Understanding Material Characteristics through Signature Traits from Helium Pycnometry.

Although helium pycnometry is generally the method of choice for skeletal density measurements of porous materials, few studies have provided a wide range of case studies that demonstrate how to best interpret raw data and perform measurements using it. The examination of several different classes of materials yielded signature traits from helium pycnometry data that are highlighted. Experimental parameters important in obtaining the most precise and accurate value of skeletal density from the helium pycnometer are as high as possible percent fill volume and good thermostability. The degree of sample activation is demonstrated to affect the measured skeletal density of porous zeolitic, carbon, and hybrid inorganic-organic materials. In the presence of a significant amount of physisorbed contaminants (water vapor, atmospheric gases, residual solvents, etc.), which was the case for ZSM-5, MIL-53, and F400, but not ZIF-8, the skeletal density tended to be overestimated in the low percent volume region. In addition, the kinetic data (i.e., skeletal density vs measurement cycle) reveals distinctive traits for a properly activated vs a nonactivated sample for all examined samples: activated samples with a significant amount of mass loss show a curved down plot that eventually reaches the equilibrium value, whereas nonactivated, nonporous, or extremely hydrophobic samples exhibit a flat line. This work illustrates how helium pycnometry can provide information about the structure of a material, and that, conversely, when  the structure of the material and its percent mass loss after activation (amount of physisorbed contaminants) are known, the behavior of activated and nonactivated samples in terms of skeletal density, percent fill volume, and measurement cycle can be predicted.

Molecular simulation of capillary phase transitions in flexible porous materials.

We used flat-histogram sampling Monte Carlo to study capillary phase transitions in deformable adsorbent materials. Specifically, we considered a pure adsorbate fluid below its bulk critical temperature within a slit pore of variable pore width. The instantaneous pore width is dictated by a number of factors, such as adsorbate loading, reservoir pressure, fluid-wall interaction, and bare adsorbent properties. In the slit pores studied here, the bare adsorbent free energy was assumed to be biparabolic, consisting of two preferential pore configurations, namely, the narrow pore and the large pore configurations. Four distinct phases could be found in the adsorption isotherms. We found a low-pressure phase transition, driven primarily by capillary condensation/evaporation and accompanied by adsorbent deformation in response. The deformation can be a relatively small contraction/expansion as seen in elastic materials, or a large-scale structural transformation of the adsorbent. We also found a high-pressure transition driven by excluded volume effects, which tends to expand the material and thus results in a large-scale structural transformation of the adsorbent. The adsorption isotherms and osmotic free energies can be rationalized by considering the relative free energy differences between the basins of the bare adsorbent free energy.

The Ninth Industrial Fluid Properties Simulation Challenge.

The Ninth Industrial Fluid Properties Simulation Challenge aimed to test the ability of molecular modeling approaches to predict water/oil interfacial tension (IFT) at conditions of high temperature and pressure. In particular, the challenge featured water/oil IFT where the oil was n-dodecane, toluene, or a 50:50 n-dodecane/toluene blend at 1.825 MPa and temperatures in the range of 383 K to 443 K. Seven entries were received including approaches such as molecular dynamics (MD) and Monte Carlo (MC) simulations, COSMO-RS, and iSAFT, and they were judged by comparison to pendant drop tensiometer benchmark data. The quality of predictions varied among the entries between approximately 20 % and 70 % of the total points possible with the entries based on MD and MC having the highest scores in most cases. As is often the case in molecular modeling, predictions of the relative trends tended to be reliable even if the absolute values were not.

Quasi-Two-Dimensional Phase Transition of Methane Adsorbed in Cylindrical Silica Mesopores.

