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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. [ABSTRACT FROM AUTHOR]

Metal–organic frameworks (MOFs) with open metal sites have been widely investigated for the selective adsorption of small molecules via redox mechanisms where charge transfer can take place between the binding site and the adsorbate of interest. Quantum-chemical screening methods based on density functional theory have emerged as a promising route to accelerate the discovery of MOFs with enhanced binding affinities toward various adsorbates. However, the success of this approach is linked to the accuracy of the underlying density functional approximations (DFAs). In this work, we compare commonly used generalized gradient approximation (GGA), GGA+U, and meta-GGA exchange-correlation functionals in modeling redox-dependent binding at open metal sites in MOFs using O2 and N2 as representative small molecules. We find that the self-interaction error inherent to the widely used Perdew, Burke, and Ernzerhof (PBE) GGA predicts metal sites that are artificially redox-active, as evidenced by their strong binding affinities, short metal–adsorbate bond distances, and large degree of charge transfer. The incorporation of metal-specific, empirical Hubbard U corrections based on the transition metal oxide literature systematically reduces the redox activity of the open metal sites, often improving agreement with experiment. Additionally, the binding behavior shifts from strong chemisorption to weaker physisorption as a function of U. The M06-L meta-GGA typically predicts binding energies between those of PBE-D3(BJ) and PBE-D3(BJ)+U when using empirically derived U values from the transition metal oxide literature. Despite the strong sensitivity of the binding affinities toward a given DFA, the GGA, GGA+U, and meta-GGA approaches often yield the same qualitative trends and structure–property relationships. [ABSTRACT FROM AUTHOR]

Through quantum‐chemical calculations, we investigate a family of metal–organic frameworks (MOFs) containing triazolate linkers, M2X2(BBTA) (M=metal, X=bridging anion, H2BBTA=1H,5H‐benzo(1,2‐d:4,5‐d′)bistriazole), for their ability to form terminal metal–oxo sites and subsequently activate the C−H bond of methane. By varying the metal and bridging anion in the framework, we show how to significantly tune the reactivity of this series of MOFs. The electronic structure of the metal–oxo active site is analyzed for each combination of metal and bridging ligand, and we find that spin density localized on the oxo ligand is not an inherent requirement for low C−H activation barriers. For the Mn‐ and Fe‐containing frameworks, a transition from ferromagnetic to antiferromagnetic coupling between the metal binding site and terminal oxo ligand during the C−H activation process can greatly reduce the kinetic barrier, a unique case of two‐state reactivity without a change in the net spin multiplicity. [ABSTRACT FROM AUTHOR]

The effective detoxification of chemical warfare agents, specifically nerve agents, is a pressing issue in the modern world. Due to the high toxicity of these molecules, simulants are often used in experiments as substitutes for the agents. However, there is little reason to believe that the current simulants used in the literature are optimal predictors of nerve agent reactivity. Density functional theory calculations were performed on the alkaline hydrolysis of over 100 organophosphate molecules to identify improved simulants for the G‐series nerve agents soman and sarin, based on low toxicity and similarity to nerve agent hydrolysis energetics and degradation mechanism. This screening highlighted 5 molecules that have nearly identical reaction barriers to the actual agents, while being far less toxic. Quantitative structure–activity relationship (QSAR) models were also derived to determine the most significant molecular descriptors for describing the hydrolysis free energy barriers of these reactions. The optimal QSAR model was subjected to a thorough statistical analysis and validation procedure to confirm its predictive capacity, showing excellent quantitative and ranking accuracy. It was further shown that the model trained on G‐series agents can reliably predict energetics for other organophosphate classes as well, including VX. Through these computational insights, experimentalists may be aided in accurately and safely studying these reactions with less toxic simulants. [ABSTRACT FROM AUTHOR]

