6 Materialchemie
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We demonstrate a strategy for simulating wide-range X-ray scattering patterns, which spans the small- and wide scattering angles as well as the scattering angles typically used for Pair Distribution Function (PDF) analysis. Such simulated patterns can be used to test holistic analysis models, and, since the diffraction intensity is on the same scale as the scattering intensity, may offer a novel pathway for determining the degree of crystallinity.
The "Ultima Ratio" strategy is demonstrated on a 64-nm Metal Organic Framework (MOF) particle, calculated from Q < 0.01 1/nm up to Q < 150 1/nm, with a resolution of 0.16 Angstrom. The computations exploit a modified 3D Fast Fourier Transform (3D-FFT), whose modifications enable the transformations of matrices at least up to 8000^3 voxels in size. Multiple of these modified 3D-FFTs are combined to improve the low-Q behaviour. The resulting curve is compared to a wide-range scattering pattern measured on a polydisperse MOF powder. While computationally intensive, the approach is expected to be useful for simulating scattering from a wide range of realistic, complex structures, from (poly-)crystalline particles to hierarchical, multicomponent structures such as viruses and catalysts.
A novel cop olyme r based on supramolecular motif2,6-diaminopyridin e and water-soluble acrylamide, poly[N-(6-ace tamidopyridin-2-yl) acrylamide-co-acrylamide], was synthe-size d via rev ersible addi tion–fragmentation chain transfer (RAFT)polymerization with various monomer compositions. The thermo-respon sive behavior of the copolymers was studied by turbidime-try and dynamic light scattering (DLS). The obtained copolymersshowed an upper critical solution temperature (UCST)-typ e phasetransition behavior in water and electrolyte solution. The phasetransition temperature was found to increase with decreasingam ount of acrylamide in the copolymer and increasing concentra-tion of the solution. Furth ermore, the phase transition temperatureva ried in aqueous solutions of electrolytes according to the naturean d concentration of the electrolyte in accordance with theHoffmeister series. A dramatic solvent isotope effect on thetransition temperature was o bserved in this study, as the transitiontemperature was almost 10–12C higher in D2OthaninH2Oatthesame concentration and acrylamide co mposition. The size of theaggregates below the transition temperature was larger in D2Ocompared to that in H2O that can be explained by deuterium iso-tope effect. The thermoresponsive behavior of the copolymers wasalso investigated in different cell medium and found to be exhibitedUCST-type phase transition behavior in different cell medium.Such behavior of the copo lyme rs can be useful in many a pplica-tions including biomedical, microfluidics, optical materials, and indrug delivery.
Lake Magadi, East African Rift Valley, is a hyperalkaline and saline soda lake highly enriched in Na+, K+, CO32–, Cl–, HCO3–, and SiO2 and depleted in Ca2+ and Mg2+, where thick evaporite deposits and siliceous sediments have been forming for 100 000 years. The hydrogeochemistry and the evaporite deposits of soda lakes are subjects of growing interest in paleoclimatology, astrobiology, and planetary sciences. In Lake Magadi, different hydrates of sodium carbonate/bicarbonate and other saline minerals precipitate. The precipitation sequence of these minerals is a key for understanding the hydrochemical evolution, the paleoenvironmental conditions of ancient evaporite deposits, and industrial crystallization. However, accurate determination of the precipitation sequence of these minerals was challenging due to the dependency of the different hydrates on temperature, water activity, pH and pCO2, which could induce phase transformation and secondary mineral precipitation during sample handling. Here, we report a comprehensive methodology applied for monitoring the evaporitic mineral precipitation and hydrochemical evolution of Lake Magadi. Evaporation and mineral precipitations were monitored by using in situ video microscopy and synchrotron X-ray diffraction of acoustically levitated droplets. The mineral patterns were characterized by ex situ Raman spectroscopy, X-ray diffraction, and scanning electron microscopy. Experiments were coupled with thermodynamic models to understand the evaporation and precipitation-driven hydrochemical evolution of brines. Our results closely reproduced the mineral assemblages, patterns, and textural relations observed in the natural setting. Alkaline earth carbonates and fluorite were predicted to precipitate first followed by siliceous sediments. Among the salts, dendritic and acicular trona precipitate first via fractional crystallization─reminiscent of grasslike trona layers of Lake Magadi. Halite/villiaumite, thermonatrite, and sylvite precipitate sequentially after trona from residual brines depleted in HCO3–. The precipitation of these minerals between trona crystals resembles the precipitation process observed in the interstitial brines of the trona layers. Thermonatrite precipitation began after trona equilibrated with the residual brines due to the absence of excess CO2 input. We have shown that evaporation and mineral precipitation are the major drivers for the formation of hyperalkaline, saline, and SiO2-rich brines. The discrepancy between predicted and actual sulfate and phosphate ion concentrations implies the biological cycling of these ions. The combination of different in situ and ex situ methods and modeling is key to understanding the mineral phases, precipitation sequences, and textural relations of modern and ancient evaporite deposits. The synergy of these methods could be applicable in industrial crystallization and natural brines to reconstruct the hydrogeochemical and hydroclimatic conditions of soda lakes, evaporite settings, and potentially soda oceans of early Earth and extraterrestrial planets.
