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.

Exploring mechanistic routes for light alkane oxidation with an iron-triazolate metal-organic framework.

In this work, we computationally explore the formation and subsequent reactivity of various iron-oxo species in the iron-triazolate framework Fe2(µ-OH)2(bbta) (H2bbta = 1H,5H-benzo(1,2-d:4,5-d')bistriazole) for the catalytic activation of strong C-H bonds. With the direct conversion of methane to methanol as the probe reaction of interest, we use density functional theory (DFT) calculations to evaluate multiple mechanistic pathways in the presence of either N2O or H2O2 oxidants. These calculations reveal that a wide range of transition metal-oxo sites - both terminal and bridging - are plausible in this family of metal-organic frameworks, making it a unique platform for comparing the electronic structure and reactivity of different proposed active site motifs. Based on the DFT calculations, we predict that Fe2(µ-OH)2(bbta) would exhibit a relatively low barrier for N2O activation and energetically favorable formation of an [Fe(O)]2+ species that is capable of oxidizing C-H bonds. In contrast, the use of H2O2 as the oxidant is predicted to yield an assortment of bridging iron-oxo sites that are less reactive. We also find that abstracting oxo ligands can exhibit a complex mixture of both positive and negative spin density, which may have broader implications for relating the degree of radical character to catalytic activity. In general, we consider the coordinatively unsaturated iron sites to be promising for oxidation catalysis, and we provide several recommendations on how to further tune the catalytic properties of this family of metal-triazolate frameworks.

Fine-Tuning a Robust Metal-Organic Framework toward Enhanced Clean Energy Gas Storage.

The development of adsorbents with molecular precision offers a promising strategy to enhance storage of hydrogen and methane─considered the fuel of the future and a transitional fuel, respectively─and to realize a carbon-neutral energy cycle. Herein we employ a postsynthetic modification strategy on a robust metal-organic framework (MOF), MFU-4l, to boost its storage capacity toward these clean energy gases. MFU-4l-Li displays one of the best volumetric deliverable hydrogen capacities of 50.2 g L-1 under combined temperature and pressure swing conditions (77 K/100 bar → 160 K/5 bar) while maintaining a moderately high gravimetric capacity of 9.4 wt %. Moreover, MFU-4l-Li demonstrates impressive methane storage performance with a 5-100 bar usable capacity of 251 cm3 (STP) cm-3 (0.38 g g-1) and 220 cm3 (STP) cm-3 (0.30 g g-1) at 270 and 296 K, respectively. Notably, these hydrogen and methane storage capacities are significantly improved compared to those of its isoreticular analogue, MFU-4l, and place MFU-4l-Li among the best MOF-based materials for this application.

Tuning the Redox Activity of Metal-Organic Frameworks for Enhanced, Selective O2 Binding: Design Rules and Ambient Temperature O2 Chemisorption in a Cobalt-Triazolate Framework.

Metal-organic frameworks (MOFs) with coordinatively unsaturated metal sites are appealing as adsorbent materials due to their tunable functionality and ability to selectively bind small molecules. Through the use of computational screening methods based on periodic density functional theory, we investigate O2 and N2 adsorption at the coordinatively unsaturated metal sites of several MOF families. A variety of design handles are identified that can be used to modify the redox activity of the metal centers, including changing the functionalization of the linkers (replacing oxido donors with sulfido donors), anion exchange of bridging ligands (considering µ-Br-, µ-Cl-, µ-F-, µ-SH-, or µ-OH- groups), and altering the formal oxidation state of the metal. As a result, we show that it is possible to tune the O2 affinity at the open metal sites of MOFs for applications involving the strong and/or selective binding of O2. In contrast with O2 adsorption, N2 adsorption at open metal sites is predicted to be relatively weak across the MOF dataset, with the exception of MOFs containing synthetically elusive V2+ open metal sites. As one example from the screening study, we predicted that exchanging the µ-Cl- ligands of M2Cl2(BBTA) (H2BBTA = 1H,5H-benzo(1,2-d:4,5-d')bistriazole) with µ-OH- groups would significantly enhance the strength of O2 adsorption at the open metal sites without a corresponding increase in the N2 affinity. Experimental investigation of Co2Cl2(BBTA) and Co2(OH)2(BBTA) confirms that the former exhibits weak physisorption of both N2 and O2, whereas the latter is capable of chemisorbing O2 at room temperature in a highly selective manner. The O2 chemisorption behavior is attributed to the greater electron-donating character of the µ-OH- ligands and the presence of H-bonding interactions between the µ-OH- bridging ligands and the reduced O2 adsorbate.

