Off-lattice reconstruction of porous media: critical evaluation, geometrical confinement and molecular transport

Dynamic NMR Relaxometry as a Simple Tool for Measuring Liquid Transfers and Characterizing Surface and Structure Evolution in Porous Media

Porous media containing voids which can be filled with gas and/or liquids are ubiquitous in our everyday life: soils, wood, bricks, concrete, sponges, and textiles. It is of major interest to identify how a liquid, pushing another fluid or transporting particles, ions, or nutriments, can penetrate or be extracted from the porous medium. High-resolution X-ray microtomography, neutron imaging, and magnetic resonance imaging are techniques allowing us to obtain, in a nondestructive way, a view of the internal processes in nontransparent porous media. Here we review the possibilities of a simple though powerful technique which provides various direct quantitative information on the liquid distribution inside the porous structure and its variations over time due to fluid transport and/or phase changes. It relies on the analysis of the details of the NMR (nuclear magnetic resonance) relaxation of the proton spins of the liquid molecules and its evolution during some process such as the imbibition, drying, or phase change of the sample. This rather cheap technique then allows us to distinguish how the liquid is distributed in the different pore sizes or pore types and how this evolves over time; since the NMR relaxation time depends on the fraction of time spent by the molecule along the solid surface, this technique can also be used to determine the specific surface of some pore classes in the material. The principles of the technique and its contribution to the physical understanding of the processes are illustrated through examples: imbibition, drying or fluid transfers in a nanoporous silica glass, large pores dispersed in a fine polymeric porous matrix, a pile of cellulose fibers partially saturated with bound water, a softwood, and a simple porous inclusion in a cement paste. We thus show the efficiency of the technique to quantify the transfers with a good temporal resolution.

Nostoc muscorum is a novel source of microalgal lectins with potent antiviral activity against herpes simplex type-1

In our survey for a new antiviral agent, two types of lectin were purified from Nostoc muscorum using both ion-exchange and affinity columns chromatography. Nostoc muscorum lectins (NMLs) are categorized based on their carbohydrate preference. Nostoc muscorum lectin-1(NML-1) exhibited a strict binding specificity for complex glycoproteins without linked carbohydrates, and the other displayed specificity for α- glycosides mannose polymers (NML-2) and was classified as a glycoprotein with 16.8% linked carbohydrates. NML-1 displayed a single band of 166 kDa on native-PAGE and two bands of 81 kDa and 85 kDa on SDS-PAGE, which confirmed the heterodimeric nature of this lectin. While NML-2 is a 50 kDa glycoprotein composed of 25 kDa subunits. Physical characterization of NML-1 displayed its stability at a higher temperature of 90 °C for 5 min and over a wide pH range (4-9), while MNL-2 displayed stability up to a temperature of 80 °C for 25 min and a pH range of 5-8. NML-1 didn't require metal ions for agglutination activity, while the activity of NML-2 was doubled by manganese ions. The antiviral activity of two lectins was assessed against herpes simplex type-1 (HSV-1) using a plaque assay which revealed that NML-1 inhibited HSV-1 infection at an early stage in contrast to NML-2 which exerted its antiviral effect at the late stage of infection. These results suggest that Nostoc muscorum is a unique lead for antiviral drug discovery as it is a novel source for antiviral lectins with different modes of action.

Experimental Investigation on Post-Peak Permeability Evolution Law of Saturated Sandstone under Various Cyclic Loading–Unloading and Confining Pressure

The permeability evolution law of saturated rock under cyclic loading–unloading after shear yield is an important basis for revealing the water resistance performance and water inrush risk of overlying rock under multiple mining conditions. In this paper, the influence of the confining pressure, the cyclic loading–unloading times (CLT), and the volumetric strain on the post-peak permeability of saturated sandstone was studied by carrying out a post-peak permeability experiment. Based on SEM images and an improved simulated annealing algorithm, the 3D internal structure characteristics of sandstone samples before and after the experiment were reconstructed. The influences of the confining pressure on pore diameter, effective porosity, connectivity, seepage path length, and tortuosity of the sandstone before and after the experiment are discussed. Research results indicated that (1) In the post-peak cyclic loading–unloading stage, the volumetric strain is negatively correlated with permeability. At the unloading and initial loading stage, the volumetric strain showed a gradually decreasing trend as the specimen was slowly compressed. However, at the middle and final loading stages, the volumetric strain curve shifted to the left and showed a decreasing trend, resulting in an obvious increase in permeability. (2) The influence of CLT on k is closely related to the confining pressure level. When the confining pressure changed from 4 MPa to 12 MPa, the volumetric strain–average stress hysteretic curve shifted to the left in turn and the corresponding permeability gradually increased. When the confining pressure increased to 16 MPa and 20 MPa, the volumetric strain–average stress hysteretic curve shifted to the right in turn and the corresponding permeability showed a decreasing trend. No matter what the value of CLT, the magnitude of sandstone permeability gradually decreased and the decreasing trend became flat as the confining pressure increased, especially for σ3 = 16 MPa and 20 MPa. (3) No matter what value of the confining pressure, the hysteresis area of the first cycle was larger than that of last three cycles, indicating that the plastic deformation generated in the first cycle was larger than that generated in the last three cycles and the recovery rate of the permeability increased with an increase of CLT. (4) As the confining pressure gradually increased, the pore diameter, effective porosity, and connectivity all approximately showed a linear decrease due to more easily compacted pores and cracks under high confining pressure, lower connectivity, and permeability, while the length and tortuosity of the seepage path increased nonlinearly, roughly due to a more significant shear failure phenomenon where the seepage path became more tortuous, that is, the greater the tortuosity, the longer the seepage path. The research results can provide an important theoretical basis for water resistance performance and water inrush risk assessment of overlying aquifer under the influence of mining stress.

