Vapor–liquid equilibria of mixtures containing nitrogen, oxygen, carbon dioxide, and ethane

An amine decorated MOF for direct capture of CO2 from ambient air

A Zn(II)-based metal-organic framework (MOF) was synthesized by the self-assembly of the dicarboxylate ligand terephthalic acid (TPA), 2-aminoterephthalic acid (NH2-TPA) and N-donor auxiliary ligand 1,4-bis(4-pyridinylmethyl)piperazine (bpmp) using Zn(NO3)2·6H2O under hydrothermal conditions. {[Zn(TPA)0.5(NH2TPA)0.5(bpmp)]·DMF·7H2O}n (framework 1) has an sra topology with a BET surface area of 756 m2 g-1. The microporous nature of the framework is apparent from the significant CO2 adsorption capacities observed at various temperatures: 57 cc g-1 at 283 K, 46 cc g-1 at 293 K, 37 cc g-1 at 303 K, and 30 cc g-1 at 313 K. The considerable CO2 adsorption may be caused by the existence of free carboxylate and amine substituents that interact with the gas molecules and micropores. At room temperature, the activated MOF readily converts CO2 into cyclic carbonates when a suspension of the MOF is bubbled with ambient air and different epoxides under solvent-free conditions. The amine groups located within the pores of the MOF interact with CO2 molecules, enhancing their sorption and conversion to cyclic carbonates. However, due to interpenetration within framework 1, only smaller size epoxides can be accommodated and converted to cyclic carbonates in good yields. Additionally, the effectiveness of the catalyst is further confirmed by the positive outcomes obtained from the hot filtration control test. Grand canonical Monte Carlo (GCMC) molecular simulations were utilized to gain a better understanding of molecular interactions. GCMC results are in line with the experiments. The substantial adsorption of CO2 can be ascribed to the strong intermolecular interactions that occur between the amine groups within the framework and the CO2 molecules.

Solvent-derived defects suppress adsorption in MOF-74

Defects in metal-organic frameworks (MOFs) have great impact on their nano-scale structure and physiochemical properties. However, isolated defects are easily concealed when the frameworks are interrogated by typical characterization methods. In this work, we unveil the presence of solvent-derived formate defects in MOF-74, an important class of MOFs with open metal sites. With multi-dimensional solid-state nuclear magnetic resonance (NMR) investigations, we uncover the ligand substitution role of formate and its chemical origin from decomposed N,N-dimethylformamide (DMF) solvent. The placement and coordination structure of formate defects are determined by ¹³C NMR and density functional theory (DFT) calculations. The extra metal-oxygen bonds with formates partially eliminate open metal sites and lead to a quantitative decrease of N₂ and CO₂ adsorption with respect to the defect concentration. In-situ NMR analysis and molecular simulations of CO₂ dynamics elaborate the adsorption mechanisms in defective MOF-74. Our study establishes comprehensive strategies to search, elucidate and manipulate defects in MOFs.

Combining Computational Screening and Machine Learning to Predict Metal-Organic Framework Adsorbents and Membranes for Removing CH4 or H2 from Air

Separating and capturing small amounts of CH₄ or H₂ from a mixture of gases, such as coal mine spent air, at a large scale remains a great challenge. We used large-scale computational screening and machine learning (ML) to simulate and explore the adsorption, diffusion, and permeation properties of 6013 computation-ready experimental metal-organic framework (MOF) adsorbents and MOF membranes (MOFMs) for capturing clean energy gases (CH₄ and H₂) in air. First, we modeled the relationships between the adsorption and the MOF membrane performance indicators and their characteristic descriptors. Among three ML algorithms, the random forest was found to have the best prediction efficiency for two systems (CH₄/(O₂ + N₂) and H₂/(O₂ + N₂)). Then, the algorithm was further applied to quantitatively analyze the relative importance values of seven MOF descriptors for five performance metrics of the two systems. Furthermore, the 20 best MOFs were also selected. Finally, the commonalities between the high-performance MOFs were analyzed, leading to three types of material design principles: tuned topology, alternative metal nodes, and organic linkers. As a result, this study provides microscopic insights into the capture of trace amounts of CH₄ or H₂ from air for applications involving coal mine spent air and hydrogen leakage.

