Inorganic-organic hybrid materials such as organically templated metal oxides, metal-organic frameworks (MOFs) and organohalide perovskites have been studied for decades, and hydrothermal and (non-aqueous) solvothermal syntheses have produced thousands of new materials that collectively contain nearly all the metals in the periodic table. Nevertheless, the formation of these compounds is not fully understood, and development of new compounds relies primarily on exploratory syntheses. Simulation- and data-driven approaches (promoted by efforts such as the Materials Genome Initiative) provide an alternative to experimental trial-and-error. Three major strategies are: simulation-based predictions of physical properties (for example, charge mobility, photovoltaic properties, gas adsorption capacity or lithium-ion intercalation) to identify promising target candidates for synthetic efforts; determination of the structure-property relationship from large bodies of experimental data, enabled by integration with high-throughput synthesis and measurement tools; and clustering on the basis of similar crystallographic structure (for example, zeolite structure classification or gas adsorption properties). Here we demonstrate an alternative approach that uses machine-learning algorithms trained on reaction data to predict reaction outcomes for the crystallization of templated vanadium selenites. We used information on 'dark' reactions--failed or unsuccessful hydrothermal syntheses--collected from archived laboratory notebooks from our laboratory, and added physicochemical property descriptions to the raw notebook information using cheminformatics techniques. We used the resulting data to train a machine-learning model to predict reaction success. When carrying out hydrothermal synthesis experiments using previously untested, commercially available organic building blocks, our machine-learning model outperformed traditional human strategies, and successfully predicted conditions for new organically templated inorganic product formation with a success rate of 89 per cent. Inverting the machine-learning model reveals new hypotheses regarding the conditions for successful product formation.

No abstract

The development of materials that reversibly store high densities of thermal energy is critical to the more efficient and sustainable utilization of energy. Herein, we investigate metal− organic compounds as a new class of solid−liquid phase-change materials (PCMs) for thermal energy storage. Specifically, we show that isostructural series of divalent metal amide complexes featuring extended hydrogen bond networks can undergo tunable, high-enthalpy melting transitions over a wide temperature range. Moreover, these coordination compounds provide a powerful platform to explore the specific factors that contribute to the energy density and entropy of metal−organic PCMs. Through a systematic analysis of the structural and thermochemical properties of these compounds, we investigated the influence of coordination bonds, hydrogen-bond networks, neutral organic ligands, and outer-sphere anions on their phase-change thermodynamics. In particular, we identify the importance of high densities of coordination bonds and hydrogen bonds to achieving a high PCM energy density, and we show how metal-dependent changes to the local coordination environment during melting impact the entropy and enthalpy of metal−organic PCMs. These results highlight the potential of manipulating order− disorder phase transitions in metal−organic materials for thermal energy storage.

Understanding the factors that govern gas absorption in ionic liquids is critical to the development of high-capacity solvents for catalysis, electrochemistry, and gas separations. Here, we report experimental probes of liquid structure that provide insights into how free volume impacts the O2 absorption properties of ionic liquids. Specifically, we establish that isothermal compressibilitymeasured rapidly and accurately through small-angle X-ray scatteringreports on the size distribution of transient voids within a representative series of ionic liquids and is correlated with O2 absorption capacity. Additionally, O2 absorption capacities are correlated with thermal expansion coefficients, reflecting the beneficial effect of weak intermolecular interactions in ionic liquids on free volume and gas absorption capacity. Molecular dynamics simulations show that the void size distributionin particular, the probability of forming larger voids within an ionic liquidhas a greater impact on O2 absorption than the total free volume. These results establish relationships between the ionic liquid structure and gas absorption properties that offer design strategies for ionic liquids with high gas solubilities.

Owing to their high tunability and predictable structures, metal−organic materials offer a powerful platform to study glass formation and crystallization processes and to design glasses with unique properties. Here, we report a novel series of glass-forming metal−ethylenebis(acetamide) networks that undergo reversible glass and crystallization transitions below 200 °C. The glass-transition temperatures, crystallization kinetics, and glass stability of these materials are readily tunable, either by synthetic modification or by liquid-phase blending, to form binary glasses. Pair distribution function (PDF) analysis reveals extended structural correlations in both single and binary metal−bis-(acetamide) glasses and highlights the important role of metal− metal correlations during structural evolution across glass−crystal transitions. Notably, the glass and crystalline phases of a Co− ethylenebis(acetamide) binary network feature a large reflectivity contrast ratio of 4.8 that results from changes in the local coordination environment around Co centers. These results provide new insights into glass−crystal transitions in metal−organic materials and have exciting implications for optical switching, rewritable data storage, and functional glass ceramics.

No abstract

The unique chemistry of fluorocarbons (in particular, their weak intermolecular interactions and high degree of intrinsic free volume) makes them promising building blocks for ionic liquids with high gas capacities. Here, we report a generalizable method for the synthesis of fluorinated ionic liquids, which relies on the evolution of gaseous byproducts to drive product formation. This synthetic strategy overcomes solubility challenges that can hinder the synthesis of highly fluorinated ionic liquids via conventional methods and enables a systematic investigation of the effect of fluorination on ionic liquid viscosity and gas solubility.