Comparing GGA, GGA+U, and meta-GGA functionals for redox-dependent binding at open metal sites in metal-organic frameworks.

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.

High-Valent Metal-Oxo Species at the Nodes of Metal-Triazolate Frameworks: The Effects of Ligand Exchange and Two-State Reactivity for C-H Bond Activation.

Through quantum-chemical calculations, we investigate a family of metal-organic frameworks (MOFs) containing triazolate linkers, M2 X2 (BBTA) (M=metal, X=bridging anion, H2 BBTA=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.

Identifying promising metal-organic frameworks for heterogeneous catalysis via high-throughput periodic density functional theory.

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.

Tetrazine-Linked Covalent Organic Frameworks With Acid Sensing and Photocatalytic Activity.

The first synthesis and comprehensive characterization of two vinyl tetrazine-linked covalent organic frameworks (COF), TA-COF-1 and TA-COF-2, are reported. These materials exhibit high crystallinity and high specific surface areas of 1323 and 1114 m2 g-1. The COFs demonstrate favorable band positions and narrow band gaps suitable for light-driven applications. These advantages enable TA-COFs to act as reusable metal-free photocatalysts in the arylboronic acids oxidation and light-induced coupling of benzylamines. In addition, these TA-COFs show acid sensing capabilities, exhibiting visible and reversible color changes upon exposure to HCl solution, HCl vapor, and NH3 vapor. Further, the TA-COFs outperform a wide range of previously reported COF photocathodes. The tetrazine linker in the COF skeleton represents a significant advancement in the field of COF synthesis, enhancing the separation efficiency of charge carriers during the photoreaction and contributing to their photocathodic properties. TA-COFs can also degrade 5-nitro-1,2,4-triazol-3-one (NTO), an insensitive explosive present in industrial wastewater, in 20 min in a sunlight-driven photocatalytic process; thus, revealing dual functionality of the protonated TA-COFs as both photodegradation and Brønsted acid catalysts. This pioneering work opens new avenues for harnessing the potential of the tetrazine linker in COF-based materials, facilitating advances in catalysis, sensing, and other related fields.

Structured information extraction from scientific text with large language models.

Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models (GPT-3, Llama-2) can be fine-tuned to extract useful records of complex scientific knowledge. We test three representative tasks in materials chemistry: linking dopants and host materials, cataloging metal-organic frameworks, and general composition/phase/morphology/application information extraction. Records are extracted from single sentences or entire paragraphs, and the output can be returned as simple English sentences or a more structured format such as a list of JSON objects. This approach represents a simple, accessible, and highly flexible route to obtaining large databases of structured specialized scientific knowledge extracted from research papers.

Free-atom-like d states beyond the dilute limit of single-atom alloys.

Through a data-mining and high-throughput density functional theory approach, we identify a diverse range of metallic compounds that are predicted to have transition metals with "free-atom-like" d states that are highly localized in terms of their energetic distribution. Design principles that favor the formation of localized d states are uncovered, among which we note that site isolation is often necessary but that the dilute limit, as in most single-atom alloys, is not a pre-requisite. Additionally, the majority of localized d state transition metals identified from the computational screening study exhibit partial anionic character due to charge transfer from neighboring metal species. Using CO as a representative probe molecule, we show that localized d states for Rh, Ir, Pd, and Pt tend to reduce the binding strength of CO compared to their pure elemental analogues, whereas this does not occur as consistently for the Cu binding sites. These trends are rationalized through the d-band model, which suggests that the significantly reduced d-band width results in an increased orthogonalization energy penalty upon CO chemisorption. With the multitude of inorganic solids that are predicted to have highly localized d states, the results of the screening study are likely to result in new avenues for heterogeneous catalyst design from an electronic structure perspective.

An Ecosystem for Digital Reticular Chemistry.

The vastness of the materials design space makes it impractical to explore using traditional brute-force methods, particularly in reticular chemistry. However, machine learning has shown promise in expediting and guiding materials design. Despite numerous successful applications of machine learning to reticular materials, progress in the field has stagnated, possibly because digital chemistry is more an art than a science and its limited accessibility to inexperienced researchers. To address this issue, we present mofdscribe, a software ecosystem tailored to novice and seasoned digital chemists that streamlines the ideation, modeling, and publication process. Though optimized for reticular chemistry, our tools are versatile and can be used in nonreticular materials research. We believe that mofdscribe will enable a more reliable, efficient, and comparable field of digital chemistry.