Does repeat synthesis in materials chemistry obey a power law?

Finding examples where experimental measurements have been repeated is a powerful strategy for assessing reproducibility of scientific data. Here, we collect quantitative data to assess how often synthesis of a newly reported material is repeated in the scientific literature. We present a simple power-law model for the frequency of repeat syntheses and assess the validity of this model using a specific class of materials, metal-organic frameworks (MOFs). Our data suggest that a power law describes the frequency of repeat synthesis of many MOFs but that a small number of "supermaterials" exist that have been replicated many times more than a power law would predict. Our results also hint that there are many repeat syntheses that have been performed but not reported in the literature, which suggests simple steps that could be taken to greatly increase the number of reports of replicate experiments in materials chemistry.

Accelerating Solvent Selection for Type II Porous Liquids.

Type II porous liquids, comprising intrinsically porous molecules dissolved in a liquid solvent, potentially combine the adsorption properties of porous adsorbents with the handling advantages of liquids. Previously, discovery of appropriate solvents to make porous liquids had been limited to direct experimental tests. We demonstrate an efficient screening approach for this task that uses COSMO-RS calculations, predictions of solvent pKa values from a machine-learning model, and several other features and apply this approach to select solvents from a library of more than 11,000 compounds. This method is shown to give qualitative agreement with experimental observations for two molecular cages, CC13 and TG-TFB-CHEDA, identifying solvents with higher solubility for these molecules than had previously been known. Ultimately, the algorithm streamlines the downselection of suitable solvents for porous organic cages to enable more rapid discovery of Type II porous liquids.

Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal-organic frameworks.

Energy-related descriptors in machine learning are a promising strategy to predict adsorption properties of metal-organic frameworks (MOFs) in the low-pressure regime. Interactions between hosts and guests in these systems are typically expressed as a sum of dispersion and electrostatic potentials. The energy landscape of dispersion potentials plays a crucial role in defining Henry's constants for simple probe molecules in MOFs. To incorporate more information about this energy landscape, we introduce the Gaussian-approximated Lennard-Jones (GALJ) potential, which fits pairwise Lennard-Jones potentials with multiple Gaussians by varying their heights and widths. The GALJ approach is capable of replicating information that can be obtained from the original LJ potentials and enables efficient development of Gaussian integral (GI) descriptors that account for spatial correlations in the dispersion energy environment. GI descriptors would be computationally inconvenient to compute using the usual direct evaluation of the dispersion potential energy surface. We show that these new GI descriptors lead to improvement in ML predictions of Henry's constants for a diverse set of adsorbates in MOFs compared to previous approaches to this task.

Impact of intrinsic framework flexibility for selective adsorption of sarin in non-aqueous solvents using metal-organic frameworks.

Molecular modeling of mixture adsorption in nanoporous materials can provide insight into the molecular-level details that underlie adsorptive separations. Modeling of adsorption often employs a rigid framework approximation for computational convenience. All real materials, however, have intrinsic flexibility due to thermal vibrations of their atoms. In this article, we examine quantitative predictions of the adsorption selectivity for a dilute concentration of a chemical warfare agent, sarin, from bulk mixtures with aqueous and non-aqueous (methanol, isopropyl alcohol) solvents using metal-organic frameworks (MOFs). These predictions were made in MOFs approximated as rigid and also in MOFs allowed to have intrinsic flexibility. Including framework flexibility appears to have important consequences for quantitative predictions of adsorption selectivity, particularly for sarin/water mixtures. Our observations suggest the intrinsic flexibility of MOFs can have a nontrivial impact on adsorption modeling of molecular mixtures, especially for mixtures containing polar species and molecules of different sizes.

Structural and Mechanistic Differences in Mixed-Linker Zeolitic Imidazolate Framework Synthesis by Solvent Assisted Linker Exchange and de Novo Routes.

