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

Isotope-selective pore opening in a flexible metal-organic framework

Flexible metal-organic frameworks that show reversible guest-induced phase transitions between closed and open pore phases have enormous potential for highly selective, energy-efficient gas separations. Here, we present the gate-opening process of DUT-8(Ni) that selectively responds to D₂, whereas no response is observed for H₂ and HD. In situ neutron diffraction directly reveals this pressure-dependent phase transition. Low-temperature thermal desorption spectroscopy measurements indicate an outstanding D₂-over-H₂ selectivity of 11.6 at 23.3 K, with high D₂ uptake. First-principles calculations coupled with statistical thermodynamics predict the isotope-selective gate opening, rationalized by pronounced nuclear quantum effects. Simulations suggest DUT-8(Ni) to remain closed in the presence of HT, while it also opens for DT and T₂, demonstrating gate opening as a highly effective approach for isotopolog separation.

Putting Forward NUS-8-CO2H/PIM-1 as a Mixed Matrix Membrane for CO2 Capture

Mixed matrix membranes (MMMs) composed of NUS-8 metal-organic framework (MOF) nanosheets dispersed into a polymer of intrinsic microporosity 1 (PIM-1) polymer matrix are known to be promising candidates for CO₂/N₂ separation because of a solubility-driven separation mechanism. In this work, we predict that a chemical functionalization of the organic linker of NUS-8 by a CO₂-philic function confers an even better separation performance to the resulting MMM. Our simulations revealed that the NUS-8-CO₂H/PIM-1 composite exhibits a 3-fold increase in CO₂/N₂ selectivity versus the NUS-8/PIM-1 analogue while achieving a high CO₂ permeability (6700 barrer). We demonstrated that this improved level of performance is due to an increase both in the total MOF/polymer interfacial pore volume and in the CO₂-affinity due to the chemical functionalization. These results suggest that an appropriate choice of chemical functionalization of a MOF is a promising strategy to improve gas separation performances for MMM composites that exhibit a solubility-driven separation mechanism.

Evaluation of Gas Adsorption in Nanoporous Shale by Simplified Local Density Model Integrated with Pore Structure and Pore Size Distribution

Simplified local density (SLD) model has been widely used to describe the gas adsorption behaviors in porous media. However, the slit pore geometry and constant pore width associated with the SLD model may fail to represent the heterogeneous pore network structure in shale. In this study, a new method to integrate the SLD model with the slit and cylindrical pore structures as well as the pore size distribution (PSD) is proposed and validated by the grand canonical Monte Carlo (GCMC) simulations and the experimentally measured adsorption of methane on shale with complex pore network. Comparison results show that reasonably good agreement is achieved between the SLD model and GCMC simulations for both the gas adsorption isotherms and discrete-density profiles in multiwalled carbon nanoslit and nanotube. The corresponding average absolute percentage deviations (% AADs) are below 0.3 and 9.3 for gas adsorption isotherm and discrete-density profile, respectively. In addition, the SLD model coupled with the PSD of slit and cylindrical pores ranging from micro- to macropores properly characterizes the measured excess adsorption of methane on Wolfcamp shale core sample with % AADs between 1.7 and 3.6. It is found that when the pore volume is fixed, the gas adsorption isotherm and gas density profile are heavily dependent on the pore geometry and pore size. Furthermore, integrating the PSD into the SLD model can guarantee the valid identification of the adsorbed- and free-gas regions in flow channels with different sizes based on the gas density profiles. The findings of this study shed light on the effects of pore structure on gas adsorption in nanopores and enable us to precisely evaluate and predict the gas adsorption behaviors in slit and cylindrical pores over a wide range of pore sizes.

