Avoiding pitfalls in molecular simulation of vapor sorption: Example of propane and isobutane in metal-organic frameworks for adsorption cooling applications.

This study introduces recommendations for conducting molecular simulations of vapor adsorption, with an emphasis on enhancing the accuracy, reproducibility, and comparability of results. The first aspect we address is consistency in the implementation of some details of typical molecular models, including tail corrections and cutoff distances, due to their significant influence on generated data. We highlight the importance of explicitly calculating the saturation pressures at relevant temperatures using methods such as Gibbs ensemble Monte Carlo simulations and illustrate some pitfalls in extrapolating saturation pressures using this method. For grand canonical Monte Carlo (GCMC) simulations, the input fugacity is usually calculated using an equation of state, which often requires the critical parameters of the fluid. We show the importance of using critical parameters derived from the simulation with the same model to ensure internal consistency between the simulated explicit adsorbate phase and the implicit bulk phase in GCMC. We show the advantages of presenting isotherms on a relative pressure scale to facilitate easier comparison among models and with experiment. Extending these guidelines to a practical case study, we evaluate the performance of various isoreticular metal-organic frameworks (MOFs) in adsorption cooling applications. This includes examining the advantages of using propane and isobutane as working fluids and identifying MOFs with a superior performance.

An active, stable cubic molybdenum carbide catalyst for the high-temperature reverse water-gas shift reaction.

Although technologically promising, the reduction of carbon dioxide (CO2) to produce carbon monoxide (CO) remains economically challenging owing to the lack of an inexpensive, active, highly selective, and stable catalyst. We show that nanocrystalline cubic molybdenum carbide (α-Mo2C), prepared through a facile and scalable route, offers 100% selectivity for CO2 reduction to CO while maintaining its initial equilibrium conversion at high space velocity after more than 500 hours of exposure to harsh reaction conditions at 600°C. The combination of operando and postreaction characterization of the catalyst revealed that its high activity, selectivity, and stability are attributable to crystallographic phase purity, weak CO-Mo2C interactions, and interstitial oxygen atoms, respectively. Mechanistic studies and density functional theory (DFT) calculations provided evidence that the reaction proceeds through an H2-aided redox mechanism.

Chemically Reversible CO2 Uptake by Dendrimer-Impregnated Metal-Organic Frameworks.

Industrialization over the past two centuries has resulted in a continuous rise in global CO2 emissions. These emissions are changing ecosystems and livelihoods. Therefore, methods are needed to capture these emissions from point sources and possibly from our atmosphere. Though the amount of CO2 is rising, it is challenging to capture directly from air because its concentration in air is extremely low, 0.04%. In this study, amines installed inside metal-organic frameworks (MOFs) are investigated for the adsorption of CO2, including at low concentrations. The amines used are polyamidoamine dendrimers that contain many primary amines. Chemically reversible adsorption of CO2 via carbamate formation was observed, as was enhanced uptake of carbon dioxide, likely via dendrimer-amide-based physisorption. Limiting factors in this initial study are comparatively low dendrimer loadings and slow kinetics for carbon dioxide uptake and release, even at 80 °C.

Tailoring Hydrophobicity and Pore Environment in Physisorbents for Improved Carbon Dioxide Capture under High Humidity.

CALF-20, a Zn-triazolate-based metal-organic framework (MOF), is one of the most promising adsorbent materials for CO2 capture. However, competitive adsorption of water severely limits its performance when the relative humidity (RH) exceeds 40%, limiting the potential implementation of CALF-20 in practical settings where CO2 is saturated with moisture, such as postcombustion flue gas. In this work, three newly designed MOFs related to CALF-20, denoted as NU-220, CALF-20M-w, and CALF-20M-e that feature hydrophobic methyltriazolate linkers, are presented. Inclusion of methyl groups in the linker is proposed as a strategy to improve the uptake of CO2 in the presence of water. Notably, both CALF-20M-w and CALF-20M-e retain over 20% of their initial CO2 capture efficiency at 70% RH─a threshold at which CALF-20 shows negligible CO2 uptake. Grand canonical Monte Carlo simulations reveal that the methyl group hinders water network formation in the pores of CALF-20M-w and CALF-20M-e and enhances their CO2 selectivity over N2 in the presence of a high moisture content. Moreover, calculated radial distribution functions indicate that introducing the methyl group into the triazolate linker increases the distance between water molecules and Zn coordination bonds, offering insights into the origin of the enhanced moisture stability observed for CALF-20M-w and CALF-20M-e relative to CALF-20. Overall, this straightforward design strategy has afforded more robust sorbents that can potentially meet the challenge of effectively capturing CO2 in practical industrial applications.