Mixed-linker zeolitic imidazolate frameworks (ZIFs) are a subclass of metal-organic frameworks (MOFs) amenable to significant property tuning by altering the functional groups on the imidazolate linkers. Solvent assisted linker exchange (SALE) and de novo synthesis of mixed-linker ZIFs have been demonstrated, but the differences in structural properties-most importantly the linker distributions-and synthesis mechanisms of these two different types of hybrid ZIFs are unknown. In this work, a combination of 1H NMR combined rotation and multiple pulse spectroscopy (CRAMPS), water adsorption, and nitrogen measurements reveal distinct differences in linker mixing between SALE and de novo ZIF-8-90 hybrids. Native-fluorescence confocal microscopy is shown to provide a direct means to visualize these differences. The effects of crystal size, temperature, and SALE duration were studied in detail, and a generalizable mechanism for SALE processes in ZIFs is proposed. The SALE process is found to follow a diffusion-limited behavior leading to core-shell morphologies. Under harsher SALE conditions, deviations from diffusion-limited behavior are found due to etching and partial dissolution of the initial ZIF-8 crystals. With the selection of appropriate reaction conditions, SALE processes appear to be capable of generating controlled core-shell ZIF structures of good morphological quality that complement the well-mixed structures obtained by de novo methods.

Lattice-Gas Modeling of Adsorbate Diffusion in Mixed-Linker Zeolitic Imidazolate Frameworks: Effect of Local Imidazolate Ordering.

The rates of adsorbate diffusion in zeolitic imidazolate frameworks (ZIFs) can be varied by several orders of magnitude by incorporating two different imidazolate linkers in the ZIF crystals. Although some prior measurements of short-range order in these mixed-linker materials have been reported, it is unclear how this short-range order impacts the net diffusion of adsorbates. We introduce a lattice diffusion model that treats diffusion in ZIF-8x-90100-x crystals as a series of activated hops between cages, allowing us to assess the effects of short-range imidazolate order on molecular diffusion.

Structure Elucidation of Mixed-Linker Zeolitic Imidazolate Frameworks by Solid-State (1)H CRAMPS NMR Spectroscopy and Computational Modeling.

Mixed-linker zeolitic imidazolate frameworks (ZIFs) are nanoporous materials that exhibit continuous and controllable tunability of properties like effective pore size, hydrophobicity, and organophilicity. The structure of mixed-linker ZIFs has been studied on macroscopic scales using gravimetric and spectroscopic techniques. However, it has so far not been possible to obtain information on unit-cell-level linker distribution, an understanding of which is key to predicting and controlling their adsorption and diffusion properties. We demonstrate the use of (1)H combined rotation and multiple pulse spectroscopy (CRAMPS) NMR spin exchange measurements in combination with computational modeling to elucidate potential structures of mixed-linker ZIFs, particularly the ZIF 8-90 series. All of the compositions studied have structures that have linkers mixed at a unit-cell-level as opposed to separated or highly clustered phases within the same crystal. Direct experimental observations of linker mixing were accomplished by measuring the proton spin exchange behavior between functional groups on the linkers. The data were then fitted to a kinetic spin exchange model using proton positions from candidate mixed-linker ZIF structures that were generated computationally using the short-range order (SRO) parameter as a measure of the ordering, clustering, or randomization of the linkers. The present method offers the advantages of sensitivity without requiring isotope enrichment, a straightforward NMR pulse sequence, and an analysis framework that allows one to relate spin diffusion behavior to proposed atomic positions. We find that structures close to equimolar composition of the two linkers show a greater tendency for linker clustering than what would be predicted based on random models. Using computational modeling we have also shown how the window-type distribution in experimentally synthesized mixed-linker ZIF-8-90 materials varies as a function of their composition. The structural information thus obtained can be further used for predicting, screening, or understanding the tunable adsorption and diffusion behavior of mixed-linker ZIFs, for which the knowledge of linker distributions in the framework is expected to be important.

Engineering Porous Organic Cage Crystals with Increased Acid Gas Resistance.

Both known and new CC3-based porous organic cages are prepared and exposed to acidic SO2 in vapor and liquid conditions. Distinct differences in the stability of the CC3 cages exist depending on the chirality of the diamine linkers used. The acid catalyzed CC3 degradation mechanism is probed via in situ IR and a degradation pathway is proposed and supported with computational results. CC3 crystals synthesized with racemic mixtures of diaminocyclohexane exhibited enhanced stability compared to CC3-R and CC3-S. Confocal fluorescent microscope images reveal that the stability difference in CC3 species originates from an abundance of mesoporous grain boundaries in CC3-R and CC3-S, allowing facile access of aqueous SO2 throughout the crystal, promoting decomposition. These grain boundaries are absent from CC3 crystals made with racemic linkers.

Temperature and Loading-Dependent Diffusion of Light Hydrocarbons in ZIF-8 as Predicted Through Fully Flexible Molecular Simulations.