Inelastic neutron scattering analysis with time-dependent Gaussian-field models

Converting neutron scattering data to real-space time-dependent structures can only be achieved through suitable models, which is particularly challenging for geometrically disordered structures. We address this problem by introducing time-dependent clipped Gaussian field models. General expressions are derived for all space- and time-correlation functions relevant to coherent inelastic neutron scattering for multiphase systems and arbitrary scattering contrasts. Various dynamic models are introduced that enable one to add time-dependence to any given spatial statistics, as captured, e.g., by small-angle scattering. In a first approach, the Gaussian field is decomposed into localized waves that are allowed to fluctuate in time or to move either ballistically or diffusively. In a second approach, a dispersion relation is used to make the spectral components of the field time-dependent. The various models lead to qualitatively different dynamics, which can be discriminated by neutron scattering. The methods of this paper are illustrated with oil/water microemulsion studied by small-angle scattering and neutron spin-echo. All available data-in both film and bulk contrasts, over the entire range of q and τ-are analyzed jointly with a single model. The analysis points to the static large-scale structure of the oil and water domains while the interfaces are subject to thermal fluctuations. The fluctuations have an amplitude of around 60 Å and contribute to 30% of the total interface area.

Impact of Geometrical Disorder on Phase Equilibria of Fluids and Solids Confined in Mesoporous Materials

Porous solids used in practical applications often possess structural disorder over broad length scales. This disorder strongly affects different properties of the substances confined in their pore spaces. Quantifying structural disorder and correlating it with the physical properties of confined matter is thus a necessary step toward the rational use of porous solids in practical applications and process optimization. The present work focuses on recent advances made in the understanding of correlations between the phase state and geometric disorder in nanoporous solids. We overview the recently developed statistical theory for phase transitions in a minimalistic model of disordered pore networks: linear chains of pores with statistical disorder. By correlating its predictions with various experimental observations, we show that this model gives notable insight into collective phenomena in phase-transition processes in disordered materials and is capable of explaining self-consistently the majority of the experimental results obtained for gas-liquid and solid-liquid equilibria in mesoporous solids. The potentials of the theory for improving the gas sorption and thermoporometry characterization of porous materials are discussed.

A Multi-Scale Study of Water Dynamics under Confinement, Exploiting Numerical Simulations in Relation to NMR Relaxometry, PGSE and NMR Micro-Imaging Experiments: An Application to the Clay/Water Interface

Water mobility within the porous network of dense clay sediments was investigated over a broad dynamical range by using 2H nuclear magnetic resonance spectroscopy. Multi-quanta 2H NMR spectroscopy and relaxation measurements were first performed to identify the contributions of the various relaxation mechanisms monitoring the time evolution of the nuclear magnetisation of the confined heavy water. Secondly, multi-quanta spin-locking NMR relaxation measurements were then performed over a broad frequency domain, probing the mobility of the confined water molecules on a time-scale varying between microseconds and milliseconds. Thirdly, 1H NMR pulsed-gradient spin-echo attenuation experiments were performed to quantify water mobility on a time-scale limited by the NMR transverse relaxation time of the confined NMR probe, typically a few milliseconds. Fourthly, the long living quantum state of the magnetisation of quadrupolar nuclei was exploited to probe a two-time correlation function at a time-scale reaching one second. Finally, magnetic resonance imaging measurements allow probing the same dynamical process on time-scales varying between seconds and several hours. In that context, multi-scale modelling is required to interpret these NMR measurements and extract information on the influences of the structural properties of the porous network on the apparent mobility of the diffusing water molecules. That dual experimental and numerical approach appears generalizable to a large variety of porous networks, including zeolites, micelles and synthetic or biological membranes.

