arteries for catalytically active sites. At the mesoscale, the micropore structure is important for ensuring that there are enough active sites that are accessible for the gas to reach the catalyst nanoparticles. Whereas at the atomic scale, the structure of the catalyst material determines the performance and selectivity within the filter. Understanding all length scales requires a correlative approach but this is often quite difficult to achieve due to the number of software packages a scientist has to deal with. We demonstrate how current state of the art approaches in the field can be combined into a streamlined pipeline to characterise particulate filters by digitally reconstructing the sample, analysing it at high throughput, and eventually used as an input for gas flow simulations and better product design.

Vitreous Carbon, Geometry and Topology: A Hollistic Approach

Glass-like carbon (GLC) is a complex structure with astonishing properties: isotropic sp2 structure, low density and chemical robustness. Despite the expanded efforts to understand the structure, it remains little known. We review the different models and a physical route (pulsed laser deposition) based on a well controlled annealing of the native 2D/3D amorphous films. The many models all have compromises: neither all bad nor entirely satisfactory. Properties are understood in a single framework given by topological and geometrical properties. To do this, we present the basic tools of topology and geometry at a ground level for 2D surface, graphene being the best candidate to do this. With this in mind, special attention is paid to the hyperbolic geometry giving birth to triply periodic minimal surfaces. Such surfaces are the basic tools to understand the GLC network architecture. Using two theorems (the classification and the uniformisation), most of the GLC properties can be tackled at least at a heuristic level. All the properties presented can be extended to 2D materials. It is hoped that some researchers may find it useful for their experiments.

Nanoscale Accessible Porosity as a Key Parameter Depicting the Topological Evolution of Organic Porous Networks

A significant part of the hydrocarbons contained in source rocks remains confined within the organic matter-called kerogen-from where they are generated. Understanding the sorption and transport properties of confined hydrocarbons within the kerogens is, therefore, paramount to predict production. Specifically, knowing the impact of thermal maturation on the evolution of the organic porous network is key. Here, we propose an experimental procedure to study the interplay between the chemical evolution and the structural properties of the organic porous network at the nanometer scale. First, the organic porous networks of source rock samples, covering a significant range of natural thermal maturation experienced by the Vaca Muerta formation (Neuquén Basin, Argentina), are physically reconstructed using bright-field electron tomography. Their structural description allows us to measure crucial parameters such as the porosity, specific pore volume and surface area, aperture and cavity size distributions, and constriction. In addition, a model-free computation of the topological properties (effective porosity, connectivity, and tortuosity) is conducted. Overall, we document a general increase of the specific pore volume with thermal maturation. This controls the topological features depicting increasing accessibility to alkane molecules, sensed by the evolution of the effective porosity. Collectively, our results highlight the input of bright-field electron tomography in the study of complex disordered amorphous porous media, especially to describe the interplay between the structural features and transport properties of confined fluids.

Retention loss of reversed-phase chromatographic columns using 100% aqueous mobile phases from fundamental insights to best practice

This work deals with experimental investigations pertaining to the impact of chemical (electrolyte concentration from 0 to 100 mM, dissolved nitrogen gas from 0 to 6.7  ×  10^-4 M in water; surface chemistry including hexylphenyl, polyphenyl, C₃₀, C₁₈, and C₈; surface coverage in C₁₈-bonded chains from 1.5 to 3.5 µmol/m²; presence of surface dopant), physical (hydrostatic pressure of water from 50 to 500 bar; temperature from 27 ^∘C to 75 ^∘C), and structural parameters (average pore size from 50 Å to 400 Å; pore connectivity) on the dewetting kinetics of water from the hydrophobic mesopores of particles packed in RPLC columns. The results are explained from physico-chemical viewpoints involving intrusion and extrusion Laplace pressures, advancing and receding contact angles, surface tension of water, vapor pressure of water, 3D reconstruction of the actual mesoporous structure, pore connectivity, and the hysteresis in nitrogen adsorption and desorption isotherm onto reversed-phase chromatographic materials. A model of water dewetting consistent with the observations and the physical interpretations is then proposed. Finally, the most relevant practical solutions (pressurizing the column in absence of flow, pore size enlargement, using phenyl-bonded phase, polar embedded or surface doped C₁₈-bonded phases, reducing the C₁₈ surface coverage, doping the silica surface, lengthening of the alkyl-bonded chains, applying low temperatures, purging and degassing the mobile phase with helium gas) are suggested in order to eliminate or at least minimize the retention loss of RPLC columns when using fully aqueous mobile phases.