Anion Regulates Topological Porous Coordination Polymers into the Acetylene Trap

The development of efficient porous absorbents with high uptake and selectivity remains a great challenge, especially for the recovery of acetylene (C₂H₂) from its carbon dioxide (CO₂)-containing mixtures. Here, we propose and report an anion-planting strategy for regulating the scu topological porous coordination polymers (PCPs) into the C₂H₂ trap. The three electronegative anions SiF₆^2-, TiF₆^2-, and ZrF₆^2-, in addition to the ligand of 3,5-di(1H-imidazol-1-yl)benzoic acid (HL) and Cu²⁺ ion, were employed to construct highly porous PCPs (NTU-60, NTU-61, and NTU-62) with varied window aperture. Especially, due to a matching distance (d_F-F) of 5.7 Å along the c-axis, the limited space that can be assigned as a single C₂H₂ trap enables NTU-61 to show optimal ability for C₂H₂ (van der Waals (vdW) parameters of the two H atoms: ∼5.72 Å) recognition, validated by Grand Canonical Monte Carlo (GCMC) calculations and Raman spectra. These characteristics allow the NTU-series to show higher C₂H₂ uptake, as well as excellent C₂H₂/CO₂ separation performance under dynamic conditions. The molecular insight and strategy here not only permit balanced adsorption and separation in a single domain but also exhibit an opportunity to develop advanced adsorbents in nearly all frameworks with lattice or coordinated ions, which may act as the platforms for various selective guest trappings with on-demand time and/or spatial resolution.

Three-Dimensional Triptycene-Functionalized Covalent Organic Frameworks with hea Net for Hydrogen Adsorption

Owing to the finite building blocks and difficulty in structural identification, it remains a tremendous challenge to elaborately design and synthesize three-dimensional covalent organic frameworks (3D COFs) with predetermined topologies. Herein, we report the first two cases of 3D COFs with the non-interpenetrated hea net, termed JUC-596 and JUC-597, by using the combination of tetrahedral and triangular prism building units. Due to the presence of triptycene functional groups and fluorine atoms, JUC-596 exhibits an exceptional performance in the H₂ adsorption up to 305 cm³  g^-1 (or 2.72 wt%) at 77 K and 1 bar, which is higher than previous benchmarks from porous organic materials reported so far. Furthermore, the strong interaction between H₂ and COF materials is verified through the DFT theoretical calculations. This work represents a captivating example of rational design of functional COFs based on a reticular chemistry guide and demonstrates its promising application in clean energy storage.

Computational Screening of Metal-Organic Frameworks for Ethylene Purification from Ethane/Ethylene/Acetylene Mixture

Identification of high-performing sorbent materials is the key step in developing energy-efficient adsorptive separation processes for ethylene production. In this work, a computational screening of metal-organic frameworks (MOFs) for the purification of ethylene from the ternary ethane/ethylene/acetylene mixture under thermodynamic equilibrium conditions is conducted. Modified evaluation metrics are proposed for an efficient description of the performance of MOFs for the ternary mixture separation. Two different separation schemes are proposed and potential MOF adsorbents are identified accordingly. Finally, the relationships between the MOF structural characteristics and its adsorption properties are discussed, which can provide valuable information for optimal MOF design.

CF4 Capture and Separation of CF4-SF6 and CF4-N2 Fluid Mixtures Using Selected Carbon Nanoporous Materials and Metal-Organic Frameworks: A Computational Study

The adsorption of pure fluid carbon tetrafluoride and the separation of CF₄-SF₆ and CF₄-N₂ fluid mixtures using representative nanoporous materials have been investigated by employing Monte Carlo and molecular dynamics simulation techniques. The selected materials under study were the three-dimensional carbon nanotube networks, pillared graphene using carbon nanotube pillars, and the SIFSIX-2-Cu metal-organic framework. The selection of these materials was based on their previously reported efficiency to separate fluid SF₆-N₂ mixtures. The pressure dependence of the thermodynamic and kinetic separation selectivity for the CF₄-SF₆ and CF₄-N₂ fluid mixtures has therefore been investigated, to provide deeper insights into the molecular scale phenomena taking place in the investigated nanoporous materials. The results obtained have revealed that under near-ambient pressure conditions, the carbon-based nanoporous materials exhibit a higher gravimetric fluid uptake and thermodynamic separation selectivity. The SIFSIX-2-Cu material exhibits a slightly higher kinetic selectivity at ambient and high pressures.

Can Charge-Modulated Metal-Organic Frameworks Achieve High-Performance CO2 Capture and Separation over H2 , N2 , and CH4 ?