Geometry and Chemistry: Influence of Pore Functionalization on Molecular Transport and Diffusion in Solvent-Filled Zirconium Metal-Organic Frameworks.

Postsynthetic modification (PSM) of metal-organic frameworks (MOFs) enables incorporation of diverse functionalities in pores for chemical separations, drug delivery, and heterogeneous catalysis. However, the effect of PSM on molecular transport, which is essential for most applications of MOFs, has been rarely studied. In this paper, we used perfluoroalkane-functionalized Zr-MOF NU-1008 as a platform to systematically interrogate transport processes and mechanisms in solvated pores. We anchored perfluoroalkanes onto NU-1008 nodes by solvent-assisted ligand incorporation (SALI-n, with n = 3, 5, 7, and 9 denoting the number of fluorinated carbons). Transport of a luminescent molecule, BODIPY, through individual crystallites of four versions of methanol-filled SALI-n was monitored by confocal fluorescence microscopy as a function of time and location. In comparison with the parent NU-1008, the diffusivity of the probe molecules within SALI-n declined by 2- to 7-fold depending on chain length and loading, presumably due to the reduction in pore diameter or adsorptive interactions with perfluoroalkyl chains. Atomistic simulations were performed to uncover the microscopic behavior of the BODIPY diffusion in SALI-n. The perfluoroalkyl chains are observed to stay close to the pore walls, instead of extending toward the pore center. BODIPY molecules, which preferably interact with linkers, were pushed to the interior of the channels as the chain length increased, resulting in solvated diffusion and minor differences in the short-time mobility of BODIPY in SALI-n. This suggested that the observed decline of transport diffusivity in SALI-n mainly stemmed from the reduction in the pore size when these flexible chains are present. We anticipate that this proof of concept will assist in understanding how pore functionalization can physically and chemically affect mass transport in MOFs and will be useful in further guiding the design of PSM to realize the optimal performance of MOFs for various applications.

Air-Stable Cu(I) Metal-Organic Framework for Hydrogen Storage.

Metal-organic frameworks (MOFs) that contain open metal sites have the potential for storing hydrogen (H2) at ambient temperatures. In particular, Cu(I)-based MOFs demonstrate very high isosteric heats of adsorption for hydrogen relative to other reported MOFs with open metal sites. However, most of these Cu(I)-based MOFs are not stable in ambient conditions since the Cu(I) species display sensitivity toward moisture and can rapidly oxidize in air. As a result, researchers have focused on the synthesis of new air-stable Cu(I)-based materials for H2 storage. Here, we have developed a de novo synthetic strategy to generate a robust Cu(I)-based MOF, denoted as NU-2100, using a mixture of Cu/Zn precursors in which zinc acts as a catalyst to transform an intermediate MOF into NU-2100 without getting incorporated into the final MOF structure. NU-2100 is air-stable and displays one of the initial highest isosteric heats of adsorption (32 kJ/mol) with good hydrogen storage capability under ambient conditions (10.4 g/L, 233 K/100 bar to 296 K/5 bar). We further elucidated the H2 storage performance of NU-2100 using a combination of spectroscopic analysis and computational modeling studies. Overall, this new synthetic route may enable the design of additional stable Cu(I)-MOFs for next-generation hydrogen storage adsorbents at ambient temperatures.

Regulating adsorption performance of zeolites by pre-activation in electric fields.

