Configurational-bias Monte Carlo Research Articles

Elucidating the failure of the Ideal Adsorbed Solution Theory for CO2/H2O mixture adsorption in CALF-20

The use of CALF-20 for CO2 capture from humid flue gases has attracted a vast amount of attention from both academia and industry. The focus of this article is on CO2/H2O mixture adsorption for which published experimental data demonstrate the severe limitations of the Ideal Adsorbed Solution Theory (IAST) in providing a quantitative estimation of the component loadings. We use Configurational-Bias Monte Carlo (CBMC) simulations for elucidating the origins of thermodynamic non-idealities. The CBMC simulations reveal that two distinct regimes prevail during mixture adsorption. For low relative humidities less than say 20 %, the CO2 loadings in the adsorbed phase is significantly higher than anticipated by the IAST. CBMC simulations of intermolecular distances for guest pairs reveal that failure of the IAST can be traced to the phenomenon of segregated adsorption. The H2O-H2O pairs are close together at typical distances of about 3 Å. The CO2-H2O pairs are typically 8 Å apart, occupying adjacent adsorption sites corresponding to the O atoms of the oxalate group. This implies that the CO2 molecules face a less severe competitive adsorption with H2O than is anticipated by the IAST, whose applicability mandates a uniform and homogeneous distribution of adsorbates in pore space. The situation changes dramatically at high values of relative humidities, typically larger than about 50 %; in this scenario, the adsorbed phase is significantly richer in H2O. The CO2 molecules are compelled to share same adsorption site with pairs of H2O molecules that are hydrogen-bonded with each other. Consequently, the competition faced by CO2 is significantly higher than anticipated by the IAST, resulting in significantly lower CO2 uptakes.The important message that emerges from this investigation is the need to incorporate the Real Adsorbed Solution Theory (RAST) for quantitative modelling of fixed-bed adsorbers in CO2 capture with CALF-20.

Fundamental insights into the variety of factors that influence water/alcohol membrane permeation selectivity

The primary objective of this article is to develop a fundamental understanding of water/methanol and water/ethanol mixture permeation across microporous membrane constructs. Configurational-Bias Monte Carlo (CBMC) simulations were undertaken for water/methanol and water/ethanol mixture adsorption in all-silica zeolites (CHA, DDR, FAU, LTA) and ZIF-8. Additionally, Molecular Dynamics (MD) simulations were used to determine the intra-crystalline diffusivities in water/alcohol mixtures. The combination of CBMC and MD simulations allow the calculation of membrane permeation selectivities. This study provides insights into the influence of the structural properties of the microporous layer on the permeation selectivity. Another key result that emerges is that the water/alcohol permeation selectivity becomes increasingly in favor of water as the feed mixtures becomes richer in alcohol. The reason for the dependence can be traced to strong hydrogen bonding between water and alcohol molecular pairs resulting in cluster formation and enhanced water ingress; these results provide a rationalization of a number of membrane permeation studies in the literature. A corollary to the reported results is that the use of the Ideal Adsorbed Solution Theory (IAST) is unable to provide a quantitative description of mixture adsorption equilibrium and thermodynamic non-idealities need to be accounted for in modelling membrane permeation of water/alcohol mixtures.

Hierarchical Computational Screening of Quantum Metal-Organic Framework Database to Identify Metal-Organic Frameworks for Volatile Organic-Compound Capture from Air.