Accurate and efficient predictions of hydrocarbon diffusivities in zeolitic imidazolate frameworks (ZIFs) are challenging, due to the small pore size of materials such as ZIF-8 and the wide range of diffusion time scales of hydrocarbon molecules in ZIFs. Here we have computationally measured the hopping rates of 15 different molecules (kinetic diameters of 2.66-5.10 Å) in ZIF-8 via dynamically corrected transition state theory (dcTST). Umbrella sampling combined with the one-dimensional weighted histogram analysis method (WHAM) was used to calculate the diffusion free energy barriers. Both the umbrella sampling and dynamical correction calculations included ZIF-8 flexibility, which is found to be critical in accurately describing molecular diffusion in this material. Comparison of the computed diffusivities to extant experimental results shows remarkable agreement within an order of magnitude for all the molecules. The dcTST method was also applied to study the effect of hydrocarbon loadings. Self and transport diffusion coefficients of methane, ethane, ethylene, propane, propylene, n-butane, and 1-butene in ZIF-8 are reported over a temperature range of 0-150 °C and loadings from infinite dilution to liquid-like loadings.

Fluorinated carbide-derived carbon: more hydrophilic, yet apparently more hydrophobic.

We explore the effect of fluorine doping on hydrophobicity of nanoporous silicon carbide-derived carbon (SiCDC), and investigate the underlying barriers for adsorption and diffusion of water vapor and CO2 in the fluorinated and nonfluorinated structures. We develop atomistic models of fluorine-doped SiCDC at three different levels of fluorination, based on a hybrid reverse Monte Carlo constructed model of SiCDC, and develop a novel first-principles force field for the simulation of adsorption and transport of water and CO2 in the fluorine-doped carbon materials. We demonstrate an apparent dual effect of fluorination, showing that while fluorination generates more hydrophilic carbon surfaces, they actually act as more hydrophobic structures due to enhanced energy barriers in the disordered network of microporous carbon. While an increase in adsorption energy and in water uptake is seen for fluorine-doped carbon, large internal free energy barriers as well as the results of MD simulations demonstrate that the increased adsorption is kinetically limited and not experimentally observable on practical time scales. We show that an increase in apparent hydrophobicity due to fluorination is mediated by larger free energy barriers arising from stronger binding of fluid molecules inside the pore network, as opposed to repulsion or steric hindrance to the diffusion of molecules through narrow pore entries. For carbon dioxide, adsorption enthalpies and activation energy barriers are both decreased on fluorination, indicating weakened solid-fluid binding energies in the fluorinated systems.

Highly tunable molecular sieving and adsorption properties of mixed-linker zeolitic imidazolate frameworks.

Nanoporous zeolitic imidazolate frameworks (ZIFs) form structural topologies equivalent to zeolites. ZIFs containing only one type of imidazole linker show separation capability for limited molecular pairs. We show that the effective pore size, hydrophilicity, and organophilicity of ZIFs can be continuously and drastically tuned using mixed-linker ZIFs containing two types of linkers, allowing their use as a more general molecular separation platform. We illustrate this remarkable behavior by adsorption and diffusion measurements of hydrocarbons, alcohols, and water in mixed-linker ZIF-8(x)-90(100-x) materials with a large range of crystal sizes (338 nm to 120 µm), using volumetric, gravimetric, and PFG-NMR methods. NMR, powder FT-Raman, and micro-Raman spectroscopy unambiguously confirm the mixed-linker nature of individual ZIF crystals. Variation of the mixed-linker composition parameter (x) allows continuous control of n-butane, i-butane, butanol, and isobutanol diffusivities over 2-3 orders of magnitude and control of water and alcohol adsorption especially at low activities.

Powered by DFT: Screening methods that accelerate materials development for hydrogen in metals applications.