Stochastic models of dense or hollow nanoparticles and their scattering properties

A family of stochastic models of disordered particles is proposed, obtained by clipping a Gaussian random field with a function that is space dependent. Depending on the shape of the clipping function, dense or hollow particles can be modelled. General expressions are derived for the form factor of the particles, for their average volume and surface area, and for their density and surface-area distributions against the distance to the particle centre. A general approximation for the form factor is also introduced, based on the density and surface-area distributions, which coincides with the Guinier and Porod expressions in the limits of low and high scattering vector magnitude q. The models are illustrated with the fitting of small-angle X-ray scattering (SAXS) data measured on Pt/Ni hollow nanoparticles. The SAXS analysis and modelling notably capture the collapse of the particles' porosity after being used as oxygen-reduction catalysts.

Quantifying accuracy of stochastic methods of reconstructing complex materials by deep learning

Time and cost are two main hurdles to acquiring a large number of digital image I of the microstructure of materials. Thus, use of stochastic methods for producing plausible realizations of materials' morphology based on one or very few images has become an increasingly common practice in their modeling. The accuracy of the realizations is often evaluated using two-point microstructural descriptors or physics-based modeling of certain phenomena in the materials, such as transport processes or fluid flow. In many cases, however, two-point correlation functions do not provide accurate evaluation of the realizations, as they are usually unable to distinguish between high- and low-quality reconstructed models. Calculating flow and transport properties of the realization is an accurate way of checking the quality of the realizations, but it is computationally expensive. In this paper a method based on machine learning is proposed for evaluating stochastic approaches for reconstruction of materials, which is applicable to any of such methods. The method reduces the dimensionality of the realizations using an unsupervised deep-learning algorithm by compressing images and realizations of materials. Two criteria for evaluating the accuracy of a reconstruction algorithm are then introduced. One, referred to as the internal uncertainty space, is based on the recognition that for a reconstruction method to be effective, the differences between the realizations that it produces must be reasonably wide, so that they faithfully represent all the possible spatial variations in the materials' microstructure. The second criterion recognizes that the realizations must be close to the original I and, thus, it quantifies the similarity based on an external uncertainty space. Finally, the ratio of two uncertainty indices associated with the two criteria is considered as the final score of the accuracy of a stochastic algorithm, which provides a quantitative basis for comparing various realizations and the approaches that produce them. The proposed method is tested with images of three types of heterogeneous materials in order to evaluate four stochastic reconstruction algorithms.

Coarsening Kinetics of Complex Macromolecular Architectures in Bad Solvent

This study reports a general scenario for the out-of-equilibrium features of collapsing polymeric architectures. We use molecular dynamics simulations to characterize the coarsening kinetics, in bad solvent, for several macromolecular systems with an increasing degree of structural complexity. In particular, we focus on: flexible and semiflexible polymer chains, star polymers with 3 and 12 arms, and microgels with both ordered and disordered networks. Starting from a powerful analogy with critical phenomena, we construct a density field representation that removes fast fluctuations and provides a consistent characterization of the domain growth. Our results indicate that the coarsening kinetics presents a scaling behaviour that is independent of the solvent quality parameter, in analogy to the time-temperature superposition principle. Interestingly, the domain growth in time follows a power-law behaviour that is approximately independent of the architecture for all the flexible systems; while it is steeper for the semiflexible chains. Nevertheless, the fractal nature of the dense regions emerging during the collapse exhibits the same scaling behaviour for all the macromolecules. This suggests that the faster growing length scale in the semiflexible chains originates just from a faster mass diffusion along the chain contour, induced by the local stiffness. The decay of the dynamic correlations displays scaling behavior with the growing length scale of the system, which is a characteristic signature in coarsening phenomena.

Small-angle scattering by supported nanoparticles: exact results and useful approximations

In functional materials, nanoparticles are often dispersed in a porous support for the purpose of stabilizing them. This makes their characterization by small-angle scattering challenging because the signal comprises contributions from the nanoparticles of interest, from the inert support and from their cross-correlation. Exact analytical expressions for all three contributions are derived in the case of a Gaussian-field model of the porous support, with nanoparticles randomly distributed over the surface. For low nanoparticle loading, the expressions simplify to the addition of properly scaled support and particle scattering. For higher loadings, however, the cross-correlation cannot be ignored. Two approximations are introduced, which capture correlation effects in cases where the pores of the support are much larger or only slightly larger than the nanoparticles. The methods of the paper are illustrated with the small-angle X-ray scattering analysis of hollow metallic nanoparticles supported on porous carbon.