While multiple external stimuli (e.g., temperature, light, pressure) have been reported to regulate gas adsorption, limited studies have been conducted on controlling molecular admission in nanopores through the application of electric fields (E-field). Here we show gas adsorption capacity and selectivity in zeolite molecular sieves can be regulated by an external E-field. Through E-field pre-activation during degassing, several zeolites exhibited enhanced CO2 adsorption and decreased CH4 and N2 adsorptions, improving the CO2/CH4 and CO2/N2 separation selectivity by at least 25%. The enhanced separation performance of the zeolites pre-activated by E-field was maintained in multiple adsorption/desorption cycles. Powder X-ray diffraction analysis and ab initio computational studies revealed that the cation relocation and framework expansion induced by the E-field accounted for the changes in gas adsorption capacities. These findings demonstrate a regulation approach to sharpen the molecular sieving capability by E-fields and open new avenues for carbon capture and molecular separations.

High-Throughput Screening of the CoRE-MOF-2019 Database for CO2 Capture from Wet Flue Gas: A Multi-Scale Modeling Strategy.

Stabilizing the escalating CO2 levels in the atmosphere is a grand challenge in view of the increasing global demand for energy, the majority of which currently comes from the burning of fossil fuels. Capturing CO2 from point source emissions using solid adsorbents may play a part in meeting this challenge, and metal-organic frameworks (MOFs) are considered to be a promising class of materials for this purpose. It is important to consider the co-adsorption of water when designing materials for CO2 capture from post-combustion flue gases. Computational high-throughput screening (HTS) is a powerful tool to identify top-performing candidates for a particular application from a large material database. Using a multi-scale modeling strategy that includes a machine learning model, density functional theory (DFT) calculations, force field (FF) optimization, and grand canonical Monte Carlo (GCMC) simulations, we carried out a systematic computational HTS of the all-solvent-removed version of the computation-ready experimental metal-organic framework (CoRE-MOF-2019) database for selective adsorption of CO2 from a wet flue gas mixture. After initial screening based on the pore diameters, a total of 3703 unique MOFs from the database were considered for screening based on the FF interaction energies of CO2, N2, and H2O molecules with the MOFs. MOFs showing stronger interactions with CO2 compared to that with H2O and N2 were considered for the next level of screening based on the interaction energies calculated from DFT. CO2-selective MOFs from DFT screening were further screened using two-component (CO2 and N2) and finally three-component (CO2, N2, and H2O) GCMC simulations to predict the CO2 capacity and CO2/N2 selectivity. Our screening study identified MOFs that show selective CO2 adsorption under wet flue gas conditions with significant CO2 uptake capacity and CO2/N2 selectivity in the presence of water vapor. We also analyzed the nature of pore confinements responsible for the observed CO2 selectivity.

Water-Accelerated Transport: Vapor-Phase Nerve Agent Simulant Delivery within a Catalytic Zirconium Metal-Organic Framework as a Function of Relative Humidity.

Zirconium-based metal-organic frameworks (MOFs) are candidate materials for effective nerve agent detoxification due to their thermo- and water stability as well as high density of catalytic Zr sites. However, as high-porosity materials, most of the active sites of Zr-MOFs can only be accessed by diffusion into the crystal interior. Therefore, the transport of nerve agents in nanopores is an important factor in the catalytic performance of Zr-MOFs. Here, we investigated the transport process and mechanism of a vapor-phase nerve agent simulant, dimethyl methyl phosphonate (DMMP), through a representative Zr-MOF, NU-1008, under practical conditions of varying humidity. Confocal Raman microscopy was used to monitor the transport of DMMP vapor through individual NU-1008 crystallites, where the relative humidity (RH) of the environment was tuned to understand the impact of water. Counterintuitively, water in the MOF channels, instead of blocking DMMP transport, assists DMMP diffusion; indeed, the transport diffusivity (Dt) of DMMP in NU-1008 is one order of magnitude higher at 70% than 0% RH. To understand the mechanism, magic angle spinning NMR and molecular dynamics simulations were performed and suggested that high water content in the channels prevents DMMP from hydrogen-bonding with the nodes, allowing for faster diffusion of DMMP in the channels. The simulated self-diffusivity (Ds) of DMMP is observed to be concentration-dependent. At low loading of DMMP, Ds is higher at 70% RH than 0% RH, while at high loadings the trend reverses due to the DMMP aggregation in water and the reduction of free volume in channels.

Computational investigation of hysteresis and phase equilibria of n-alkanes in a metal-organic framework with both micropores and mesopores.