Using Monte Carlo and molecular dynamics simulations, we examine the adsorption of methane in cylindrical silica mesopores in an effort to understand a possible phase transition of adsorbed methane in MCM-41 and SBA-15 silica that was previously identified by an unexpected increase in the adsorbed fluid density following capillary condensation, as measured by small-angle neutron scattering (SANS) [Chiang, W-S., et al., Langmuir 2016, 32, 8849]. Our initial simulation results identify a roughly 10 % increase in the density of the liquidlike adsorbed phase for either an isotherm with increasing pressure or an isobar with decreasing temperature and that this densification is associated with a local maximum in the isosteric enthalpy of adsorption. Subsequent analysis of the simulated fluid, via computation of bond-orientational order parameters of specific annular layers of the adsorbed fluid, showed that the layers undergo an ordering transition from a disordered, amorphous state to one with two-dimensional hexagonal structure. Furthermore, this two-dimensional restructuring of the fluid occurs at the same thermodynamic state points as the aforementioned densification and local maximum in the isosteric enthalpy of adsorption. We thus conclude that the densification of the fluid is the result of structural reorganization, which is signaled by the maximum in the isosteric enthalpy. Owing to the qualitative similarity of the structural transitions in the simulated and experimental methane fluids, we propose this hexagonal reorganization as a plausible explanation of the densification observed in SANS measurements. Lastly, we speculate how this structural transition may impact the transport properties of the adsorbed fluid.

Position-Dependent Dynamics Explain Pore-Averaged Diffusion in Strongly Attractive Adsorptive Systems.

Using molecular simulations, we investigate the relationship between the pore-averaged and position-dependent self-diffusivity of a fluid adsorbed in a strongly attractive pore as a function of loading. Previous work (Krekelberg, W. P.; Siderius, D. W.; Shen, V. K.; Truskett, T. M.; Errington, J. R. Connection between thermodynamics and dynamics of simple fluids in highly attractive pores. Langmuir 2013, 29, 14527-14535, doi: 10.1021/la4037327) established that pore-averaged self-diffusivity in the multilayer adsorption regime, where the fluid exhibits a dense film at the pore surface and a lower density interior pore region, is nearly constant as a function of loading. Here we show that this puzzling behavior can be understood in terms of how loading affects the fraction of particles that reside in the film and interior pore regions as well as their distinct dynamics. Specifically, the insensitivity of pore-averaged diffusivity to loading arises from the approximate cancellation of two factors: an increase in the fraction of particles in the higher diffusivity interior pore region with loading and a corresponding decrease in the particle diffusivity in that region. We also find that the position-dependent self-diffusivities scale with the position-dependent density. We present a model for predicting the pore-average self-diffusivity based on the position-dependent self-diffusivity, which captures the unusual characteristics of pore-averaged self-diffusivity in strongly attractive pores over several orders of magnitude.

Modulus-pressure equation for confined fluids.

Ultrasonic experiments allow one to measure the elastic modulus of bulk solid or fluid samples. Recently such experiments have been carried out on fluid-saturated nanoporous glass to probe the modulus of a confined fluid. In our previous work [G. Y. Gor et al., J. Chem. Phys., 143, 194506 (2015)], using Monte Carlo simulations we showed that the elastic modulus K of a fluid confined in a mesopore is a function of the pore size. Here we focus on the modulus-pressure dependence K(P), which is linear for bulk materials, a relation known as the Tait-Murnaghan equation. Using transition-matrix Monte Carlo simulations we calculated the elastic modulus of bulk argon as a function of pressure and argon confined in silica mesopores as a function of Laplace pressure. Our calculations show that while the elastic modulus is strongly affected by confinement and temperature, the slope of the modulus versus pressure is not. Moreover, the calculated slope is in a good agreement with the reference data for bulk argon and experimental data for confined argon derived from ultrasonic experiments. We propose to use the value of the slope of K(P) to estimate the elastic moduli of an unknown porous medium.

The Eighth Industrial Fluids Properties Simulation Challenge.

The goal of the eighth industrial fluid properties simulation challenge was to test the ability of molecular simulation methods to predict the adsorption of organic adsorbates in activated carbon materials. In particular, the eighth challenge focused on the adsorption of perfluorohexane in the activated carbon BAM-109. Entrants were challenged to predict the adsorption in the carbon at 273 K and relative pressures of 0.1, 0.3, and 0.6. The predictions were judged by comparison to a benchmark set of experimentally determined values. Overall good agreement and consistency were found between the predictions of most entrants.

Adsorption, X-ray Diffraction, Photoelectron, and Atomic Emission Spectroscopy Benchmark Studies for the Eighth Industrial Fluid Properties Simulation Challenge.