CO₂ capture and separation by using charge-modulated adsorbent materials is a promising strategy to reduce CO₂ emissions. Herein, three TM-HAB (TM=Co, Ni, and Cu; HAB=hexa-aminobenzene) metal-organic frameworks (MOFs) were evaluated as charge-modulated CO₂ capture and separation materials by using density functional theory and grand canonical Monte Carlo simulations. The results showed that each TM-HAB presented a high electrical conductivity and structural stability when injecting charges. The CO₂ adsorption energy increased from 0.211 to 2.091 eV on Co-HAB, 0.262 to 2.119 eV on Ni-HAB, and 0.904 to 2.803 eV on Cu-HAB, respectively, with the increase in charge state from 0.0 to 3.0 e^- . Co-HAB and Ni-HAB were better charge-modulated CO₂ capture materials with less structure deformation based on energy decomposition analyses. The kinetic process demonstrated that considerably low energy consumptions of 0.911 and 1.589 GJ ton^-1 CO₂ were observed for a complete adsorption-desorption cycle on Co-HAB and Ni-HAB. All charged MOFs, especially Co-HAB and Ni-HAB, exhibited higher CO₂ adsorption energies and adsorption capacities than those of H₂ , N₂ , and CH₄ , thereby exhibiting high CO₂ selectivities. Interaction analysis confirmed that the injecting charges had a more pronounced enhancement in the coulombic interactions between CO₂ and MOFs. The results of this work highlight Co-HAB and Ni-HAB as promising charge-modulated CO₂ capture and separation materials with controllable CO₂ capture, high selectivity, and low energy consumption.

Molecular Simulation on Permeation Behavior of CH4/CO2/H2S Mixture Gas in PVDF at Service Conditions

Reinforced thermoplastic composite pipes (RTPs) have been widely used for oil and gas gathering and transportation. Polyvinylidene fluoride (PVDF) has the greatest potential as a thermoplastic liner of RTPs due to its excellent thermal and mechanical properties. However, permeation of gases is inevitable in the thermoplastic liner, which may lead to blister failure of the liner and damage the safe operation of the RTPs. In order to clarify the permeation behavior and obtain the permeation mechanism of the mixture gas (CH4/CO2/H2S) in PVDF at the normal service conditions, molecular simulations were carried out by combining the Grand Canonical Monte Carlo (GCMC) method and the Molecular Dynamics (MD) method. The simulated results showed that the solubility coefficients of gases increased with the decrease in temperature and the increase in pressure. The adsorption isotherms of all gases were consistent with the Langmuir model. The order of the adsorption concentration for different gases was H2S > CO2> CH4. The isosteric heats of gases at all the actual service conditions were much less than 42 kJ/mol, which indicated that the adsorption for all the gases belonged to the physical adsorption. Both of the diffusion and permeation coefficients increased with the increase in temperature and pressure. The diffusion belonged to Einstein diffusion and the diffusion coefficients of each gas followed the order of CH4 > CO2 > H2S. During the permeation process, the adsorption of gas molecules in PVDF exhibited selective aggregation, and most of them were adsorbed in the low potential energy region of PVDF cell. The mixed-gas molecules vibrated within the hole of PVDF at relatively low temperature and pressure. As the temperature and pressure increase, the gas molecules jumped into the neighboring holes occasionally and then dwelled in the holes, moving around their equilibrium positions.

Coupling Postsynthetic High-Temperature Oxidative Thermolysis and Thermal Rearrangements in Isoreticular Zinc MOFs

Herein, we report coupling in situ high temperature postsynthetic modifications (PSMs) in metal-organic frameworks (MOFs). Thermo-reactive propargyloxy-functionalized zinc IRMOFs (isoreticular metal-organic frameworks) prepared from 2-(prop-2-yn-1-yloxy)-[1,1'-biphenyl]-4,4'-dicarboxylic acid (H₂bpdcOCH₂CCH) were investigated for their high-temperature postsynthetic rearrangement (PSR) chemistry to heterocyclic chromenes and benzofurans and then coupled to solid-gas reactions with molecular oxygen. The selectivity for the initial molecular rearrangements was found to be inverted in the porous MOF environment compared to conventional melt reactions of the ester compound Me₂bpdcOCH₂CCH and proceeded far more easily than the solid-state transformation from H₂bpdcOCH₂CCH, showing the potential of MOFs to give rise to different chemistry. The major oxidative process was thermolysis of the chromene ring with a minor pathway of allylic-type oxidation to give heterocyclic chromenone functionality. The sequence was also successful on a series of two-component multivariate IRMOF frameworks prepared from thermo-reactive H₂bpdcOCH₂CCH and thermo-resistant H₂bpdcOMe linkers, demonstrating that these reactions can be used with known crystal engineering strategies. All transformations were fully compatible with the requirements to maintain MOF crystallinity and porosity as evidenced by surface area analysis and X-ray powder diffraction measurements. This work contributes to establishing the feasibility of high-temperature solid-gas manifolds for MOF PSM.