Diffusive Escape of a Nanoparticle from a Porous Cavity

Narrow escape from confinement through a nanochannel is the critical step of complex transport processes including size-exclusion-based separations, oil and gas extraction from the microporous subsurface environment, and ribonucleic acid translocation through nuclear pore complex channels. While narrow escape has been studied using theoretical and computational methods, experimental quantification is rare because of the difficulty in confining a particle into a microscopic space through a nanoscale hole. Here, we studied narrow escape in the context of continuous nanoparticle diffusion within the liquid-filled void space of an ordered porous material. Specifically, we quantified the spatial dependence of nanoparticle motion and the sojourn times of individual particles in the interconnected confined cavities of a liquid-filled inverse opal film. We found that nanoparticle motion was inhibited near cavity walls and cavity escape was slower than predicted by existing theories and random-walk simulations. A combined computational-experimental analysis indicated that translocation through a nanochannel is barrier controlled rather than diffusion controlled.

Gamma-irradiation-induced micro-structural variations in flame-retardant polyurethane foam using synchrotron X-ray micro-tomography

Flame-retardant polyurethane foams are potential packing materials for the transport casks of highly active nuclear materials for shock absorption and insulation purposes. Exposure of high doses of gamma radiation causes cross-linking and chain sectioning of macromolecules in this polymer foam, which leads to reorganization of their cellular microstructure and thereby variations in physico-mechanical properties. In this study, in-house-developed flame-retardant rigid polyurethane foam samples were exposed to gamma irradiation doses in the 0-20 kGy range and synchrotron radiation X-ray micro-computed tomography (SR-µCT) imaging was employed for the analysis of radiation-induced morphological variations in their cellular microstructure. Qualitative and quantitative analysis of SR-µCT images has revealed significant variations in the average cell size, shape, wall thickness, orientations and spatial anisotropy of the cellular microstructure in polyurethane foam.

Advanced Laguerre Tessellation for the Reconstruction of Ceramic Foams and Prediction of Transport Properties

Ceramic foams are promising, highly porous materials, with a wide range of specific surface area and low fluid flow resistance, which are well-suited for filtering applications. They are comprised mainly of macrovoids that are interconnected with struts. A branch-shaped reconstruction algorithm is introduced in the present work to reconstruct various ceramic foams from electron microscopy images using the Laguerre tessellation method. Subsequently, the reconstructed samples are used for the numerical calculation of pore structure and transport properties, including specific surface area, tortuosity, effective diffusivity, and flow permeability. Following comparison with experimental data, this reconstruction method is shown to be more reliable than typical analytical expressions that are suggested in the literature for the aforementioned structural and transport properties. Extracting the equivalent pore radius of the reconstructed domains offers improved accuracy of the analytical expressions for the permeability estimation.

Microstructure degradation of Ni/CGO anodes for solid oxide fuel cells after long operation time using 3D reconstructions by FIB tomography

The 3D reconstructions of SOFC anode microstructure aged up to 20 000 h under realistic conditions was carried out with FIB/SEM tomography in order to calculate the microstructure key parameters.

On the underestimated impact of the gelation temperature on macro- and mesoporosity in monolithic silica

Elucidating pore formation in monolithic SiO₂: small variations in gelation temperature have a surprisingly strong impact on the meso- and macroporosity.

High-performance monoliths in heterogeneous catalysis with single-phase liquid flow

On-line control and monitoring in heterogeneous catalysis utilizing high-performance supports allows rapid screening of intrinsic reaction parameters in continuous-flow mode.