Computational investigation of microgels: synthesis and effect of the microstructure on the deswelling behavior

We present computer simulations of a realistic model of microgels. Unlike the regular network frameworks usually assumed in the simulation literature, we model and simulate a realistic and efficient synthesis route, mimicking cross-linking of functionalized chains inside a cavity. This model is inspired, e.g., by microfluidic fabrication of microgels from macromolecular precursors and is different from standard polymerization routes. The assembly of the chains is mediated by a low fraction of interchain crosslinks. The microgels are polydisperse in size and shape but globally spherical objects. In order to deeply understand the microgel structure and eventually improve the synthesis protocol we characterize their conformational properties and deswelling kinetics, and compare them with the results found for microgels obtained via underlying regular (diamond-like) structures. For the same molecular weight, monomer concentration and effective degree of cross-linking, the specific microstructure of the microgel has no significant effect on the locus of the volume phase transition (VPT). However, it strongly affects the deswelling kinetics, as revealed by a consistent analysis of the domain growth during the microgel collapse. Though both the disordered and the regular networks exhibit a similar early growth of the domains, an acceleration is observed in the regular network at the late stage of the collapse. Similar trends are found for the dynamic correlations coupled to the domain growth. As a consequence, the fast late processes for the domain growth and the dynamic correlations in the regular network are compensated, and the dynamic correlations follow a power-law dependence on the growing length scale that is independent of the microgel microstructure.

Stochastic analysis of capillary condensation in disordered mesopores

Most mesoporous materials of practical interest are inherently disordered, which has a significant impact on the condensation and evaporation of vapours in their pores. Traditionally, the effect of disorder is theoretically analyzed in a perturbative approach whereby slight elements of disorder (constriction, corrugation) are added to geometrically ideal pores. We propose an alternative approach, which consists of using a stochastic geometrical model to describe both the porous material and the condensate within the pores. This is done through a multiphase generalisation of the standard Gaussian random field model of disordered materials. The model parameters characterising the condensate provide a low-dimensional approximation of its configuration space, and we use a Derjaguin-Broekhoff-de Boer approximation to calculate the free-energy landscape. Our analysis notably questions the existence of vapour-like metastable states in realistically disordered mesoporous materials. Beyond capillary condensation, our general methodology is applicable to a broad array of confined phenomena.

Effect of capillary condensation on gas transport properties in porous media

We investigate the effect of capillary condensation on gas diffusivity in porous media composed of randomly packed spheres with moderate wettability. To simulate capillary phenomena at the pore scale while retaining complex pore networks of the porous media, we employ density functional theory (DFT) for coarse-grained lattice gas models. The lattice DFT simulations reveal that capillary condensations preferentially occur at confined pores surrounded by solid walls, leading to the occlusion of narrow pores. Consequently, the characteristic lengths of the partially wet structures are larger than those of the corresponding dry structures with the same porosities. Subsequent gas diffusion simulations exploiting the mean-square displacement method indicate that while the effective diffusion coefficients significantly decrease in the presence of partially condensed liquids, they are larger than those in the dry structures with the same porosities. Moreover, we find that the ratio of the porosity to the tortuosity factor, which is a crucial parameter that determines an effective diffusion coefficient, can be reasonably related to the porosity even for the partially wet porous media.

Mapping the Functional Tortuosity and Spatiotemporal Heterogeneity of Porous Polymer Membranes with Super-Resolution Nanoparticle Tracking

As particles flow through porous media, they follow complex pathways and experience heterogeneous environments that are challenging to characterize. Tortuosity is often used as a parameter to characterize the complexity of pathways in porous materials and is useful in understanding hindered mass transport in industrial filtration and mass separation processes. However, conventional calculations of tortuosity provide only average values under static conditions; they are insensitive to the intrinsic heterogeneity of porous media and do not account for potential effects of operating conditions. Here, we employ a high-throughput nanoparticle tracking method which enables the observation of actual particle trajectories in polymer membranes under relevant operating conditions. Our results indicate that tortuosity is not simply a structural material property but is instead a functional property that depends on flow rate and particle size. We also resolved the spatiotemporal heterogeneity of flowing particles in these porous media. The distributions of tortuosity and of local residence/retention times were surprisingly broad, exhibiting heavy tails representing a population of highly tortuous trajectories and local regions with anomalously long residence times. Interestingly, local tortuosity and residence times were directly correlated, suggesting the presence of highly confining regions that cause more meandering trajectories and longer retention times. The comprehensive information about tortuosity and spatiotemporal heterogeneity provided by these methods will advance the understanding of complex mass transport and assist rational design and synthesis of porous materials.