Prediction of O2/N2 Selectivity in Metal-Organic Frameworks via High-Throughput Computational Screening and Machine Learning

Machine learning (ML), which is becoming an increasingly popular tool in various scientific fields, also shows the potential to aid in the screening of materials for diverse applications. In this study, the computation-ready experimental (CoRE) metal-organic framework (MOF) data set for which the O₂ and N₂ uptakes, self-diffusivities, and Henry's constants were calculated was used to fit the ML models. The obtained models were subsequently employed to predict such properties for a hypothetical MOF (hMOF) data set and to identify structures having a high O₂/N₂ selectivity at room temperature. The performance of the model on known entries indicated that it would serve as a useful tool for the prediction of MOF characteristics with r² correlations between the true and predicted values typically falling between 0.7 and 0.8. The use of different descriptor groups (geometric, atom type, and chemical) was studied; the inclusion of all descriptor groups yielded the best overall results. Only a small number of entries surpassed the performance of those in the CoRE MOF set; however, the use of ML was able to present the structure-property relationship and to identity the top performing hMOFs for O₂/N₂ separation based on the adsorption and diffusion selectivity.

Robust ultrathin nanoporous MOF membrane with intra-crystalline defects for fast water transport

Rational design of high-performance stable metal–organic framework (MOF) membranes is challenging, especially for the sustainable treatment of hypersaline waters to address critical global environmental issues. Herein, a molecular-level intra-crystalline defect strategy combined with a selective layer thinning protocol is proposed to fabricate robust ultrathin missing-linker UiO-66 (ML-UiO-66) membrane to enable fast water permeation. Besides almost complete salt rejection, high and stable water flux is achieved even under long-term pervaporation operation in hash environments, which effectively addresses challenging stability issues. Then, detailed structural characterizations are employed to identify the type, chemical functionality, and density of intra-crystalline missing-linker defects. Moreover, molecular dynamics simulations shed light on the positive atomistic role of these defects, which are responsible for substantially enhancing structural hydrophilicity and enlarging pore window, consequently allowing ultra-fast water transport via a lower-energy-barrier pathway across three-dimensional sub-nanochannels during pervaporation. Unlike common unfavorable defect effects, the present positive intra-crystalline defect engineering concept at the molecular level is expected to pave a promising way toward not only rational design of next-generation MOF membranes with enhanced permeation performance, but additional water treatment applications.

The development of highly water-permeable membranes is key for the treatment of high salinity waters. Here the authors enhance the water permeability of a metal-organic framework nanoporous membrane via an intra-crystalline defect engineering strategy.

Machine Learning-Assisted Computational Screening of Metal-Organic Frameworks for Atmospheric Water Harvesting

Atmospheric water harvesting by strong adsorbents is a feasible method of solving the shortage of water resources, especially for arid regions. In this study, a machine learning (ML)-assisted high-throughput computational screening is employed to calculate the capture of H2O from N2 and O2 for 6013 computation-ready, experimental metal-organic frameworks (CoRE-MOFs) and 137,953 hypothetical MOFs (hMOFs). Through the univariate analysis of MOF structure-performance relationships, Qst is shown to be a key descriptor. Moreover, three ML algorithms (random forest, gradient boosted regression trees, and neighbor component analysis (NCA)) are applied to hunt for the complicated interrelation between six descriptors and performance. After the optimizing strategy of grid search and five-fold cross-validation is performed, three ML can effectively build the predictive model for CoRE-MOFs, and the accuracy R2 of NCA can reach 0.97. In addition, based on the relative importance of the descriptors by ML, it can be quantitatively concluded that the Qst is dominant in governing the capture of H2O. Besides, the NCA model trained by 6013 CoRE-MOFs can predict the selectivity of hMOFs with a R2 of 0.86, which is more universal than other models. Finally, 10 CoRE-MOFs and 10 hMOFs with high performance are identified. The computational screening and prediction of ML could provide guidance and inspiration for the development of materials for water harvesting in the atmosphere.

Machine learning accelerated high-throughput screening of zeolites for the selective adsorption of xylene isomers

A combination of machine learning and high throughput simulation has identified several potential zeolite structures that appear to outperform the leading commercially used material and explained the key factors for high selectivity.

Benzene and triazine-based porous organic polymers with azo, azoxy and azodioxy linkages: a computational study

Computational study of azoxy and azodioxy-based 2D layered structures revealed their potential for the selective binding of CO2 over N2.