Metal–organic frameworks (MOFs) are a class of nanoporous materials with highly tunable structures in terms of both chemical composition and topology. Due to their tunable nature, high‐throughput computational screening is a particularly appealing method to reduce the time‐to‐discovery of MOFs with desirable physical and chemical properties. In this work, a fully automated, high‐throughput periodic density functional theory (DFT) workflow for screening promising MOF candidates was developed and benchmarked, with a specific focus on applications in catalysis. As a proof‐of‐concept, we use the high‐throughput workflow to screen MOFs containing open metal sites (OMSs) from the Computation‐Ready, Experimental MOF database for the oxidative C—H bond activation of methane. The results from the screening process suggest that, despite the strong C—H bond strength of methane, the main challenge from a screening standpoint is the identification of MOFs with OMSs that can be readily oxidized at moderate reaction conditions. © 2019 Wiley Periodicals, Inc. In this work, a high‐throughput periodic density functional theory (DFT) workflow is developed for the automated screening of metal–organic frameworks for applications in catalysis. As a proof‐of‐concept, the DFT workflow is then used to screen MOFs with open metal sites from the Computation‐Ready, Experimental MOF database to identify promising candidates for methane activation. [ABSTRACT FROM AUTHOR]

Density functional theory was used to study interactions between phosphine and 17 functional groups, revealing that only the functional groups containing metal ions bind phosphine strongly. This led to a detailed examination of the adsorption of the pnictogen hydride gases ammonia, phosphine, and arsine on 33 metal catecholates in order to examine periodic trends in the binding strength for these adsorbates. Phosphine and arsine adsorption is primarily driven by donation of electron density from the adsorbate molecule to the metal atom, while ammonia binding involves both electron donation and a significant Coulomb attraction between the negatively charged N atom and the positive metal atom. This Coulomb effect results in notably different binding behavior for ammonia than for phosphine and arsine, which are quite similar to each other. Generally, for metals on the left side of the periodic table, the Coulomb effect dominates in ammonia adsorption, and metals on the right side of the periodic table have lower positive charge and accept greater amounts of electron density, making the electron-sharing contribution more important to the binding strength. We find that more electronegative metals, particularly Pd, Ir, Pt, and Au, which accept more electron density from the adsorbate, yield the best selectivity for the target molecules over water because water adsorption is mostly due to Coulomb attraction. We also analyze changes in the d orbital occupancy upon ammonia and phosphine adsorption. [ABSTRACT FROM AUTHOR]

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 (a-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. [ABSTRACT FROM AUTHOR]

• VO x and CeO 2 surface speciation on Al 2 O 3 depends on the ALD growth sequence. • The presence of CeO 2 does not impact the electronic structure of the V O bond. • VO x and CeO 2 on Al 2 O 3 migrate at elevated temperatures under reducing conditions. • CeO 2 clusters on Al 2 O 3 and ceria surface sites in VO x /CeO 2 favor total oxidation. • Different active sites on CeO 2 show varying reactivity towards alkane and alkene. Alumina-supported VO x -CeO 2 materials are synthesized by atomic layer deposition (ALD) and evaluated in cyclohexane oxidative dehydrogenation (ODH). The order of deposition of the two metal oxides by ALD influences the size, geometry and oxidation state of the resulting surface species as indicated by Raman spectroscopy coupled with density functional theory (DFT) calculations and XPS. The individual contributions of VO x and CeO 2 surface sites to the cyclohexane ODH reaction mechanism are investigated through a comparison of the catalytic activity of the supported mixed metal oxide materials, VO x /Al 2 O 3 , VO x /CeO 2 and a bare CeO 2 support. The highest activity is observed for CeO 2 , and different surface active sites are distinguished by introducing cyclohexane and cyclohexene in the reactant feed mixture. The catalytic behavior is dependent on the nature of V O S (S, Support) bonds, and small clusters of CeO 2 on Al 2 O 3 favor total oxidation, similar to exposed CeO 2 sites in VO x /CeO 2. [ABSTRACT FROM AUTHOR]