Optically transparent dense colloidal gels

Traditionally it has been difficult to study the porous structure of dense colloidal gels and (macro) molecular transport through them simply because of the difference in refractive index between the colloid material and the continuous fluid phase surrounding it, rendering the samples opaque even at low colloidal volume fractions. Here, we demonstrate a novel colloidal gel that can be refractive index-matched in aqueous solutions owing to the low refractive index of fluorinated latex (FL)-particles (n = 1.37). Synthesizing them from heptafluorobutyl methacrylate using emulsion polymerization, we demonstrate that they can be functionalized with short DNA sequences via a dense brush-layer of polystyrene-b-poly(ethylene oxide) block-copolymers (PS-PEO). The block-copolymer, holding an azide group at the free PEO end, was grafted to the latex particle utilizing a swelling-deswelling method. Subsequently, DNA was covalently attached to the azide-end of the block copolymer via a strain-promoted alkyne-azide click reaction. For comparison, we present a structural study of single gels made of FL-particles only and composite gels made of a percolating FL-colloid gel coated with polystyrene (PS) colloids. Further we demonstrate that the diffusivity of tracer colloids dispersed deep inside a refractive index matched FL-colloidal gel can be measured as function of the local confinement using Dynamic Differential Microscopy (DDM).

A carbon nanopore model to quantify structure and kinetics of ion electrosorption with in situ small-angle X-ray scattering

In situ small-angle X-ray scattering was carried out on a custom-built supercapacitor cell and is presented together with a novel data analysis strategy to study the structure and kinetics of ion electrosorption in a nanoporous carbon electrode.

Review of pore network modelling of porous media: Experimental characterisations, network constructions and applications to reactive transport

Pore network models have been applied widely for simulating a variety of different physical and chemical processes, including phase exchange, non-Newtonian displacement, non-Darcy flow, reactive transport and thermodynamically consistent oil layers. The realism of such modelling, i.e. the credibility of their predictions, depends to a large extent on the quality of the correspondence between the pore space of a given medium and the pore network constructed as its representation. The main experimental techniques for pore space characterisation, including direct imaging, mercury intrusion porosimetry and gas adsorption, are firstly summarised. A review of the main pore network construction techniques is then presented. Particular focus is given on how such constructions are adapted to the data from experimentally characterised pore systems. Current applications of pore network models are considered, with special emphasis on the effects of adsorption, dissolution and precipitation, as well as biomass growth, on transport coefficients. Pore network models are found to be a valuable tool for understanding and predicting meso-scale phenomena, linking single pore processes, where other techniques are more accurate, and the homogenised continuum porous media, used by engineering community.

Small-angle scattering and scale-dependent heterogeneity

Although small-angle scattering is often discussed qualitatively in terms of material heterogeneity, when it comes to quantitative data analysis this notion becomes somehow hidden behind the concept of correlation function. In the present contribution, a quantitative measure of heterogeneity is defined, it is shown how it can be calculated from scattering data, and its structural significance for the purpose of material characterization is discussed. Conceptually, the procedure consists of using a finite probe volume to define a local average density at any point of the material; the heterogeneity is then quantitatively defined as the fluctuations of the local average density when the probe volume is moved systematically through the sample. Experimentally, it is shown that the so-defined heterogeneity can be estimated by projecting the small-angle scattering intensity onto the form factor of the chosen probe volume. Choosing probe volumes of various sizes and shapes enables one to comprehensively characterize the heterogeneity of a material over all its relevant length scales. General results are derived for asymptotically small and large probes in relation to the material surface area and integral range. It is also shown that the correlation function is equivalent to a heterogeneity calculated with a probe volume consisting of two points only. The interest of scale-dependent heterogeneity for practical data analysis is illustrated with experimental small-angle X-ray scattering patterns measured on a micro- and mesoporous material, on a gel, and on a semi-crystalline polyethylene sample. Using different types of probes to analyse a given scattering pattern enables one to focus on different structural characteristics of the material, which is particularly useful in the case of hierarchical structures.

Designing disordered materials using DNA-coated colloids of bacteriophage fd and gold

DNA has emerged as an exciting binding agent for programmable colloidal self-assembly. Its popularity derives from its unique properties: it provides highly specific short-ranged interactions and at the same time it acts as a steric stabilizer against non-specific van der Waals and Coulomb interactions. Because complementary DNA strands are linked only via hydrogen bonds, DNA-mediated binding is thermally reversible: it provides an effective attraction that can be switched off by raising the temperature only by a few degrees. In this article we introduce a new binary system made of DNA-functionalized filamentous fd viruses of ∼880 nm length with an aspect ratio of ∼100, and 50 nm gold nanoparticles (gold NPs) coated with the complementary DNA strands. When quenching mixtures below the melt temperature Tm, at which the attraction is switched on, we observe aggregation. Conversely, above Tm the system melts into a homogenous particulate 'gas'. We present the aggregation behavior of three different gold NP to virus ratios and compare them to a gel made solely of gold NPs. In particular, we have investigated the aggregate structures as a function of cooling rate and determine how they evolve as function of time for given quench depths, employing fluorescence microscopy. Structural information was extracted in the form of an effective structure factor and chord length distributions. Rapid cooling rates lead to open aggregates, while slower controlled cooling rates closer to equilibrium DNA hybridization lead to more fine-stranded gels. Despite the different structures we find that for both cooling rates the quench into the two-phase region leads to initial spinodal decomposition, which becomes arrested. Surprisingly, although the fine-stranded gel is disordered, the overall structure and the corresponding length scale distributions in the system are remarkably reproducible. Such highly porous systems can be developed into new functional materials.