Kinetic separation of C2H6/C2H4 in a cage-interconnected metal–organic framework: an interaction-screening mechanism

Multi-scale simulations were carried out on a cage-interconnected metal-organic framework (JNU-2), revealing a rarely observed interaction-screening mechanism that corroborates its large C2H6/C2H4 adsorption selectivity.

Performance of GFN1-xTB for periodic optimization of Metal Organic Frameworks

Tight-binding approaches bridge the gap between force field methods and Density Functional Theory (DFT). Density Functional Tight Binding (DFTB) has been employed for a wide range of systems containing up...

An approach for the pore-centred description of adsorption in hierarchical porous materials

Analysis of metal–organic frameworks featuring hierarchical pore systems is presented and leveraged to understand adsorption in unique pore structures.

Thermal Management for Hydrogen Charging and Discharging in a Screened Metal-Organic Framework Particle Tank

Thermal management of H₂ gas storage in a tank is crucial for determining the H₂ gas deliverable capacity. In this study, a strategy for the design of an excellent comprehensive performance fuel storage tank from the screening of microscopic materials to the design of macroscopic particle adsorption tank performance is proposed. The best metal-organic framework (MOF) for H₂ deliverable capacity in a computation-ready experimental MOF database is first screened using a grand canonical Monte Carlo (GCMC) method. An upscale model that combines the finite volume method with GCMC is then established to investigate the H₂ charging and discharging processes in a screened best MOF-filled adsorption particle tank that is integrated with a phase-change material (PCM) jacket. The process of the heat and mass transfer in the screened best MOF particle adsorption tank with and without the PCM jacket-inserted metal foam is studied. The results show that the prescreened XAWVUN has the highest gravimetric and considerable volumetric deliverable capacity among 503 MOFs, which can reach up to 23.1 mol·kg^-1 and 20.8 kg·m^-3 at 298 K and pressures between 35 000 kPa (adsorption pressure) and 160 kPa (desorption pressure), respectively. The H₂ deliverable capacity can be maximized by 3.2 and 12.1% for PCM jackets inserted with metal foam in the H₂ charging and discharging processes when it is compared with the case without the PCM jacket, respectively. The above study will facilitate the development of new equipment for hydrogen storage.

Incorporating Flexibility Effects into Metal-Organic Framework Adsorption Simulations Using Different Models

High-throughput calculations based on molecular simulations to predict the adsorption of molecules inside metal-organic frameworks (MOFs) have become a useful complement to experimental efforts to identify promising adsorbents for chemical separations and storage. For computational convenience, all existing efforts of this kind have relied on simulations in which the MOF is approximated as rigid. In this paper, we use extensive adsorption-relaxation simulations that fully include MOF flexibility effects to explore the validity of the rigid framework approximation. We also examine the accuracy of several approximate methods to incorporate framework flexibility that are more computationally efficient than adsorption-relaxation calculations. We first benchmark various models of MOF flexibility for four MOFs with well-established CO₂ experimental consensus isotherms. We then consider a range of adsorption properties, including Henry's constants, nondilute loadings, and adsorption selectivity, for seven adsorbates in 15 MOFs randomly selected from the CoRE MOF database. Our results indicate that in many MOFs adsorption-relaxation simulations are necessary to make quantitative predictions of adsorption, particularly for adsorption at dilute concentrations, although more standard calculations based on rigid structures can provide useful information. Finally, we investigate whether a correlation exists between the elastic properties of empty MOFs and the importance of including framework flexibility in making accurate predictions of molecular adsorption. Our results did not identify a simple correlation of this type.

Diversifying Databases of Metal Organic Frameworks for High-Throughput Computational Screening

By combining metal nodes and organic linkers, an infinite number of metal organic frameworks (MOFs) can be designed in silico. Therefore, when making new databases of such hypothetical MOFs, we need to ensure that they not only contribute toward the growth of the count of structures but also add different chemistries to the existing databases. In this study, we designed a database of ∼20,000 hypothetical MOFs, which are diverse in terms of their chemical design space─metal nodes, organic linkers, functional groups, and pore geometries. Using machine learning techniques, we visualized and quantified the diversity of these structures. We find that on adding the structures of our database, the overall diversity metrics of hypothetical databases improve, especially in terms of the chemistry of metal nodes. We then assessed the usefulness of diverse structures by evaluating their performance, using grand-canonical Monte Carlo simulations, in two important environmental applications─post-combustion carbon capture and hydrogen storage. We find that many of these structures perform better than widely used benchmark materials such as Zeolite-13X (for post-combustion carbon capture) and MOF-5 (for hydrogen storage). All the structures developed in this study, and their properties, are provided on the Materials Cloud to encourage further use of these materials for other applications.