The design and discovery of novel porous materials that can efficiently capture volatile organic compounds (VOCs) from air are critical to address one of the most important challenges of our world, air pollution. In this work, we studied a recently introduced metal-organic framework (MOF) database, namely, quantum MOF (QMOF) database, to unlock the potential of both experimentally synthesized and hypothetically generated structures for adsorption-based n-butane (C4H10) capture from air. Configurational Bias Monte Carlo (CBMC) simulations were used to study the adsorption of a quaternary gas mixture of N2, O2, Ar, and C4H10 in QMOFs for two different processes, pressure swing adsorption (PSA) and vacuum-swing adsorption (VSA). Several adsorbent performance evaluation metrics, such as C4H10 selectivity, working capacity, the adsorbent performance score, and percent regenerability, were used to identify the best adsorbent candidates, which were then further studied by molecular simulations for C4H10 capture from a more realistic seven-component air mixture consisting of N2, O2, Ar, C4H10, C3H8, C3H6, and C2H6. Results showed that the top five QMOFs have C4H10 selectivities between 6.3 × 103 and 9 × 103 (3.8 × 103 and 5 × 103) at 1 bar (10 bar). Detailed analysis of the structure-performance relations showed that low/mediocre porosity (0.4-0.6) and narrow pore sizes (6-9 Å) of QMOFs lead to high C4H10 selectivities. Radial distribution function analyses of the top materials revealed that C4H10 molecules tend to confine close to the organic parts of MOFs. Our results provided the first information in the literature about the VOC capture potential of a large variety and number of MOFs, which will be useful to direct the experimental efforts to the most promising adsorbent materials for C4H10 capture from air.

Using the spreading pressure to inter-relate the characteristics of unary, binary and ternary mixture permeation across microporous membranes

The primary objective of this article is to investigate the possibility of inter-relating the characteristics of unary, binary, and ternary mixtures across microporous zeolite membranes. Towards this end, we performed Configurational-Bias Monte Carlo (CBMC) simulations of mixture adsorption equilibrium, and Molecular Dynamics (MD) simulations of guest diffusivities in unary (CO2, CH4, N2, and H2), binary (CO2/CH4, CO2/N2, CH4/N2, CO2/H2), and ternary (CO2/CH4/N2, CO2/CH4/H2, CO2/N2/H2) mixtures in four zeolites: CHA, DDR, MFI, and FAU. The combined CBMC and MD data are used to obtain fundamental insights into the adsorption, diffusion, and permeation characteristics of the variety of guest/host combinations. Application of the Myers-Prausnitz theory shows that the adsorption selectivity for the i-j pair, Sads,ij, in ternary mixtures has practically the same value as for the binary i-j mixture, provided the comparison is made as the same surface potential Φ, a convenient and practical proxy for the spreading pressure π, that is calculable on the basis of the data on the unary isotherms of the constituent guests. For the mixtures investigated, departures from thermodynamic idealities do not cause deviations from the uniqueness of the Sads,ij vs Φ dependence because the ratios of the activity coefficients γi/γj also appear to uniquely depend on Φ.The surface potential Φ is also the thermodynamically correct metric to describe the loading dependence of diffusivities. Compared at the same Φ, the diffusion selectivity for the i-j pair, Sdiff,ij, in ternary mixtures has practically the same value as for the binary i-j mixture. Consequently, the permeation selectivity, Sperm,ij=Sads,ij×Sdiff,ij is also uniquely dependent on Φ. When compared at the same Φ, the component permeabilities, Πi for CO2, CH4, and N2 are found to be independent of the partners in the binary and ternary mixtures investigated and have practically the same as the values for the corresponding unary permeabilities.

The shape selectivity of zeolites in isobutane alkylation: An investigation using CBMC and MD simulations

The adsorption and diffusion behaviors of C8 isomers and C9 component as main products of the isobutane alkylation catalyzed by zeolites with different topologies were investigated using configurational bias Monte Carlo (CBMC) and MD simulations in this work. The adsorption capacity of zeolites at 353 K and 2.0 MPa relies on their pore volume with the order of FAU > BEA > LTL > MOR. The diffusion coefficient of C8 and C9 molecules increases with the decrease of loading and the increase of temperature, and the more compact molecules diffuse slower than the slimmer ones at low loadings while quicker at higher loadings. It was found that for zeolites, small adsorption heat of C8 isomers, or large molecular diffusion coefficient would correspond to a high selectivity of target alkylates. Particularly, BEA zeolite with large RPLD/LCD shows high reaction selectivity, rendering it a good candidate catalyst for C4 alkylation.

Partial Order–Disorder Transformation of Interpenetrated Porous Coordination Polymers

Controlling interpenetration and flexibility behaviors is intriguing and fundamental for porous coordination polymers. We report exceptional interpenetration behaviors involving controllable partia...

How Reliable Is the Ideal Adsorbed Solution Theory for the Estimation of Mixture Separation Selectivities in Microporous Crystalline Adsorbents?