Mesoscale texture of cement hydrates

Strength and other mechanical properties of cement and concrete rely upon the formation of calcium-silicate-hydrates (C-S-H) during cement hydration. Controlling structure and properties of the C-S-H phase is a challenge, due to the complexity of this hydration product and of the mechanisms that drive its precipitation from the ionic solution upon dissolution of cement grains in water. Departing from traditional models mostly focused on length scales above the micrometer, recent research addressed the molecular structure of C-S-H. However, small-angle neutron scattering, electron-microscopy imaging, and nanoindentation experiments suggest that its mesoscale organization, extending over hundreds of nanometers, may be more important. Here we unveil the C-S-H mesoscale texture, a crucial step to connect the fundamental scales to the macroscale of engineering properties. We use simulations that combine information of the nanoscale building units of C-S-H and their effective interactions, obtained from atomistic simulations and experiments, into a statistical physics framework for aggregating nanoparticles. We compute small-angle scattering intensities, pore size distributions, specific surface area, local densities, indentation modulus, and hardness of the material, providing quantitative understanding of different experimental investigations. Our results provide insight into how the heterogeneities developed during the early stages of hydration persist in the structure of C-S-H and impact the mechanical performance of the hardened cement paste. Unraveling such links in cement hydrates can be groundbreaking and controlling them can be the key to smarter mix designs of cementitious materials.

Intermittent dynamics and logarithmic domain growth during the spinodal decomposition of a glass-forming liquid

We use large-scale molecular dynamics simulations of a simple glass-forming system to investigate how its liquid-gas phase separation kinetics depends on temperature. A shallow quench leads to a fully demixed liquid-gas system whereas a deep quench makes the dense phase undergo a glass transition and become an amorphous solid. This glass has a gel-like bicontinuous structure that evolves very slowly with time and becomes fully arrested in the limit where thermal fluctuations become negligible. We show that the phase separation kinetics changes qualitatively with temperature, the microscopic dynamics evolving from a surface tension-driven diffusive motion at high temperature to a strongly intermittent, heterogeneous, and thermally activated dynamics at low temperature, with a logarithmically slow growth of the typical domain size. These results elucidate the microscopic mechanisms underlying a specific class of viscoelastic phase separation.

Effect of surface texture on freezing in nanopores: surface-induced versus homogeneous crystallization

Freezing of argon in ordered and disordered carbon pores of a similar diameter D ∼ 2.4 nm is investigated using extensive molecular simulations with large system sizes up to 10(4) atoms. While crystallization in the atomistically smooth pore consists in a surface-induced phase transition occurring at a temperature larger than the bulk, crystallization in the disordered pores, which is only partial as it is spatially restricted to the pore center, occurs through homogeneous crystallization. These results shed light on solidification in pores by showing that there is a crossover between surface-induced and homogeneous crystallization upon increasing the surface disorder of the host material. In the latter case, the Gibbs-Thomson equation, in which crystallization is assumed to occur when the crystal size equals the pore size corrected for the thickness of the unfreezable layer at the pore surface, is in reasonable agreement with the observed freezing temperature.

Stochastic reconstruction using multiple correlation functions with different-phase-neighbor-based pixel selection

A reconstruction methodology based on threshold energy based energy minimization (TA) and different-phase-neighbor (DPN)-based pixel swapping is presented. The TA method uses an energy threshold rather than probabilities as an acceptance criteria for annealing steps. The DPN-based pixel selection method gives priority to pixels which are segregated from clusters instead of random selection. An in-house solver has been developed to obtain two-dimensional reconstructions of heterogeneous two-phase mediums. Compared to conventional simulated annealing with random pixel swapping, the proposed method was found to achieve an optimal structure with up to an order of magnitude reduction in energy. When selecting a threshold tolerance value, the proposed method showed a 50% improvement in convergence time compared to conventional simulated annealing with random pixel swapping. The improved algorithm is used to study the effect of multiple correlation functions during the reconstruction. It was found that a combination of two-point correlation function and lineal path function for both phases results in most accurate reconstructions.