Prediction of Contact Angles and Density Profiles of Sessile Droplets Using Classical Density Functional Theory Based on the PCP-SAFT Equation of State

This study demonstrates the capability of the density functional theory (DFT) formalism to predict contact angles and density profiles of model fluids and of real substances in good quantitative agreement with molecular simulations and experimental data. The DFT problem is written in cylindrical coordinates, and the solid-fluid interactions are defined as external potentials toward the fluid phase. Monte Carlo (MC) molecular simulations are conducted in order to assess the density profiles resulting from the Helmholtz energy functional used in the DFT formalism. Good quantitative agreement between DFT predictions and MC results for Lennard-Jones and ethane nanodroplets is observed, both for density profiles and for contact angles. That comparison suggests, first, that the Helmholtz energy functional proposed in a previous study [ Sauer , E. ; Gross , J. Ind. Eng. Chem. Res. 56 , 2017 , 4119 - 4135 ] is suitable for three-phase contact lines and, second, that Lagrange multipliers can be used to constrain the number of molecules, similar to a canonical ensemble. Experiments of sessile droplets on solid surfaces are performed to assess whether a real solid with its microscopic roughness can be described through a simple model potential. Comparison of DFT results to experimental data is done for a Teflon surface because Teflon can be regarded as a substrate exhibiting only attractive interactions of van der Waals type. It is shown that the real solid can be described as a perfectly planar solid with effective solvent-to-solid interactions, defined through a single adjustable parameter for the solid. Subsequent predictions for the contact angle of eight solvents, including polar components such as water, are found in very good agreement to experimental data using simple Berthelot-Lorentz combining rules. For the eight investigated solvents, we find mean absolute deviations of 3.77°.

Molecular simulation of the thermophysical properties and phase behaviour of impure CO2 relevant to CCS

Impurities from the CCS chain can greatly influence the physical properties of CO₂. This has important design, safety and cost implications for the compression, transport and storage of CO₂. There is an urgent need to understand and predict the properties of impure CO₂ to assist with CCS implementation. However, CCS presents demanding modelling requirements. A suitable model must both accurately and robustly predict CO₂ phase behaviour over a wide range of temperatures and pressures, and maintain that predictive power for CO₂ mixtures with numerous, mutually interacting chemical species. A promising technique to address this task is molecular simulation. It offers a molecular approach, with foundations in firmly established physical principles, along with the potential to predict the wide range of physical properties required for CCS. The quality of predictions from molecular simulation depends on accurate force-fields to describe the interactions between CO₂ and other molecules. Unfortunately, there is currently no universally applicable method to obtain force-fields suitable for molecular simulation. In this paper we present two methods of obtaining force-fields: the first being semi-empirical and the second using ab initio quantum-chemical calculations. In the first approach we optimise the impurity force-field against measurements of the phase and pressure-volume behaviour of CO₂ binary mixtures with N₂, O₂, Ar and H₂. A gradient-free optimiser allows us to use the simulation itself as the underlying model. This leads to accurate and robust predictions under conditions relevant to CCS. In the second approach we use quantum-chemical calculations to produce ab initio evaluations of the interactions between CO₂ and relevant impurities, taking N₂ as an exemplar. We use a modest number of these calculations to train a machine-learning algorithm, known as a Gaussian process, to describe these data. The resulting model is then able to accurately predict a much broader set of ab initio force-field calculations at comparatively low numerical cost. Although our method is not yet ready to be implemented in a molecular simulation, we outline the necessary steps here. Such simulations have the potential to deliver first-principles simulation of the thermodynamic properties of impure CO₂, without fitting to experimental data.

Study of structural and transport properties of argon, krypton, and their binary mixtures at different temperatures

Molecular dynamics simulation of argon, krypton, and their binary mixtures were performed at different temperatures and constant pressure (P = 1.013 bar) using GROMACS - Groningen Machine for Chemical Simulations. The gases are modeled by Lennard-Jones pair potential, with parameters taken from the literature. The study of radial distribution functions (RDFs) shows a single peak which indicates that there is no packing effect in gaseous state for argon, krypton, and their binary mixtures. The self-diffusion coefficients of argon and krypton is determined by using mean-square displacement(MSD) method and the mutual diffusion coefficients of binary mixtures are determined using Darken's relation. The values of simulated diffusion coefficients are compared with their corresponding theoretical values, numerical estimation, and experimental data. A good agreement between these sets of data is found. The diffusion coefficients obey Arrhenius behavior to a good extent for both pure components and binary mixtures. The values of simulated diffusion coefficient are used to estimate viscosities and thermal conductivities which agree with theoretical values, numerical estimation, and experimental data within 10 %. These results support that the LJ potential is sufficient for description of molecular interactions in argon and krypton.