Microporous crystalline adsorbents such as zeolites and metal–organic frameworks (MOFs) have potential use in a wide variety of separation applications. The adsorption selectivity Sads is a key metric that quantifies the efficacy of any microporous adsorbent in mixture separations. The Ideal Adsorbed Solution Theory (IAST) is commonly used for estimating the value of Sads, with unary isotherms of the constituent guests as data inputs. There are two basic tenets underlying the development of the IAST. The first tenet mandates a homogeneous distribution of adsorbates within the pore landscape. The second tenet requires the surface area occupied by a guest molecule in the mixture to be the same as that for the corresponding pure component. Configurational-bias Monte Carlo (CBMC) simulations are employed in this article to highlight several scenarios in which the IAST fails to provide a quantitatively correct description of mixture adsorption equilibrium due to a failure to conform to either of the two tenets underpinning the IAST. For CO2 capture with cation-exchanged zeolites and MOFs with open metal sites, there is congregation of CO2 around the cations and unsaturated metal atoms, resulting in failure of the IAST due to an inhomogeneous distribution of adsorbates in the pore space. Thermodynamic non-idealities also arise due to the preferential location of CO2 molecules at the window regions of 8-ring zeolites such as DDR and CHA or within pockets of MOR and AFX zeolites. Thermodynamic non-idealities are evidenced for water/alcohol mixtures due to molecular clustering engendered by hydrogen bonding. It is also demonstrated that thermodynamic non-idealities can be strong enough to cause selectivity reversals, which are not anticipated by the IAST.

Using Molecular Simulations to Unravel the Benefits of Characterizing Mixture Permeation in Microporous Membranes in Terms of the Spreading Pressure.

The separation performance of microporous crystalline materials in membrane constructs is dictated by a combination of mixture adsorption and intracrystalline diffusion characteristics; the permeation selectivity Sperm is a product of the adsorption selectivity Sads and the diffusion selectivity, Sdiff. The primary objective of this article is to gain fundamental insights into Sads and Sdiff by use of molecular simulations. We performed configurational-bias Monte Carlo (CBMC) simulations of mixture adsorption equilibrium and molecular dynamics (MD) simulations of guest self-diffusivities of a number of binary mixtures of light gaseous molecules (CO2, CH4, N2, H2, and C2H6) in a variety of microporous hosts of different pore dimensions and topologies. Irrespective of the bulk gas compositions and bulk gas fugacities, the adsorption selectivity, Sads, is found to be uniquely determined by the adsorption potential, Φ, a convenient and practical proxy for the spreading pressure π that is calculable using the ideal adsorbed solution theory for mixture adsorption equilibrium. The adsorption potential Φ is also a proxy for the pore occupancy and is the thermodynamically appropriate yardstick to determine the loading and composition dependences of intracrystalline diffusivities and diffusion selectivities, Sdiff. When compared at the same Φ, the component permeabilities, Πi for CO2, CH4, and N2, determinable from CBMC/MD data, are found to be independent of the partners in the various mixtures investigated and have practically the same values as the values for the corresponding unary permeabilities. In all investigated systems, the H2 permeability in a mixture is significantly lower than the corresponding unary value. These reported results have important practical consequences in process development and are also useful for screening of materials for use as membrane devices.

Water/Alcohol Mixture Adsorption in Hydrophobic Materials: Enhanced Water Ingress Caused by Hydrogen Bonding.

Microporous crystalline porous materials such as zeolites, metal–organic frameworks, and zeolitic imidazolate frameworks (ZIFs) have potential use for separating water/alcohol mixtures in fixed bed adsorbers and membrane permeation devices. For recovery of alcohols present in dilute aqueous solutions, the adsorbent materials need to be hydrophobic in order to prevent the ingress of water. The primary objective of this article is to investigate the accuracy of ideal adsorbed solution theory (IAST) for prediction of water/alcohol mixture adsorption in hydrophobic adsorbents. For this purpose, configurational bias Monte Carlo (CBMC) simulations are used to determine the component loadings for adsorption equilibrium of water/methanol and water/ethanol mixtures in all-silica zeolites (CHA, DDR, and FAU) and ZIF-8. Due to the occurrence of strong hydrogen bonding between water and alcohol molecules and attendant clustering, IAST fails to provide quantitative estimates of the component loadings and the adsorption selectivity. For a range of operating conditions, the water loading in the adsorbed phase may exceed that of pure water by one to two orders of magnitude. Furthermore, the occurrence of water–alcohol clusters moderates size entropy effects that prevail under pore saturation conditions. For quantitative modeling of the CBMC, simulated data requires the application of real adsorbed solution theory by incorporation of activity coefficients, suitably parameterized by the Margules model for the excess Gibbs free energy of adsorption.