Computational Design of MOF-Based Electronic Noses for Dilute Gas Species Detection: Application to Kidney Disease Detection

The diverse chemical composition of exhaled human breath contains a vast amount of information about the health of the body, and yet this is seldom taken advantage of for diagnostic purposes due to the lack of appropriate gas-sensing technologies. In this work, we apply computational methods to design mass-based gas sensor arrays, often called electronic noses, that are optimized for detecting kidney disease from breath, for which ammonia is a known biomarker. We define combined linear adsorption coefficients (CLACs), which are closely related to Henry's law coefficients, for calculating gas adsorption in metal-organic frameworks (MOFs) of gases commonly found in breath (i.e., carbon dioxide, argon, and ammonia). These CLACs were determined computationally using classical atomistic molecular simulation techniques and subsequently used to design and evaluate gas sensor arrays. We also describe a novel numerical algorithm for determining the composition of a breath sample given a set of sensor outputs and a library of CLACs. After identifying an optimal array of five MOFs, we screened a set of 100 simplified computer-generated, water-free breath samples for kidney disease and were able to successfully quantify the amount of ammonia in all samples within the tolerances needed to classify them as either healthy or diseased, demonstrating the promise of such devices for disease detection applications.

Synthesis of Extra-Large Pore, Large Pore and Medium Pore Zeolites Using a Small Imidazolium Cation as the Organic Structure-Directing Agent

One common strategy in the search for new zeolites is the use of organic structure-directing agents (OSDA). Typically, one seeks to achieve a high specificity in the structure-directing effect of the OSDA. This study shows, however, that an OSDA lacking strong specificity towards any particular zeolite may provide opportunities for discovery when other synthesis parameters are systematically screened. Thus, 1-methyl-2-ethyl-3-n-propylimidazolium has allowed to crystallize the new large/medium pore zeolite HPM-16 as well as the recently reported extra-large pore -SYT and the medium/small pore and chiral STW. The sophisticated OSDA originally affording -SYT and the new simple OSDA have very little in common, both in terms of size, shape and flexibility, while both may still direct the synthesis of the same zeolite. In fact, molecular simulations show that the new OSDA is located in three different positions of the -SYT structure, including the discrete 8MR where the original organic could not fit.

Toward comprehensive exploration of the physisorption space in porous pseudomaterials using an iterative mutation search algorithm

We describe an updated algorithm for efficiently exploring structure-property spaces relating to physisorption of gases in porous materials. This algorithm uses previously described "pseudomaterials," which are crystals of randomly arranged and parameterized Lennard-Jones spheres, and combines it with a new iterative mutation exploration method. This algorithm is significantly more efficient at sampling the structure-property space than previously reported methods. For the sake of benchmarking to prior work, we apply this method to exploring methane adsorption at 35 bars (298 K) and void fraction as the main structure-property combination. We demonstrate the effect and importance of the changes that were required to increase efficiency over prior methods. The most important changes were (1) using "discrete" mutations less often, (2) decreasing degrees of freedom, and (3) removing biasing from mutations on bounded parameters.

Temperature-Dependent Nitrous Oxide/Carbon Dioxide Preferential Adsorption in a Thiazolium-Functionalized NU-1000 Metal-Organic Framework