The primary goal of the eighth industrial fluid properties simulation challenge was to test the ability of molecular simulation methods to predict the adsorption of organic adsorbates in activated carbon materials. The challenge focused on the adsorption of perfluorohexane in the activated carbon standard BAM-P109 (Panne and Thünemann 2010). Entrants were challenged to predict the adsorption of perfluorohexane in the activated carbon at a temperature of 273 K and at relative pressures of 0.1, 0.3, and 0.6. The relative pressure (P/Po) is defined as that relative to the bulk saturation pressure predicted by the fluid model at a given temperature (273 K in this case). The predictions were judged by comparison to a set of experimentally determined values, which are published here for the first time and were not disclosed to the entrants prior to the challenge. Benchmark experimental studies, described herein, were also carried out and provided to entrants in order to aid in the development of new force fields and simulation methods to be employed in the challenge. These studies included argon, carbon dioxide, and water adsorption in the BAM-P109 activated carbon as well as X-ray diffraction, X-ray microtomography, photoelectron spectroscopy, and atomic emission spectroscopy studies of BAM-P109. Several concurrent studies were carried out for the BAM-P108 activated carbon (Panne and Thünemann 2010). These are included in the current manuscript for comparison.

Relation between pore size and the compressibility of a confined fluid.

When a fluid is confined to a nanopore, its thermodynamic properties differ from the properties of a bulk fluid, so measuring such properties of the confined fluid can provide information about the pore sizes. Here, we report a simple relation between the pore size and isothermal compressibility of argon confined in such pores. Compressibility is calculated from the fluctuations of the number of particles in the grand canonical ensemble using two different simulation techniques: conventional grand-canonical Monte Carlo and grand-canonical ensemble transition-matrix Monte Carlo. Our results provide a theoretical framework for extracting the information on the pore sizes of fluid-saturated samples by measuring the compressibility from ultrasonic experiments.

Elucidating the effects of adsorbent flexibility on fluid adsorption using simple models and flat-histogram sampling methods.

Using flat-histogram Monte Carlo methods, we investigate the adsorptive behavior of the square-well fluid in two simple slit-pore-like models intended to capture fundamental characteristics of flexible adsorbent materials. Both models require as input thermodynamic information about the flexible adsorbent material itself. An important component of this work involves formulating the flexible pore models in the appropriate thermodynamic (statistical mechanical) ensembles, namely, the osmotic ensemble and a variant of the grand-canonical ensemble. Two-dimensional probability distributions, which are calculated using flat-histogram methods, provide the information necessary to determine adsorption thermodynamics. For example, we are able to determine precisely adsorption isotherms, (equilibrium) phase transition conditions, limits of stability, and free energies for a number of different flexible adsorbent materials, distinguishable as different inputs into the models. While the models used in this work are relatively simple from a geometric perspective, they yield non-trivial adsorptive behavior, including adsorption-desorption hysteresis solely due to material flexibility and so-called "breathing" of the adsorbent. The observed effects can in turn be tied to the inherent properties of the bare adsorbent. Some of the effects are expected on physical grounds while others arise from a subtle balance of thermodynamic and mechanical driving forces. In addition, the computational strategy presented here can be easily applied to more complex models for flexible adsorbents.

Flat-Histogram Monte Carlo Simulation of Water Adsorption in Metal-Organic Frameworks.

Molecular simulations of water adsorption in porous materials often converge slowly due to sampling bottlenecks that follow from hydrogen bonding and, in many cases, the formation of water clusters. These effects may be exacerbated in metal-organic framework (MOF) adsorbents, due to the presence of pore spaces (cages) that promote the formation of discrete-size clusters and hydrophobic effects (if present), among other reasons. In Grand Canonical Monte Carlo (MC) simulations, these sampling challenges are typically manifested by low MC acceptance ratios, a tendency for the simulation to become stuck in a particular loading state (i.e., macrostates), and the persistence of specific clusters for long periods of the simulation. We present simulation strategies to address these sampling challenges, by applying flat-histogram MC (FHMC) methods and specialized MC move types to simulations of water adsorption. FHMC, in both Transition-matrix and Wang-Landau forms, drives the simulation to sample relevant macrostates by incorporating weights that are self-consistently adjusted throughout the simulation and generate the macrostate probability distribution (MPD). Specialized MC moves, based on aggregation-volume bias and configurational bias methods, separately address low acceptance ratios for basic MC trial moves and specifically target water molecules in clusters; in turn, the specialized MC moves improve the efficiency of generating new configurations which is ultimately reflected in improved statistics collected by FHMC. The combined strategies are applied to study the adsorption of water in CuBTC and ZIF-8 at 300 K, through examination of the MPD and the adsorption isotherm generated by histogram reweighting. A key result is the appearance of nontrivial oscillations in the MPD, which we show to be associated with water clusters in the adsorption system. Additionally, we show that the probabilities of certain clusters become similar in value near the boundaries of the isotherm hysteresis loop, indicating a strong connection between cluster formation/destruction and the thermodynamic limits of stability. For a hydrophobic MOF, the FHMC results show that the phase transition from low density to high density is suppressed to water pressure far above the bulk-fluid saturation pressure; this is consistent with results presented elsewhere. We also compare our FHMC simulation isotherm to one measured by a different technique but with ostensibly the same molecular interactions and comment on observed differences and the need for follow-up work. The simulation strategies presented here can be applied to the simulation of water in other MOFs using heuristic guidelines laid out in our text, which should facilitate the more consistent and efficient simulation of water adsorption in porous materials in future applications.