Using Molecular Simulations for Elucidation of Thermodynamic Nonidealities in Adsorption of CO2-Containing Mixtures in NaX Zeolite.

Cation-exchanged zeolites are of potential use in pressure swing adsorption (PSA) technologies for CO2 capture applications. Published experimental data for CO2/CH4, CO2/N2, and CO2/C3H8 mixture adsorption in NaX zeolite, also commonly referred to by its trade name 13X, have demonstrated that the ideal adsorbed solution theory (IAST) fails to provide adequately accurate estimates of mixture adsorption equilibrium. In particular, the IAST estimates of CO2/CH4 and CO2/N2 selectivities are significantly higher than those realized in experiments. For CO2/C3H8 mixtures, the IAST fails to anticipate the selectivity reversal phenomena observed in experiments. In this article, configurational-bias Monte Carlo (CBMC) simulations are employed to provide confirmation of the observed thermodynamic nonidealities in adsorption of CO2/CH4, CO2/N2, and CO2/C3H8 mixtures in NaX zeolite. The CBMC simulations provide valuable insights into the root cause of the failure of the IAST, whose applicability mandates a homogeneous distribution of adsorbates within the pore landscape. By sampling 105 equilibrated spatial locations of individual guest molecules within the cages of NaX zeolite, the radial distribution functions (RDFs) of each of the pairs of guest molecules are determined. Examination of the RDFs clearly reveals congregation effects, wherein the CO2 guests occupy positions in close proximity to the Na+ cations. The positioning of the partner molecules (CH4, N2, or C3H8) is further removed from the CO2 guest molecules; consequently, the competition in mixture adsorption faced by the partner molecules is less severe than that anticipated by the IAST. The important message to emerge from this article is the need for quantification of thermodynamic nonideality effects in mixture adsorption.

DICE: A Monte Carlo Code for Molecular Simulation Including the Configurational Bias Monte Carlo Method

Solute-solvent systems are an important topic of study, as the effects of the solvent on the solute can drastically change its properties. Theoretical studies of these systems are done with ab initio methods, molecular simulations, or a combination of both. The simulations of molecular systems are usually performed with either molecular dynamics (MD) or Monte Carlo (MC) methods. Classical MD has evolved much in the last decades, both in algorithms and implementations, having several stable and efficient codes developed and available. Similarly, MC methods have also evolved, focusing mainly in creating and improving methods and implementations in available codes. In this paper, we provide some enhancements to a configurational bias Monte Carlo (CBMC) methodology to simulate flexible molecules using the molecular fragments concept. In our implementation the acceptance criterion of the CBMC method was simplified and a generalization was proposed to allow the simulation of molecules with any kind of fragments. We also introduce the new version of DICE, an MC code for molecular simulation (available at https://portal.if.usp.br/dice). This code was mainly developed to simulate solute-solvent systems in liquid and gas phases and in interfaces (gas-liquid and solid-liquid) that has been mostly used to generate configurations for a sequential quantum mechanics/molecular mechanics method (S-QM/MM). This new version introduces several improvements over the previous ones, with the ability of simulating flexible molecules with CBMC as one of them. Simulations of well-known molecules, such as n-octane and 1,2-dichloroethane in vacuum and in solution, are presented to validate the new implementations compared with MD simulations, experimental data, and other theoretical results. The efficiency of the conformational sampling was analyzed using the acceptance rates of different alkanes: n-octane, neopentane, and 4-ethylheptane. Furthermore, a very complex molecule, boron subphtalocyanine, was simulated in vacuum and in aqueous solution showing the versatility of the new implementation. We show that the CBMC is a very good method to perform conformation sampling of complex moderately sized molecules (up to 150 atoms) in solution following the Boltzmann thermodynamic equilibrium distribution.