Solvent-assisted ligand incorporation (SALI) of the ditopic linker 5-carboxy-3-(4-carboxybenzyl)thiazolium bromide [(H₂PhTz)Br] into the zirconium metal-organic framework NU-1000 [Zr₆O₄(OH)₈(H₂O)₄(TBAPy)₂, where NU = Northwestern University and H₄TBAPy = 1,3,6,8-tetrakis(p-benzoic-acid)pyrene], led to the SALIed NU-1000-PhTz material of minimal formula [Zr₆O₄(OH)₆(H₂O)₂(TBAPy)₂(PhTz)]Br. NU-1000-PhTz has been thoroughly characterized in the solid state. As confirmed by powder X-ray diffraction, this material keeps the same three-dimensional architecture of NU-1000 and the dicarboxylic extra linker bridges adjacent [Zr₆] nodes ca. 8 Å far apart along the crystallographic c-axis. The functionalized MOF has a BET specific surface area of 1560 m²/g, and it is featured by a slightly higher thermal stability than its parent material (T_dec = 820 vs. 800 K, respectively). NU-1000-PhTz has been exploited for the capture and separation of two pollutant gases: carbon dioxide (CO₂) and nitrous oxide (N₂O). The high thermodynamic affinity for both gases [isosteric heat of adsorption (Q_st) = 25 and 27 kJ mol^-1 for CO₂ and N₂O, respectively] reasonably stems from the strong interactions between these (polar) "stick-like" molecules and the ionic framework. Intriguingly, NU-1000-PhTz shows an unprecedented temperature-dependent adsorption capacity, loading more N₂O in the 298 K ≤ T ≤ 313 K range but more CO₂ at temperatures falling out of this range. Grand canonical Monte Carlo simulations of the adsorption isotherms confirmed that the preferential adsorption sites of both gases are the triangular channels (micropores) in close proximity to the polar pillar. While CO₂ interacts with the thiazolium ring in an "end-on" fashion through its O atoms, N₂O adopts a "side-on" configuration through its three atoms simultaneously. These findings open new horizons in the discovery of functional materials that may discriminate between polluting gases through selective adsorption at different temperatures.

Nonuniformity of Transport Coefficients in Ultrathin Nanoscale Membranes and Nanomaterials

The quest to reduce transport resistance in separations using nanomaterials has led to considerable interest in nanoscale adsorbents and ultrathin membranes. It is now established that interfacial resistance limits the performance of such nanosized materials; however, the origin of this resistance is uncertain. While it is associated with surface pore blockages and distortions in some materials, its existence even in ideal materials is largely putative. Here, we report equilibrium molecular dynamics (EMD) simulations with ideal zeolite-based nanosheets, indicating the transport resistance to be entirely distributed within the solid, without contribution from an interfacial effect. We demonstrate the presence of an internal entry region over which fluid decorrelation occurs, and in which the local transport coefficient inside the crystal is nonuniform and position-dependent, increasing to the uniform value in the bulk material at larger distances. Our EMD-based diffusivity profiles within the nanomaterial enable us to unequivocally determine the entry length, and reveal an internal excess resistance, frequently assumed to be an interfacial resistance, due to significant reduction of the internal transport coefficient in the entrance and exit regions. A decrease in the entry length with loading in PON zeolite nanosheets is seen. We demonstrate a reduction in external resistance in the external bulk chambers used in simulations, triggered by the interplay of incomplete decorrelation in the nanosheet and periodic boundary conditions imposed on the system comprising the nanosheet and surrounding bulk reservoirs when the nanosheet thickness is less than the entry length. Our analysis of the transport dynamics within the nanosheet demonstrates that, at least for ideal systems, decomposition of the inhomogeneous diffusivity-based internal resistance into an interfacial and a uniform transport coefficient-based internal contribution is not appropriate for finite-sized systems. Our results will enable the improved design of nanoscale membranes and materials for applications in separation and other processes.

Analysis of SO2 Physisorption by Edge-Functionalized Nanoporous Carbons Using Grand Canonical Monte Carlo Methods and Density Functional Theory: Implications for SO2 Removal

Nanoporous carbons (NPCs) are ideal materials for the dry process of flue gas desulfurization (FGD) due to their rich pore structure and high specific surface area. To study the effect of edge-functionalized NPCs on the physisorption mechanism of sulfur dioxide, different functional groups were embedded at the edge of NPCs, and the physisorption behavior was simulated using the grand canonical Monte Carlo method (GCMC) combined with density functional theory (DFT). The results indicated that the insertion of acidic oxygenous groups or basic nitrogenous groups into NPCs could enhance the physisorption of SO₂. The influence of edge functionalization on the pore structure of NPCs is also analyzed. To further explore the interaction in the adsorption process, the van der Waals (vdW) interaction and electrostatic interaction between the SO₂ molecule and the basic structural unit (BSU) were investigated. Simulated results showed that edge functionalization had limited influence on vdW interaction and did not significantly change the distribution characteristics of vdW interaction. According to the study on electrostatic interaction, edge functionalization was found to promote inhomogeneity of the surface charge of the adsorbent, enhance the polarity of the adsorbent, and thus enhance the physisorption capacity of SO₂. More importantly, we provide an idea for studying the difference in adsorption capacity caused by different functional groups connected to carbon adsorbents.