CONSPECTUS: Not only is hydrogen critical for current chemical and refining processes, it is also projected to be an important energy carrier for future green energy systems such as fuel cell vehicles. Scientists have examined light metal hydrides for this purpose, which need to have both good thermodynamic properties and fast charging/discharging kinetics. The properties of hydrogen in metals are also important in the development of membranes for hydrogen purification. In this Account, we highlight our recent work aimed at the large scale screening of metal-based systems with either favorable hydrogen capacities and thermodynamics for hydrogen storage in metal hydrides for use in onboard fuel cell vehicles or promising hydrogen permeabilities relative to pure Pd for hydrogen separation from high temperature mixed gas streams using dense metal membranes. Previously, chemists have found that the metal hydrides need to hit a stability sweet spot: if the compound is too stable, it will not release enough hydrogen under low temperatures; if the compound is too unstable, the reaction may not be reversible under practical conditions. Fortunately, we can use DFT-based methods to assess this stability via prediction of thermodynamic properties, equilibrium reaction pathways, and phase diagrams for candidate metal hydride systems with reasonable accuracy using only proposed crystal structures and compositions as inputs. We have efficiently screened millions of mixtures of pure metals, metal hydrides, and alloys to identify promising reaction schemes via the grand canonical linear programming method. Pure Pd and Pd-based membranes have ideal hydrogen selectivities over other gases but suffer shortcomings such as sensitivity to sulfur poisoning and hydrogen embrittlement. Using a combination of detailed DFT, Monte Carlo techniques, and simplified models, we are able to accurately predict hydrogen permeabilities of metal membranes and screen large libraries of candidate alloys, selections of which are described in this Account. To further increase the number of membrane materials that can be studied with DFT, computational costs need to be reduced either through methods development to break bottlenecks in the performance prediction algorithm, particularly related to transition state identification, or through screening techniques that take advantage of correlations to bypass constraints.

DFT-Derived Force Fields for Modeling Hydrocarbon Adsorption in MIL-47(V).

Generic force fields such as UFF and DREIDING are widely used for predicting molecular adsorption and diffusion in metal-organic frameworks (MOFs), but the accuracy of these force fields is unclear. We describe a general framework for developing transferable force fields for modeling the adsorption of alkanes in a nonflexible MIL-47(V) MOF using periodic density functional theory (DFT) calculations. By calculating the interaction energies for a large number of energetically favorable adsorbate configurations using DFT, we obtain a force field that gives good predictions of adsorption isotherms, heats of adsorption, and diffusion properties for a wide range of alkanes and alkenes in MIL-47(V). The force field is shown to be transferable to related materials such as MIL-53(Cr) and is used to calculate the free-energy differences for the experimentally observed phases of MIL-53(Fe).

Impact of branching on the supramolecular assembly of thioethers on Au(111).

Alkanethiolate monolayers are one of the most comprehensively studied self-assembled systems due to their ease of preparation, their ability to be functionalized, and the opportunity to control their thickness perpendicular to the surface. However, these systems suffer from degradation due to oxidation and defects caused by surface etching and adsorbate rotational boundaries. Thioethers offer a potential alternative to thiols that overcome some of these issues and allow dimensional control of self-assembly parallel to the surface. Thioethers have found uses in surface modification of nanoparticles, and chiral thioethers tethered to catalytically active surfaces have been shown to enable enantioselective hydrogenation. However, the effect of structural, chemical, and chiral modifications of the alkyl chains of thioethers on their self-assembly has remained largely unstudied. To elucidate how molecular structure, particularly alkyl branching and chirality, affects molecular self-assembly, we compare four related thioethers, including two pairs of structural isomers. The self-assembly of structural isomers N-butyl methyl sulfide and tert-butyl methyl sulfide was studied with high resolution scanning tunneling microscopy (STM); our results indicate that both molecules form highly ordered arrays despite the bulky tert-butyl group. We also investigated the effect of intrinsic chirality in the alkyl tails on the adsorption and self-assembly of butyl sec-butyl sulfide (BSBS) with STM and density functional theory and contrast our results to its structural isomer, dibutyl sulfide. Calculations provide the relative stability of the four stereoisomers of BSBS and STM imaging reveals two prominent monomer forms. Interestingly, the racemic mixture of BSBS is the only thioether we have examined to date that does not form highly ordered arrays; we postulate that this is due to weak enantiospecific intermolecular interactions that lead to the formation of energetically similar but structurally different assemblies. Furthermore, we studied all of the molecules in their monomeric molecular rotor form, and the surface-adsorbed chirality of the three asymmetric thioethers is distinguishable in STM images.

First-principles prediction of new complex transition metal hydrides for high temperature applications.

Metal hydrides with high thermodynamic stability are desirable for high-temperature applications, such as those that require high hydrogen release temperatures or low hydrogen overpressures. First-principles calculations have been used previously to identify complex transition metal hydrides (CTMHs) for high temperature use by screening materials with experimentally known structures. Here, we extend our previous screening of CTMHs with a library of 149 proposed materials based on known prototype structures and charge balancing rules. These proposed materials are typically related to known materials by cation substitution. Our semiautomated, high-throughput screening uses density functional theory (DFT) and grand canonical linear programming (GCLP) methods to compute thermodynamic properties and phase diagrams: 81 of the 149 materials are found to be thermodynamically stable. We identified seven proposed materials that release hydrogen at higher temperatures than the associated binary hydrides and at high temperature, T > 1000 K, for 1 bar H2 overpressure. Our results indicate that there are many novel CTMH compounds that are thermodynamically stable, and the computed thermodynamic data and phase diagrams should be useful for selecting materials and operating parameters for high temperature metal hydride applications.