Polar Sulfone-Functionalized Oxygen-Rich Metal-Organic Frameworks for Highly Selective CO2 Capture and Sensitive Detection of Acetylacetone at ppb Level.

A rational combination of an oxygen-rich pyridyl substituted tetrapodal ligand, tetrakis(4-pyridyloxymethylene)methane (TPOM), and a polar sulfone-functionalized conjugated bent dicarboxylate linker, dibenzothiophene-5,5'-dioxide-3,7-dicarboxylic acid (H2(3,7-DBTDC)), with d10 metal centers, Zn(II) and Cd(II), has led to the construction of two new three-dimensional (3D) metal-organic frameworks,{[Zn2(TPOM)(3,7-DBTDC)2]·7H2O·DMA}n (1) and {[Cd2(TPOM)(3,7-DBTDC)2]·6H2O·3DMF}n (2). Single-crystal X-ray analysis indicates that 1 is a 3D framework with a dinuclear repeating unit having two different Zn(II) centers (tetrahedral and square pyramidal) and 2 is a 3D framework comprised of a dinuclear repeating unit with one crystallographically independent distorted pentagonal bipyramidal Cd(II) coordinated to chelating/bridging carboxylates and nitrogen atoms of the TPOM ligand. In both cases, the pores are aligned with oxygen atoms of the TPOM ligand and decorated with polar sulfone moieties. On the basis of the stability established by thermogravimetric analysis and powder X-ray diffraction (PXRD) and the presence of large solvent accessible voids (25.4% for 1 and 40.6% for 2), gas sorption studies of different gases (N2, CO2, and CH4) and water vapor have been explored for both 1 and 2. The CO2 sorption isotherm depicts type I isotherm with an uptake of 93.6 cm3 g-1 (for 1) and 100.6 cm3 g-1 (for 2) at 195 K. Additionally, sorption of CO2 is highly selective over that of N2 and CH4 for both 1 and 2 due to the strong quadrupolar interactions between sulfone moieties and CO2 molecules. Configurational bias Monte Carlo (CBMC) molecular simulation has further justified the highly selective CO2 capture. On the other hand, the luminescence nature of 1 and 2 has been employed for highly selective detection of acetylacetone in aqueous methanol with a limit of 59 ppb in 1 and 66 ppb in 2, which are among the best reported values so far in the literature. The Stern-Volmer plots, spectral overlap, density functional theory calculations, CBMC simulation, and time-resolved lifetime measurements have been utilized for an extensive mechanistic study. The exclusive selectivity for acetylacetone in 1 and 2 have been confirmed by competitive selectivity test. Both exhibited good recyclability and stability after sensing experiments analyzed by fluorescence, PXRD, and field emission scanning electron microscopy studies.

Efficient configurational-bias Monte-Carlo simulations of chain molecules with "swarms" of trial configurations.

The pruned-enriched Rosenbluth method (PERM) is a popular and powerful Monte-Carlo technique for sampling flexible chain polymers of substantial length. In its original form, however, the method cannot be applied in Markov-chain Monte-Carlo schemes, which has rendered PERM unsuited for systems that consist of many chains. The current work builds on the configurational-bias Monte-Carlo (CBMC) method. The growth of a large set of trial configurations in each move is governed by simultaneous pruning and enrichment events, which tend to replace configurations with a low statistical weight by clones of stronger configurations. In simulations of dense brushes of flexible chains, a gain in efficiency of at least three orders of magnitude is observed with respect to CBMC and one order of magnitude with respect to recoil-growth approaches. Moreover, meaningful statistics can be collected from all trial configurations through the so-called "waste-recycling" Monte Carlo scheme.