Adsorption hysteresis is a phenomenon related to phase transitions that can impact applications such as gas storage and separations in porous materials. Computational approaches can greatly facilitate the understanding of phase transitions and phase equilibria in porous materials. In this work, adsorption isotherms for methane, ethane, propane, and n-hexane were calculated from atomistic grand canonical Monte Carlo (GCMC) simulations in a metal-organic framework having both micropores and mesopores to better understand hysteresis and phase equilibria between connected pores of different size and the external bulk fluid. At low temperatures, the calculated isotherms exhibit sharp steps accompanied by hysteresis. As a complementary simulation method, canonical (NVT) ensemble simulations with Widom test particle insertions are demonstrated to provide additional information about these systems. The NVT+Widom simulations provide the full van der Waals loop associated with the sharp steps and hysteresis, including the locations of the spinodal points and points within the metastable and unstable regions that are inaccessible to GCMC simulations. The simulations provide molecular-level insight into pore filling and equilibria between high- and low-density states within individual pores. The effect of framework flexibility on adsorption hysteresis is also investigated for methane in IRMOF-1.

Computational Screening of Supported Metal Oxide Nanoclusters for Methane Activation: Insights into Homolytic versus Heterolytic C-H Bond Dissociation.

Since its discovery in zeolites, the [CuOCu]2+ motif has played an important role in our understanding of selective methane activation over supported metal oxide nanoclusters. Although there are two known C-H bond dissociation mechanisms, namely, homolytic and heterolytic cleavage, most computational studies on optimizing metal oxide nanoclusters for improved methane activation reactivity have focused only on the homolytic mechanism. In this work, both mechanisms were examined for a set of 21 mixed metal oxide complexes of the form of [M1OM2]2+ (M1 and M2 = Mn, Fe, Co, Ni, Cu, and Zn). Except for pure copper, heterolytic cleavage was found to be the dominant C-H bond activation pathway for all systems. Furthermore, mixed systems including [CuOMn]2+, [CuONi]2+, and [CuOZn]2+ are predicted to possess methane activation activity similar to pure [CuOCu]2+. These results suggest that both homolytic and heterolytic mechanisms should be considered in computing methane activation energies on supported metal oxide nanoclusters.

Unveiling Unexpected Modulator-CO2 Dynamics within a Zirconium Metal-Organic Framework.

Carbon capture, storage, and utilization (CCSU) represents an opportunity to mitigate carbon emissions that drive global anthropogenic climate change. Promising materials for CCSU through gas adsorption have been developed by leveraging the porosity, stability, and tunability of extended crystalline coordination polymers called metal-organic frameworks (MOFs). While the development of these frameworks has yielded highly effective CO2 sorbents, an in-depth understanding of the properties of MOF pores that lead to the most efficient uptake during sorption would benefit the rational design of more efficient CCSU materials. Though previous investigations of gas-pore interactions often assumed that the internal pore environment was static, discovery of more dynamic behavior represents an opportunity for precise sorbent engineering. Herein, we report a multifaceted in situ analysis following the adsorption of CO2 in MOF-808 variants with different capping agents (formate, acetate, and trifluoroacetate: FA, AA, and TFA, respectively). In situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analysis paired with multivariate analysis tools and in situ powder X-ray diffraction revealed unexpected CO2 interactions at the node associated with dynamic behavior of node-capping modulators in the pores of MOF-808, which had previously been assumed to be static. MOF-808-TFA displays two binding modes, resulting in higher binding affinity for CO2. Computational analyses further support these dynamic observations. The beneficial role of these structural dynamics could play an essential role in building a deeper understanding of CO2 binding in MOFs.

Evidence of a Uranium-Paddlewheel Node in a Catecholate-Based Metal-Organic Framework.

The interactions between uranium and non-innocent organic species are an essential component of fundamental uranium redox chemistry. However, they have seldom been explored in the context of multidimensional, porous materials. Uranium-based metal-organic frameworks (MOFs) offer a new angle to study these interactions, as these self-assembled species stabilize uranium species through immobilization by organic linkers within a crystalline framework, while potentially providing a method for adjusting metal oxidation state through coordination of non-innocent linkers. We report the synthesis of the MOF NU-1700, assembled from U4+ -paddlewheel nodes and catecholate-based linkers. We propose this highly unusual structure, which contains two U4+ ions in a paddlewheel built from four linkers-a first among uranium materials-as a result of extensive characterization via powder X-ray diffraction (PXRD), sorption, transmission electron microscopy (TEM), and thermogravimetric analysis (TGA), in addition to density functional theory (DFT) calculations.