Connection between thermodynamics and dynamics of simple fluids in highly attractive pores.

Using molecular simulations, we investigate the structural and diffusive dynamics properties of a model fluid in highly absorptive cylindrical pores. At subcritical temperatures, self-diffusivity displays three distinct regimes as a function of average pore density ρ: (1) a decrease in self-diffusivity with increasing ρ at low ρ, (2) constant self-diffusivity with respect to varying ρ at moderate density, and (3) a decrease in self-diffusivity with increasing ρ at high density. These regimes are closely linked to the thermodynamic properties of the fluid in the pore, specifically, the adsorption isotherm, isosteric heat of adsorption, and the density profile. We show that these three diffusivity regimes qualitatively correspond to three distinct adsorption regimes: monolayer formation, multilayer adsorption, and pore filling, respectively. In addition, we find that the self-diffusivity is a universal function of the local film density in the monolayer formation regime at subcritical temperatures. The results of this work suggest a potential means to estimate the self-diffusivity over a broad pressure range using a limited number of experiments.

Efficiency Comparison of Single- and Multiple-Macrostate Grand Canonical Ensemble Transition-Matrix Monte Carlo Simulations.

Recent interest in parallelizing flat-histogram transition-matrix Monte Carlo simulations in the grand canonical ensemble, due to its demonstrated effectiveness in studying phase behavior, self-assembly and adsorption, has led to the most extreme case of single-macrostate simulations, where each macrostate is simulated independently with ghost particle insertions and deletions. Despite their use in several studies, no efficiency comparisons of these single-macrostate simulations have been made with multiple-macrostate simulations. We show that multiple-macrostate simulations are up to 3 orders of magnitude more efficient than single-macrostate simulations, which demonstrates the remarkable efficiency of flat-histogram biased insertions and deletions, even with low acceptance probabilities. Efficiency comparisons were made for supercritical fluids and vapor-liquid equilibrium of bulk Lennard-Jones and a three-site water model, self-assembling patchy trimer particles and adsorption of a Lennard-Jones fluid confined in a purely repulsive porous network, using the open source simulation toolkit FEASST. By directly comparing with a variety of Monte Carlo trial move sets, this efficiency loss in single-macrostate simulations is attributed to three related reasons. First, ghost particle insertions and deletions in single-macrostate simulations incur the same computational expense as grand canonical ensemble trials in multiple-macrostate simulations, yet ghost trials do not reap the sampling benefit from propagating the Markov chain to a new microstate. Second, single-macrostate simulations lack macrostate change trials that are biased by the self-consistently converging relative macrostate probability, which is a major component of flat histogram simulations. Third, limiting a Markov chain to a single macrostate reduces sampling possibilities. Existing parallelization methods for multiple-macrostate flat-histogram simulations are shown to be more efficient than parallel single-macrostate simulations by approximately an order of magnitude or more in all systems investigated.

Time-dependent CO2 sorption hysteresis in a one-dimensional microporous octahedral molecular sieve.