Configurational-Bias Monte Carlo Back-Mapping Algorithm for Efficient and Rapid Conversion of Coarse-Grained Water Structures into Atomistic Models

Coarse-grained molecular dynamics (MD) simulations represent a powerful approach to simulate longer time scale and larger length scale phenomena than those accessible to all-atom models. The gain in efficiency, however, comes at the cost of atomistic details. The reverse transformation, also known as back mapping, of coarse-grained beads into their atomistic constituents represents a major challenge. Most existing approaches are limited to specific molecules or specific force fields and often rely on running a long-time atomistic MD of the back-mapped configuration to arrive at an optimal solution. Such approaches are problematic when dealing with systems with high diffusion barriers. Here, we introduce a new extension of the configurational-bias Monte Carlo (CBMC) algorithm, which we term the crystalline-configurational-bias Monte Carlo (C-CBMC) algorithm, which allows rapid and efficient conversion of a coarse-grained model back into its atomistic representation. Although the method is generic, we use a coarse-grained water model as a representative example and demonstrate the back mapping or reverse transformation for model systems ranging from the ice-liquid water interface to amorphous and crystalline ice configurations. A series of simulations using the TIP4P/Ice model are performed to compare the new CBMC method to several other standard Monte Carlo and molecular dynamics-based back-mapping techniques. In all of the cases, the C-CBMC algorithm is able to find optimal hydrogen-bonded configuration many thousand evaluations/steps sooner than the other methods compared within this paper. For crystalline ice structures, such as a hexagonal, cubic, and cubic-hexagonal stacking disorder structures, the C-CBMC was able to find structures that were between 0.05 and 0.1 eV/water molecule lower in energy than the ground-state energies predicted by the other methods. Detailed analysis of the atomistic structures shows a significantly better global hydrogen positioning when contrasted with the existing simpler back-mapping methods. The errors in the radial distribution functions (RDFs) of back-mapped configuration relative to reference configuration for the C-CBMC, MD, and MC were found to be 6.9, 8.7, and 12.9, respectively, for the hexagonal system. For the cubic system, the relative errors of the RDFs for the C-CBMC, MD, and MC were found to be 18.2, 34.6, and 39.0, respectively. Our results demonstrate the efficiency and efficacy of our new back-mapping approach, especially for crystalline systems where simple force-field-based relaxations have a tendency to get trapped in local minima.

Investigating the non-idealities in adsorption of CO2-bearing mixtures in cation-exchanged zeolites

• Non-idealities are caused by inhomogeneous distribution of adsorbates. • The extent of thermodynamic non-idealities also depend on the Si/Al ratio. • Models for activity coefficients must include the influence of the adsorption potential. • Non-ideal adsorption may influence separation performance of fixed bed adsorbers. Cation-exchanged zeolites have significant potential for capture of CO 2 from a wide variety of mixtures containing N 2 , H 2 , alkanes and alkenes. The strong coulombic interactions of CO 2 with extra-framework cations result in strong binding and selective capture. Published experimental data on mixture adsorption indicate that the Ideal Adsorbed Solution Theory (IAST) fails to provide accurate estimates of mixture adsorption equilibrium. The reasons for the quantitative failure of IAST estimates are investigated with the aid of Configurational-Bias Monte Carlo (CBMC) simulations of mixture adsorption. Computational snapshots indicate that the failure of the IAST is traceable to inhomogeneous distribution of adsorbates within the zeolite framework.

Understanding Brønsted-Acid Catalyzed Monomolecular Reactions of Alkanes in Zeolite Pores by Combining Insights from Experiment and Theory.

Acidic zeolites are effective catalysts for the cracking of large hydrocarbon molecules into lower molecular weight products required for transportation fuels. However, the ways in which the zeolite structure affects the catalytic activity at Brønsted protons are not fully understood. One way to characterize the influence of the zeolite structure on the catalysis is to study alkane cracking and dehydrogenation at very low conversion, conditions for which the kinetics are well defined. To understand the effects of zeolite structure on the measured rate coefficient (kapp ), it is necessary to identify the equilibrium constant for adsorption into the reactant state (Kads-H+ ) and the intrinsic rate coefficient of the reaction (kint ) at reaction temperatures, since kapp is proportional to the product of Kads-H+ and kint . We show that Kads-H+ cannot be calculated from experimental adsorption data collected near ambient temperature, but can, however, be estimated accurately from configurational-bias Monte Carlo (CBMC) simulations. Using monomolecular cracking and dehydrogenation of C3 -C6 alkanes as an example, we review recent efforts aimed at elucidating the influence of the acid site location and the zeolite framework structure on the observed values of kapp and its components, Kads-H+ and kint .