First-principles screening of complex transition metal hydrides for high temperature applications.

Metal hydrides with enhanced thermodynamic stability with respect to the associated binary hydrides are useful for high temperature applications in which highly stable materials with low hydrogen overpressures are desired. Though several examples of complex transition metal hydrides (CTMHs) with such enhanced stability are known, little thermodynamic or phase stability information is available for this materials class. In this work, we use semiautomated thermodynamic and phase diagram calculations based on density functional theory (DFT) and grand canonical linear programming (GCLP) methods to screen 102 ternary and quaternary CTMHs and 26 ternary saline hydrides in a library of over 260 metals, intermetallics, binary, and higher hydrides to identify materials that release hydrogen at higher temperatures than the associated binary hydrides and at elevated temperatures, T > 1000 K, for 1 bar H2 overpressure. For computational efficiency, we employ a tiered screening approach based first on solid phase ground state energies with temperature effects controlled via H2 gas alone and second on the inclusion of phonon calculations that correct solid phase free energies for temperature-dependent vibrational contributions. We successfully identified 13 candidate CTMHs including Eu2RuH6, Yb2RuH6, Ca2RuH6, Ca2OsH6, Ba2RuH6, Ba3Ir2H12, Li4RhH4, NaPd3H2, Cs2PtH4, K2PtH4, Cs3PtH5, Cs3PdH3, and Rb2PtH4. The most stable CTMHs tend to crystallize in the Sr2RuH6 cubic prototype structure and decompose to the pure elements and hydrogen rather than to intermetallic phases.

First principles studies of proton conduction in KTaO3.

KTaO3 (KTO) is a useful prototypical perovskite for examining the mechanisms of proton transport in perovskites. Previously, Gomez et al. [J. Chem. Phys. 126, 194701 (2007)] reported density functional theory (DFT) calculations describing proton hopping in defect-free KTO. We use DFT calculations to extend that work in two directions, namely, understanding isotope effects in low and high temperature proton transport and the role of native point defects in KTO. At cryogenic temperatures, quantum tunneling plays a vital role in the net hopping of protons in KTO. At the elevated temperature characteristic of applications involving proton-conducting perovskites, tunneling is negligible but zero point energy effects still lead to non-negligible isotope effects for H(+), D(+), and T(+). We also use DFT to characterize the populations of relevant point defects in KTO as a function of experimental conditions, and to examine the migration of protons that are close in proximity to these defects. This information gives useful insight into the overall transport rates of protons through KTO under a variety of external environments. We also assess the overall diffusivity of protons in KTO at various ranges of oxygen vacancy concentrations by performing kinetic Monte Carlo simulations.

Assessing Impacts of Atmospheric Conditions on Efficiency and Siting of Large-Scale Direct Air Capture Facilities.

The cost and efficiency of direct air capture (DAC) of carbon dioxide (CO2) will be decisive in determining whether this technology can play a large role in decarbonization. To probe the role of meteorological conditions on DAC we examine, at 1 × 1° resolution for the continental United States (U.S.), the impacts of temperature, humidity, atmospheric pressure, and CO2 concentration for a representative amine-based adsorption process. Spatial and temporal variations in atmospheric pressure and CO2 concentration lead to strong variations in the CO2 available in ambient air across the U.S. The specific DAC process that we examine is described by a process model that accounts for both temperature and humidity. A process that assumes the same operating choices at all locations in the continental U.S. shows strong variations in performance, with the most influential variables being the H2O gas phase volume fraction and temperature, both of which are negatively correlated with DAC productivity for the specific process that we consider. The process also shows a moderate positive correlation of ambient CO2 with productivity and recovery. We show that optimizing the DAC process at seven representative locations to reflect temporal and spatial variations in ambient conditions significantly improves the process performance and, more importantly, would lead to different choices in the sites for the best performance than models based on a single set of process conditions. Our work provides a framework for assessing spatial variations in DAC performance that could be applied to any DAC process and indicates that these variations will have important implications in optimizing and siting DAC facilities.