The development of sorbents for next-generation CO(2) mitigation technologies will require better understanding of CO(2)/sorbent interactions. Among the sorbents under consideration are shape-selective microporous molecular sieves with hierarchical pore morphologies of reduced dimensionality. We have characterized the non-equilibrium CO(2) sorption of OMS-2, a well-known one-dimensional microporous octahedral molecular sieve with manganese oxide framework. Remarkably, we find that the degree of CO(2) sorption hysteresis increases when the gas/sorbent system is allowed to equilibrate for longer times at each pressure step. Density functional theory calculations indicate a "gate-keeping" role of the cation in the tunnel, only allowing CO(2) molecules to enter fully into the tunnel via a highly unstable transient state when CO(2) loadings exceed 0.75 mmol/g. The energy barrier associated with the gate-keeping effect suggests an adsorption mechanism in which kinetic trapping of CO(2) is responsible for the observed hysteretic behavior.

Osmotic virial coefficients for model protein and colloidal solutions: importance of ensemble constraints in the analysis of light scattering data.

Protein-protein interactions in solution may be quantified by the osmotic second virial coefficient (OSVC), which can be measured by various experimental techniques including light scattering. Analysis of Rayleigh light scattering measurements from such experiments requires identification of a scattering volume and the thermodynamic constraints imposed on that volume, i.e., the statistical mechanical ensemble in which light scattering occurs. Depending on the set of constraints imposed on the scattering volume, one can obtain either an apparent OSVC, A(2,app), or the true thermodynamic OSVC, B(22)(osm), that is rigorously defined in solution theory [M. A. Blanco, E. Sahin, Y. Li, and C. J. Roberts, J. Chem. Phys. 134, 225103 (2011)]. However, it is unclear to what extent A(2,app) and B(22)(osm) differ, which may have implications on the physical interpretation of OSVC measurements from light scattering experiments. In this paper, we use the multicomponent hard-sphere model and a well-known equation of state to directly compare A(2,app) and B(22)(osm). Our results from the hard-sphere equation of state indicate that A(2,app) underestimates B(22)(osm), but in a systematic manner that may be explained using fundamental thermodynamic expressions for the two OSVCs. The difference between A(2,app) and B(22)(osm) may be quantitatively significant, but may also be obscured in experimental application by statistical uncertainty or non-steric interactions. Consequently, the two OSVCs that arise in the analysis of light scattering measurements do formally differ, but in a manner that may not be detectable in actual application.

Temperature Extrapolation of Henry's Law Constants and the Isosteric Heat of Adsorption.

Computational screening of adsorbent materials often uses the Henry's law constant (KH) (at a particular temperature) as a first discriminator metric due to its relative ease of calculation. The isosteric heat of adsorption in the limit of zero pressure (qst∞) is often calculated along with the Henry's law constant, and both properties are informative metrics of adsorbent material performance at low-pressure conditions. In this article, we introduce a method for extrapolating KH as a function of temperature, using series-expansion coefficients that are easily computed at the same time as KH itself; the extrapolation function also yields qst∞. The extrapolation is highly accurate over a wide range of temperatures when the basis temperature is sufficiently high, for a wide range of adsorbent materials and adsorbate gases. Various results suggest that the extrapolation is accurate when the extrapolation range in inverse-temperature space is limited to |ß - ß0 | < 0.5 mol/kJ. Application of the extrapolation to a large set of materials is shown to be successful provided that KH is not extremely large and/or the extrapolation coefficients converge satisfactorily. The extrapolation is also able to predict qst∞ for a system that shows an unusually large temperature dependence. The work provides a robust method for predicting KH and qst∞ over a wide range of industrially relevant temperatures with minimal effort beyond that necessary to compute those properties at a single temperature, which facilitates the addition of practical operating (or processing) conditions to computational screening exercises.

Extension of the Steele 10-4-3 potential for adsorption calculations in cylindrical, spherical, and other pore geometries.

Simplified fluid-substrate interaction models derived from the Lennard-Jones potential are widely used in the simulation of gas physisorption phenomena. In this paper, we reinterpret the well known Steele 10-4-3 potential for a gas molecule interacting with a planar surface, and use the resultant scheme to derive new potentials for cylindrical and spherical pore geometries. These new potentials correctly recover the Steele result in the limit of infinite pore radius, a useful improvement over existing models. We demonstrate the new cylindrical Steele 10-4-3 potential in calculations of argon adsorption via fluid density functional theory. This potential yields markedly different adsorption behavior than existing cylindrical potentials, which follow from small but significant differences in both the strength and the shape of the fluid-surface interaction. These differences cannot be fully reconciled simply by reparameterizing (scaling) the existing models; the new potential is more realistic in design, and is especially to be preferred in studies where comparison with planar substrates is made. Finally, we discuss extensions of this approach to more complicated pore geometries, yielding a family of Steele-like potentials that all satisfy the correct planar limit.