Methodologies for screening and selection of crystalline microporous materials in mixture separations

Abstract Ordered crystalline microporous materials such as zeolites, metal-organic frameworks (MOFs), and zeolitic imidazolate frameworks (ZIFs) offer considerable potential for separating a wide variety of mixtures. There are basically two different separation technologies that can be employed: (1) pressure swing adsorption (PSA) unit with a fixed bed of adsorbent particles, and (2) membrane device, wherein the mixture is allowed to permeate through thin micro-porous crystalline layers. The fundamental physico-chemical principles underlying the separations in these two devices are fundamentally different. In fixed bed adsorbers, diffusional effects are usually undesirable because these tend to produce distended breakthroughs and diminished productivities. For membrane separations, both intra-crystalline diffusion and mixture adsorption equilibrium determine permeation selectivities, and diffusion selectivities are often the primary drivers for separations. Using Configurational-Bias Monte Carlo (CBMC) simulations of mixture adsorption equilibrium, and Molecular Dynamics (MD) simulations of guest diffusivities in a wide number of guest/host combinations, we demonstrate that adsorption and diffusion do not, in general, proceed hand-in-hand. Strong adsorption often implies lowered mobility. Consequently, the best material for use in fixed bed adsorbers does not always coincide with the ideal choice for use as thin layers in membrane devices. Methodologies for screening microporous materials for use in fixed-bed units and membrane devices are discussed using a large number of examples of industrially important separations.

Assessment and Optimization of Configurational-Bias Monte Carlo Particle Swap Strategies for Simulations of Water in the Gibbs Ensemble.

Particle swap moves between phases are usually the rate-limiting step for Gibbs ensemble Monte Carlo (GEMC) simulations of fluid phase equilibria at low reduced temperatures because the acceptance probabilities for these moves can become very low for molecules with articulated architecture and/or highly directional interactions. The configurational-bias Monte Carlo (CBMC) technique can greatly increase the acceptance probabilities, but the efficiency of the CBMC algorithm is influenced by multiple parameters. In this work we assess the performance of different CBMC strategies for GEMC simulations using the SPC/E and TIP4P water models at 283, 343, and 473 K, demonstrate that much higher acceptance probabilities can be achieved than previously reported in the literature, and make recommendations for CBMC strategies leading to optimal efficiency.

Structure and Phase Behavior of Mixed Self-Assembled Alkanethiolate Monolayers on Gold Nanoparticles: A Monte Carlo Study.

Configurational-bias Monte Carlo (CBMC) simulations are carried out to investigate the structure and phase behavior of self-assembled monolayers consisting of equimolar alkanethiolate mixtures chemisorbed on the surface of gold nanoparticles. The simulations probe the effects of variations in the chain length, nanoparticle curvature, and exchange of alkanethiolates between nanoparticles. The TraPPE-UA force field is used for the alkanethiolates, whereas the nanoparticle is represented by gold atoms placed on the surface of a sphere. CBMC identity exchange moves are used to enhance sampling of the spatial distribution of the different ligands and to ensure that thermodynamic equilibrium is reached. At a temperature of 298 K, mixtures differing in length by four methylene units exhibit some degree of local segregation. In contrast, the hexanethiolate/tetradecanethiolate mixture yields Janus-like arrangement when the ligands are confined to a single nanoparticle but global demixing when the ligands are allowed to distribute between two nanoparticles.

RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials

A new software package, RASPA, for simulating adsorption and diffusion of molecules in flexible nanoporous materials is presented. The code implements the latest state-of-the-art algorithms for molecular dynamics and Monte Carlo (MC) in various ensembles including symplectic/measure-preserving integrators, Ewald summation, configurational-bias MC, continuous fractional component MC, reactive MC and Baker's minimisation. We show example applications of RASPA in computing coexistence properties, adsorption isotherms for single and multiple components, self- and collective diffusivities, reaction systems and visualisation. The software is released under the GNU General Public License.