Aggregation dynamics, structure, and mechanical properties of bigels

Recently we have introduced bigels, inter-penetrating gels made of two different colloidal species. Even if particles with simple short-range isotropic potential are employed, the selective interactions enable the tunability of the self-assembly, leading to the formation of complex structures. In the present paper, we explore the non-equilibrium dynamics and the phenomenology underlying the kinetic arrest under quench and the formation of bigels. We demonstrate that the peculiar bigel kinetics can be described through an arrested spinodal decomposition driven by demixing of the colloidal species. The role played by the presence of a second colloidal species on the phase diagram, as expanded to account for the increased number of parameters, is clarified both via extensive numerical simulations and experiments. We provide details on the realisation of bigels, by means of DNA-coated colloids (DNACCs), and the consequent imaging techniques. Moreover we evidence, by comparison with the usual one-component gel formation, the emergence of controllable timescales in the aggregation of the bigels, whose final stages are also experimentally studied to provide morphological details. Finally, we use numerical models to simulate the bigel response to mechanical strain, highlighting how such a new material can bear significantly higher stress compared to the usual one-component gel. We conclude by discussing possible technological uses and by providing insights on the viable research steps to undertake for more complex and yet tuneable multi-component colloidal systems.

Efficient 3D porous microstructure reconstruction via Gaussian random field and hybrid optimization

Obtaining an accurate three-dimensional (3D) structure of a porous microstructure is important for assessing the material properties based on finite element analysis. Whereas directly obtaining 3D images of the microstructure is impractical under many circumstances, two sets of methods have been developed in literature to generate (reconstruct) 3D microstructure from its 2D images: one characterizes the microstructure based on certain statistical descriptors, typically two-point correlation function and cluster correlation function, and then performs an optimization process to build a 3D structure that matches those statistical descriptors; the other method models the microstructure using stochastic models like a Gaussian random field and generates a 3D structure directly from the function. The former obtains a relatively accurate 3D microstructure, but computationally the optimization process can be very intensive, especially for problems with large image size; the latter generates a 3D microstructure quickly but sacrifices the accuracy due to issues in numerical implementations. A hybrid optimization approach of modelling the 3D porous microstructure of random isotropic two-phase materials is proposed in this paper, which combines the two sets of methods and hence maintains the accuracy of the correlation-based method with improved efficiency. The proposed technique is verified for 3D reconstructions based on silica polymer composite images with different volume fractions. A comparison of the reconstructed microstructures and the optimization histories for both the original correlation-based method and our hybrid approach demonstrates the improved efficiency of the approach.

Three-dimensional reconstruction of liquid phases in disordered mesopores usingin situsmall-angle scattering

Small-angle scattering of X-rays (SAXS) or neutrons is one of the few experimental methods currently available for thein situanalysis of phenomena in mesoporous materials at the mesoscopic scale. In the case of disordered mesoporous materials, however, the main difficulty of the method lies in the data analysis. A stochastic model is presented, which enables one to reconstruct the three-dimensional nanostructure of liquids confined in disordered mesopores starting from small-angle scattering data. This so-called plurigaussian model is a multi-phase generalization of clipped Gaussian random field models. Its potential is illustrated through the synchrotron SAXS analysis of a gel permeated with a critical nitrobenzene/hexane solution that is progressively cooled below its consolute temperature. The reconstruction brings to light a wetting transition whereby the nanostructure of the pore-filling liquids passes from wetting layers that uniformly cover the solid phase of the gel to plugs that locally occlude the pores. Using the plurigaussian model, the dewetting phenomenon is analyzed quantitatively at the nanometre scale in terms of changing specific interface areas, contact angle and specific length of the triple line.

Wanted: a positive control for anomalous subdiffusion

Anomalous subdiffusion in cells and model systems is an active area of research. The main questions are whether diffusion is anomalous or normal, and if it is anomalous, its mechanism. The subject is controversial, especially the hypothesis that crowding causes anomalous subdiffusion. Anomalous subdiffusion measurements would be strengthened by an experimental standard, particularly one able to cross-calibrate the different types of measurements. Criteria for a calibration standard are proposed. First, diffusion must be anomalous over the length and timescales of the different measurements. The length-scale is fundamental; the time scale can be adjusted through the viscosity of the medium. Second, the standard must be theoretically well understood, with a known anomalous subdiffusion exponent, ideally readily tunable. Third, the standard must be simple, reproducible, and independently characterizable (by, for example, electron microscopy for nanostructures). Candidate experimental standards are evaluated, including obstructed lipid bilayers; aqueous systems obstructed by nanopillars; a continuum percolation system in which a prescribed fraction of randomly chosen obstacles in a regular array is ablated; single-file diffusion in pores; transient anomalous subdiffusion due to binding of particles in arrays such as transcription factors in randomized DNA arrays; and computer-generated physical trajectories.