Computational Investigation of Correlations in Adsorbate Entropy for Pure-Silica Zeolite Adsorbents.

Vast numbers of unstudied hypothetical porous frameworks continue to spark interest in optimizing adsorption and catalytic processes. Evaluating the use of such materials depends on the accessibility of thermodynamic metrics such as the free energy, which, in turn, depend on the satisfactory estimation or calculation of the adsorption entropy, which often remains elusive. Previous works using simulations and experimental data have demonstrated relationships between the entropy and system descriptors, allowing for sensible predictions based on more-easily obtained physical parameters. However, the resultant conclusions were either based on experimental data for industrially relevant alkanes or lacked a significant sample size. In this paper, we evaluate correlations between gas-phase and adsorbed-phase entropies for a larger and more chemically diverse set of adsorbate molecules by using force fields and statistical mechanical expressions to calculate those entropies. In total, we perform calculations for 37 molecules across 10 chemical categories available in the TraPPE force field set, as adsorbed in five siliceous zeolites. Our results show that linear correlations between the gas- and adsorbed-phase entropies persist for the larger and diverse set of adsorbate molecules studied here, proving a broader applicability and justifying the use of simple correlations for many adsorbates and, presumably, adsorbent materials.

Thermodynamic and structural properties of finely discretized on-lattice hard-sphere fluids: Virial coefficients, free energies, and direct correlation functions.

Using both molecular simulation and theory, we examine fluid-phase thermodynamic and structural properties of on-lattice hard-sphere fluids. Our purpose in this work is to provide reference data for on-lattice density functional theories [D. W. Siderius and L. D. Gelb, Langmuir 25, 1296 (2009)] and related perturbation theories. In this model, hard spheres are located at sites on a finely discretized cubic lattice where the spacing between lattice sites is between one-tenth and one-third the hard-sphere diameter. We calculate exactly the second, third, and fourth virial coefficients as functions of the lattice spacing. Via Monte Carlo simulation, we measure the excess chemical potential as a function of density for several lattice spacings. These results are then parametrized with a convenient functional form and can immediately be used in on-lattice density functional theories. Of particular interest is to identify those lattice spacings that yield properties similar to those of the off-lattice fluid. We find that the properties of the on-lattice fluid are strongly dependent on lattice spacing, generally approaching those of the off-lattice fluid with increasing lattice resolution, but not smoothly. These observations are consistent with results for larger lattice spacings [A. Z. Panagiotopoulos, J. Chem. Phys. 123, 104504 (2005)]. Certain lattice spacings are found to yield fluid properties in particularly good agreement with the off-lattice fluid. We also find that the agreement of many different on- and off-lattice hard-sphere fluid properties is predicted quite well by that of the virial coefficients, suggesting that they may be used to identify favorable lattice spacings. The direct correlation function at a few lattice spacings and a single density is obtained from simulation. The on-lattice fluid is structurally anisotropic, exhibiting spherical asymmetry in correlation functions. Interestingly, the anisotropies are properly captured in the Percus-Yevick-based calculation of the direct correlation function. Lastly, we speculate on the possibility of obtaining a theoretical equation of state of the on-lattice hard-sphere fluid computed in the Percus-Yevick approximation.

The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation.

Metal-organic frameworks (MOFs) are highly tuneable, extended-network, crystalline, nanoporous materials with applications in gas storage, separations, and sensing. We review how molecular models and simulations of gas adsorption in MOFs have informed the discovery of performant MOFs for methane, hydrogen, and oxygen storage, xenon, carbon dioxide, and chemical warfare agent capture, and xylene enrichment. Particularly, we highlight how large, open databases of MOF crystal structures, post-processed to enable molecular simulations, are a platform for computational materials discovery. We discuss how to orient research efforts to routinise the computational discovery of MOFs for adsorption-based engineering applications.