This review spotlights the role of atomic‐level modeling in research on metal‐organic frameworks (MOFs), especially the key methodologies of density functional theory (DFT), Monte Carlo (MC) simulations, and molecular dynamics (MD) simulations. The discussion focuses on how periodic and cluster‐based DFT calculations can provide novel insights into MOF properties, with a focus on predicting structural transformations, understanding thermodynamic properties and catalysis, and providing information or properties that are fed into classical simulations such as force field parameters or partial charges. Classical simulation methods, highlighting force field selection, databases of MOFs for high‐throughput screening, and the synergistic nature of MC and MD simulations, are described. By predicting equilibrium thermodynamic and dynamic properties, these methods offer a wide perspective on MOF behavior and mechanisms. Additionally, the incorporation of machine learning (ML) techniques into quantum and classical simulations is discussed. These methods can enhance accuracy, expedite simulation setup, reduce computational costs, as well as predict key parameters, optimize geometries, and estimate MOF stability. By charting the growth and promise of computational research in the MOF field, the aim is to provide insights and recommendations to facilitate the incorporation of computational modeling more broadly into MOF research. [ABSTRACT FROM AUTHOR]

Competitive coadsorption of water is a major problem in the deployment of adsorption-based CO2 capture. Water molecules may compete for adsorption sites, reducing the capacity of the material, and dehumidification prior to separating CO2 from N2 increases process complexity and cost. The development of adsorbent materials that can selectively adsorb CO2 in the presence of water would be a major step forward in the deployment of CO2 capture materials in practice. In this study, large-scale computational screening was carried out to search for metal-organic frameworks (MOFs) with high selectivity toward CO2 over H2O. Calculating framework charges for thousands of MOFs is a significant challenge, so initial screening used a fast, but approximate, charge calculation method. On the basis of the initial screening, 15 MOFs were selected, and Monte Carlo simulations were carried out to compute the adsorption isotherms for these MOFs using more accurate framework charges calculated by density functional theory. A detailed investigation was performed on the effect of using different methods for calculating partial charges, and it was found that electrostatic interactions contribute the majority of the adsorption energy of H2O in the selected MOFs. [ABSTRACT FROM AUTHOR]

Efforts to computationally characterize large numbers of nanoporous materials often rely on databases of experimentally resolved crystal structures. The accuracy of experimental crystal structures used in such calculations has a significant impact on the reliability of the results. In this work, we report structures optimized using periodic density functional theory (DFT) for more than 800 experimentally synthesized metal-organic frameworks (MOFs). Many MOFs changed significantly upon structural optimization, particularly materials that were crystallographically resolved in their solvated form. For each MOF, we simulated the adsorption of CH4 and CO2 using grand canonical Monte Carlo both before and after DFT optimization. The DFT optimization has a large impact on simulated gas adsorption in some cases. For example, CO2 loading at 1 bar changed by more than 25% in over 25% of the MOFs we considered. [ABSTRACT FROM AUTHOR]

"Breathing" metal-organic frameworks (MOFs) are an emerging class of soft porous crystals (SPCs) with potential for high working capacity for gas storage applications. However, most breathing MOFs have low stability and/or low surface area. Here we report a water-stable, high surface area, breathing MOF of ftw topology, NU-1105. While Zr6-oxo clusters as nodes introduce water stability in NU-1105, its high surface area and breathing character stem from its pyrene-based tetracarboxylate (Py-FP) linkers, in which the fluorene units (F) in the FP "arms" play a key role in promoting breathing behavior. During gas sorption studies, the "closed pore" (cp) ↔ "open pore" (op) transition of NU-1105 occurs at a propane pressure of ~3 bar. At 1 bar, NU-1105 is in its cp form and adsorbs less propane than it would in its op form, highlighting improved working capacity. In situ powder X-ray diffraction during propane sorption was used to track the cp ↔ op transition, and molecular modeling was used to elucidate the structure of the op and cp forms of NU-1105. According to TD-DFT calculations, the proposed conformations of the Py-FP linkers in the op and cp forms are consistent with the measured excitation and emission spectra of the op and cp forms of NU-1105. Similar structural transitions are also observed in the porphyrinic MOF NU-1104 depending on the identity of the porphyrin core; we observed breathing behavior if the constituent Por-PTP linker is nonmetalated. [ABSTRACT FROM AUTHOR]