Atomistic model of micelle-templated mesoporous silicas: structural, morphological, and adsorption properties

The structural, morphological, and adsorption properties of MCM-41 porous silicas are investigated using a realistic numerical model obtained by means of ab initio calculations [Ugliengo, P.; et al. Adv. Mater.2008, 20, 1]. Simulated X-ray diffraction, small angle neutron scattering, and electronic microscopy for the atomistic model are in good agreement with experimental data. The morphological features are also assessed from chord length distributions and porous volume and specific geometrical surface calculations, etc. The N(2), CO(2), and H(2)O adsorption isotherms in the atomistic model of MCM-41 are also in reasonable agreement with their experimental counterpart. An important finding of the present work is that water forms a film adsorbed on specific hydrophilic regions of the surface while the rest of the surface is depleted in water molecules. This result suggests that the surface of MCM-41 materials is heterogeneous, as it is made up of both hydrophilic and hydrophobic patches. While adsorption and irreversible capillary condensation can be described using the thermodynamical approach by Derjaguin (also known as the Derjaguin-Broekhoff-De Boer model), the Freundlich equation fits nicely the data for reversible and continuous filling in small pores.

Reconstruction of three-dimensional porous media using a single thin section

The purpose of any reconstruction method is to generate realizations of two- or multiphase disordered media that honor limited data for them, with the hope that the realizations provide accurate predictions for those properties of the media for which there are no data available, or their measurement is difficult. An important example of such stochastic systems is porous media for which the reconstruction technique must accurately represent their morphology--the connectivity and geometry--as well as their flow and transport properties. Many of the current reconstruction methods are based on low-order statistical descriptors that fail to provide accurate information on the properties of heterogeneous porous media. On the other hand, due to the availability of high resolution two-dimensional (2D) images of thin sections of a porous medium, and at the same time, the high cost, computational difficulties, and even unavailability of complete 3D images, the problem of reconstructing porous media from 2D thin sections remains an outstanding unsolved problem. We present a method based on multiple-point statistics in which a single 2D thin section of a porous medium, represented by a digitized image, is used to reconstruct the 3D porous medium to which the thin section belongs. The method utilizes a 1D raster path for inspecting the digitized image, and combines it with a cross-correlation function, a grid splitting technique for deciding the resolution of the computational grid used in the reconstruction, and the Shannon entropy as a measure of the heterogeneity of the porous sample, in order to reconstruct the 3D medium. It also utilizes an adaptive technique for identifying the locations and optimal number of hard (quantitative) data points that one can use in the reconstruction process. The method is tested on high resolution images for Berea sandstone and a carbonate rock sample, and the results are compared with the data. To make the comparison quantitative, two sets of statistical tests consisting of the autocorrelation function, histogram matching of the local coordination numbers, the pore and throat size distributions, multiple-points connectivity, and single- and two-phase flow permeabilities are used. The comparison indicates that the proposed method reproduces the long-range connectivity of the porous media, with the computed properties being in good agreement with the data for both porous samples. The computational efficiency of the method is also demonstrated.

Liquid intrusion and alternative methods for the characterization of macroporous materials (IUPAC Technical Report)

This document deals with the characterization of porous materials having pore widths in the macropore range of 50 nm to 500 μm. In recent years, the development of advanced adsorbents and catalysts (e.g., monoliths having hierarchical pore networks) has brought about a renewed interest in macropore structures. Mercury intrusion–extrusion porosimetry is a well-established method, which is at present the most widely used for determining the macropore size distribution. However, because of the reservations raised by the use of mercury, it is now evident that the principles involved in the application of mercury porosimetry require reappraisal and that alternative methods are worth being listed and evaluated. The reliability of mercury porosimetry is discussed in the first part of the report along with the conditions required for its safe use. Other procedures for macropore size analysis, which are critically examined, include the intrusion of other non-wetting liquids and certain wetting liquids, capillary condensation, liquid permeation, imaging, and image analysis. The statistical reconstruction of porous materials and the use of macroporous reference materials (RMs) are also examined. Finally, the future of macropore analysis is discussed.

Influence of the glass transition on the liquid-gas spinodal decomposition

We use large-scale molecular dynamics simulations to study the kinetics of the liquid-gas phase separation if the temperature is lowered across the glass transition of the dense phase. We observe a gradual change from phase separated systems at high temperatures to nonequilibrium, gel-like structures that evolve very slowly at low temperatures. The microscopic mechanisms responsible for the coarsening strongly depend on temperature, and change from diffusive motion at high temperature to a strongly intermittent, heterogeneous, and thermally activated dynamics at low temperature, leading to logarithmically slow growth of the typical domain size.