Physical adsorption at cryogenic temperature (cryoadsorption) is a reversible mechanism that can reduce the pressure of conventional compressed gas storage systems. Metal–organic framework (MOF) materials are remarkable candidates due to the combination of high specific surface area and density which, in some cases, provide a high volumetric storage capacity. However, such extensive use of MOFs for this application requires the selection of affordable structures, easy to produce and made from feasible metallic and organic components. Herein, we introduce a MOF database detailing the crystallographic and porous properties of 3600 existing MOFs made from industrially relevant metals and their organic composition. The comparison of the available minimum costs of linkers allowed the creation of a database to select affordable structures with high potential for volumetric hydrogen storage by cryoadsorption, considering their composition based on individual or mixed building blocks. A user interface, available online, facilitates the selection of MOFs based on the properties or names of structures and linkers.
An in-depth insight into the chemistry and nature of the individual chemical bonds is essential for understanding materials. Bonding analysis is thus expected to provide important features for large-scale data analysis and machine learning of material properties. Such chemical bonding information can be computed using the LOBSTER software package, which post-processes modern density functional theory data by projecting the plane wave-based wave functions onto an atomic orbital basis. With the help of a fully automatic workflow, the VASP and LOBSTER software packages are used to generate the data. We then perform bonding analyses on 1520 compounds (insulators and semiconductors) and provide the results as a database. The projected densities of states and bonding indicators are benchmarked on standard density-functional theory computations and available heuristics, respectively. Lastly, we illustrate the predictive power of bonding descriptors by constructing a machine learning model for phononic properties, which shows an increase in prediction accuracies by 27% (mean absolute errors) compared to a benchmark model differing only by not relying on any quantum-chemical bonding features.
The debate on the mechanisms which underpin mechanochemical reactions via ball mill grinding is still open. Our ability to accurately measure the microstructural (crystal size and microstrain) evolution of materials under milling conditions as well as their phase composition as a function of time is key to the in-depth understanding of the kinetics and driving forces of mechanochemical transformations. Furthermore, all ball milling reactions end with a steady state or milling equilibrium – represented by a specific phase composition and relative microstructure – that does not change as long as the milling conditions are maintained. The use of a standard sample is essential to determine the instrumental contribution to the X-ray powder diffraction (XRPD) peak broadening for time-resolved in situ (TRIS) monitoring of mechanochemical reactions under in operando conditions. Using TRIS-XRPD on a ball milling setup, coupled with low-energy synchrotron radiation, we investigated different data acquisition and analysis strategies on a silicon standard powder. The diffraction geometry and the microstructural evolution of the standard itself have been studied to model the instrumental contribution to XRPD peak broadening throughout the grinding activity. Previously proposed functions are here challenged and further developed. Importantly, we show that minor drifts of the jar position do not affect the instrumental resolution function significantly. We here report and discuss the results of such investigations and their application to TRIS-XRPD datasets of inorganic and organic ball mill grinding reactions.
Flexible organic crystals (elastic and plastic) are important materials for optical waveguides, tunable optoelectronic devices, and photonic integrated circuits. Here, we present highly elastic organic crystals of a Schiff base, 1-((E)-(2,5-dichlorophenylimino)methyl)naphthalen-2-ol (1), and an azine molecule, 2,4-dibromo-6-((E)-((E)-(2,6-dichlorobenzylidene)hydrazono)methyl)phenol (2). These microcrystals are highly flexible under external mechanical force, both in the macroscopic and the microscopic regimes. The mechanical flexibility of these crystals arises as a result of weak and dispersive C−H⋅⋅⋅Cl, Cl⋅⋅⋅Cl, Br⋅⋅⋅Br, and π⋅⋅⋅π stacking interactions. Singly and doubly-bent geometries were achieved from their straight shape by a micromechanical approach using the AFM cantilever tip. Crystals of molecules 1 and 2 display a bright-green and red fluorescence (FL), respectively, and selective reabsorption of a part of their FL band. Crystals 1 and 2 exhibit optical-path-dependent low loss emissions at the termini of crystal in their straight and even in extremely bent geometries. Interestingly, the excitation position-dependent optical modes appear in both linear and bent waveguides of crystals 1 and 2, confirming their light-trapping ability.
Mechanically flexible single crystals of molecular materials offer potential for a multitude of new directions in advanced materials design. Before the full potential of such materials can be exploited, insight into their mechanisms of action must be better understood. Such insight can be only obtained through synergistic use of advanced experimentation and simulation. We herein report the first detailed mechanistic study of elasto-plastic flexibility in a molecular solid. An atomistic origin for this mechanical behaviour is proposed through a combination of atomic force microscopy, μ-focus synchrotron X-ray diffraction, Raman spectroscopy, ab initio simulation, and computed elastic tensors. Our findings suggest that elastic and plastic bending are intimately linked and result from extensions of the same molecular deformations. The proposed mechanism bridges the gap between contested mechanisms, suggesting its applicability as a general mechanism for elastic and plastic bending in organic molecular crystals.
Automated bonding analysis software has been developed based on Crystal Orbital Hamilton Populations to facilitate high-throughput bonding analysis and machine-learning of bonding features. This work presents the software and discusses its applications to simple and complex materials such as GaN, NaCl, the oxynitrides XTaO2N (X=Ca, Ba, Sr) and Yb14Mn1Sb11.
Automation simplifies the use of computational materials science software and makes it accessible to a wide range of users. This enables high-throughput calcula-tionsand makesiteasier for non-specialists to enter computational materials science. However, in-creasing automation also poses threats that should be considered while interacting with automated procedures.