Fluid phase interface properties of acetone, oxygen, nitrogen and their binary mixtures by molecular simulation

Vapor–liquid equilibria (VLE) of the pure substances acetone, oxygen and nitrogen as well as their binary mixtures are studied by molecular dynamics (MD) simulation with a direct approach.

ls1 mardyn: The Massively Parallel Molecular Dynamics Code for Large Systems

The molecular dynamics simulation code ls1 mardyn is presented. It is a highly scalable code, optimized for massively parallel execution on supercomputing architectures and currently holds the world record for the largest molecular simulation with over four trillion particles. It enables the application of pair potentials to length and time scales that were previously out of scope for molecular dynamics simulation. With an efficient dynamic load balancing scheme, it delivers high scalability even for challenging heterogeneous configurations. Presently, multicenter rigid potential models based on Lennard-Jones sites, point charges, and higher-order polarities are supported. Due to its modular design, ls1 mardyn can be extended to new physical models, methods, and algorithms, allowing future users to tailor it to suit their respective needs. Possible applications include scenarios with complex geometries, such as fluids at interfaces, as well as nonequilibrium molecular dynamics simulation of heat and mass transfer.

Fluorinated and nanoporous graphene materials as sorbents for gas separations

The physisorption of gases on surfaces depends on the electrostatic and dispersion interactions with adsorbates. The former can be tuned by introducing charge variations in the material, and the latter can be tuned by chemical substitution. Using atomistic Monte Carlo calculations, the Henry's law constants, and isosteric heats of adsorption of CH(4), CO(2), N(2), O(2), H(2)S, SO(2), and H(2)O on graphene, two-dimensional polyphenylene (2D-PP), fluorographene, and fluoro(2D-PP) surfaces are used to demonstrate the tunability of these two types of interaction. With the exception of H(2)O, fluorination and nanoporosity-induced charge variations reduce the binding of the adsorbates. Gas separations relevant for CO(2) sequestration, biogas upgrading, SO(2) pollution control, and air dehumidification are considered, and in most cases, the nanoporosity and fluorination reduce the selectivity of adsorption. The exceptions are separations involving adsorption of H(2)O and the SO(2)/N(2) separation, where the large dipole moments of the adsorbed species leads to enhanced binding relative to the nonpolar species.

Monte Carlo simulations of high-pressure phase equilibria of CO2-H2O mixtures

Histogram-reweighting grand canonical Monte Carlo simulations were used to obtain the phase behavior of CO(2)-H(2)O mixtures over a broad temperature and pressure range (50 °C ≤ T ≤ 350 °C, 0 ≤ P ≤ 1000 bar). We performed a comprehensive test of several existing water (SPC, TIP4P, TIP4P2005, and exponential-6) and carbon dioxide (EPM2, TraPPE, and exponential-6) models using conventional Lorentz-Berthelot combining rules for the unlike-pair parameters. None of the models we studied reproduce adequately experimental data over the entire temperature and pressure range, but critical assessments were made on the range of T and P where particular model pairs perform better. Away from the critical region (T ≤ 250 °C), the exponential-6 model combination yields the best predictions for the CO(2)-rich phase, whereas the TraPPE/TIP4P2005 model combination provides the most accurate coexistence composition and pressure for the H(2)O-rich phase. Near the critical region (250 °C < T ≤ 350 °C), the critical points are not accurately estimated by any of the models studied, but the exponential-6 models are able to qualitatively capture the critical loci and the shape of the phase envelopes. Local improvements can be achieved at specific temperatures by introducing modification factors to the Lorentz-Berthelot combining rules, but the modified combining rule is still not able to achieve global improvements over the entire temperature and pressure range. Our work points to the challenge and importance of improving current atomistic models so as to accurately predict the phase behavior of this important binary mixture.