Engineering Metal-Organic Frameworks for Selective Separation of Hexane Isomers Using 3-Dimensional Linkers.

Metal-organic frameworks (MOFs) are highly tunable materials with potential for use as porous media in non-thermal adsorption or membrane-based separations. However, many separations target molecules with sub-angstrom differences in size, requiring precise control over the pore size. Herein, we demonstrate that this precise control can be achieved by installing a three-dimensional linker in an MOF with one-dimensional channels. Specifically, we synthesized single crystals and bulk powder of NU-2002, an isostructural framework to MIL-53 with bicyclo[1.1.1]pentane-1,3-dicarboxylic acid as the organic linker component. Using variable-temperature X-ray diffraction studies, we show that increasing linker dimensionality limits structural breathing relative to MIL-53. Furthermore, single-component adsorption isotherms demonstrate the efficacy of this material for separating hexane isomers based on the different sizes and shapes of these isomers.

Structure-Activity Relationship Insights for Organophosphonate Hydrolysis at Ti(IV) Active Sites in Metal-Organic Frameworks.

Organophosphorus nerve agents are among the most toxic chemicals known and remain threats to humans due to their continued use despite international bans. Metal-organic frameworks (MOFs) have emerged as a class of heterogeneous catalysts with tunable structures that are capable of rapidly detoxifying these chemicals via hydrolysis at Lewis acidic active sites on the metal nodes. To date, the majority of studies in this field have focused on zirconium-based MOFs (Zr-MOFs) that contain hexanuclear Zr(IV) clusters, despite the large toolbox of Lewis acidic transition metal ions that are available to construct MOFs with similar catalytic properties. In particular, very few reports have disclosed the use of a Ti-based MOF (Ti-MOF) as a catalyst for this transformation even though Ti(IV) is a stronger Lewis acid than Zr(IV). In this work, we explored five Ti-MOFs (Ti-MFU-4l, NU-1012-NDC, MIL-125, Ti-MIL-101, MIL-177(LT), and MIL-177(HT)) that each contains Ti(IV) ions in unique coordination environments, including monometallic, bimetallic, octanuclear, triangular clusters, and extended chains, as catalysts to explore how both different node structures and different linkers (e.g., azolate and carboxylate) influence the binding and subsequent hydrolysis of an organophosphorus nerve agent simulant at Ti(IV)-based active sites in basic aqueous solutions. Experimental and theoretical studies confirm that Ti-MFU-4l, which contains monometallic Ti(IV)-OH species, exhibits the best catalytic performance among this series with a half-life of roughly 2 min. This places Ti-MFU-4l as one of the best nerve agent hydrolysis catalysts of any MOF reported to date.

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials.

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ∼ 0.94-0.99) for predicting single-component adsorption capacity in metal-organic frameworks (MOFs). We consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

Insights and Heuristics for Predicting Diffusion Rates of Chemical Warfare Agents in Zirconium Metal-Organic Frameworks.

Designing nanoporous catalysts to destroy chemical warfare agents (CWAs) and environmental contaminants requires consideration of both intrinsic catalytic activity and the mass transfer of molecules in and out of the pores. Polar adsorbates such as CWAs experience a heterogeneous environment in many metal-organic frameworks (MOFs) due to the arrangement of the metal nodes and organic linkers of the MOF. However, quantitative relationships between the pore architecture and the resulting diffusion properties of polar molecules have not been established. We used molecular dynamics simulations to calculate the diffusion coefficients of the CWA simulant dimethyl methyl phosphonate (DMMP) in a diverse set of 776 MOFs with Zr6 nodes. We developed a 4-parameter machine learning model to predict DMMP diffusivities in Zr6 MOFs and found the model to be transferable to the CWA sarin. We then developed a simplified heuristic based on the machine learning model that the node-node distance and accessible surface area should be maximized to find MOFs with rapid CWA diffusion.