Hydrogen Bonding of Methanol in Supercritical CO2: Comparison between 1H NMR Spectroscopic Data and Molecular Simulation Results

Molecular dynamics simulation results on hydrogen bonding in mixtures of methanol with CO2 at supercritical, liquid-like conditions are compared to 1H NMR spectroscopic data that have recently become available. The molecular models are parametrized using vapor-liquid equilibrium data only, which they reliably describe. A new molecular model for methanol of Lennard-Jones plus point charge type is presented. This molecular methanol model is investigated in terms of its capability to yield hydrogen-bonding statistics. Simple assumptions are made regarding the assignment of NMR chemical shifts to the different types of hydrogen-bonded species. Only two state-independent parameters are fitted to the large NMR data set on the basis of hydrogen-bonding statistics from molecular simulations. Excellent agreement between the molecular simulation results and the NMR data is found. This shows that the molecular models of the simple type studied here cannot only describe thermodynamic properties but also structural effects of hydrogen bonding in solutions.

An advanced Gibbs-Duhem integration method: Theory and applications

The conventional Gibbs-Duhem integration method is very convenient for the prediction of phase equilibria of both pure components and mixtures. However, it turns out to be inefficient. The method requires a number of lengthy simulations to predict the state conditions at which phase coexistence occurs. This number is not known from the outset of the numerical integration process. Furthermore, the molecular configurations generated during the simulations are merely used to predict the coexistence condition and not the liquid- and vapor-phase densities and mole fractions at coexistence. In this publication, an advanced Gibbs-Duhem integration method is presented that overcomes above-mentioned disadvantage and inefficiency. The advanced method is a combination of Gibbs-Duhem integration and multiple-histogram reweighting. Application of multiple-histogram reweighting enables the substitution of the unknown number of simulations by a fixed and predetermined number. The advanced method has a retroactive nature; a current simulation improves the predictions of previously computed coexistence points as well. The advanced Gibbs-Duhem integration method has been applied for the prediction of vapor-liquid equilibria of a number of binary mixtures. The method turned out to be very convenient, much faster than the conventional method, and provided smooth simulation results. As the employed force fields perfectly predict pure-component vapor-liquid equilibria, the binary simulations were very well suitable for testing the performance of different sets of combining rules. Employing Lorentz-Hudson-McCoubrey combining rules for interactions between unlike molecules, as opposed to Lorentz-Berthelot combining rules for all interactions, considerably improved the agreement between experimental and simulated data.

Molecular Modeling of Phase Behavior and Microstructure of Acetone−Chloroform−Methanol Binary Mixtures

Force fields based on a Lennard-Jones (LJ) 12-6 plus point charge functional form are developed for acetone and chloroform specifically to reproduce the minimum pressure azeotropy found experimentally in this system. Point charges are determined from a CHELPG population analysis performed on an acetone-chloroform dimer. The required electrostatic surface for this dimer is determined from ab initio calculations performed with MP2 theory and the 6-31g++(3df,3pd) basis set. LJ parameters are then optimized such that the liquid-vapor coexistence curve, critical parameters, and vapor pressures are well reproduced by simulation. Histogram-reweighting Monte Carlo simulations in the grand canonical ensemble are used to determine the phase diagrams for the binary mixtures acetone-chloroform, acetone-methanol, and chloroform-methanol. The force fields developed in this work reproduce the minimum pressure azeotrope in the acetone-chloroform mixture found in experiment. The predicted azeotropic composition of x(CHCl3) = 0.77 is in fair agreement with the experimental value of x(CHCl3)expt = 0.64. The new force fields were also found to provide improved predictions of the pressure-composition behavior of acetone-methanol and chloroform-methanol when compared to other force fields commonly used for vapor-liquid equilibria calculations. NPT simulations were conducted at 300 K and 1 bar for equimolar mixtures of acetone-chloroform, acetone-methanol, and methanol-chloroform. Analysis of the microstructure reveals significant hydrogen bonding occurring between acetone and chloroform. Limited interspecies hydrogen bonding was found in the acetone-methanol or chloroform-methanol mixtures.