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Combinatorial Al 1− x Sc x N library decouples composition, crystal structure, and ferroelectric properties. The local chemical bonding is the key factor to control ferroelectric properties rather than extended crystal structure.
The ion figuring system at the Marshall Space Flight Center has been successfully used for at least three previous investigations into the ion milling of metals. The research was directed toward improving the surface quality of X-ray directing optics. These studies were performed on surfaces that were already hand polished to an excellent surface quality and were intended to remove the residual unwanted figure left by those techniques. The ion milling was typically carried out on test surfaces or mandrels that were several centimeters in width and length. The good thermal conductivity of the metal samples allowed the ion beam to be directed onto the sample for an indefinite period of time. This is not true of sapphire or most electrical insulators and problems have arisen in recent attempts to ion mill thin samples of sapphire. The failure and fracture of the material was likely due to thermal stresses and the relatively low thermal conductivity of sapphire (compared to most metals), These assumed stresses actually provided the key as to how they might be monitored. A thermal gradient in the sapphire sample will induce an effective index of refraction change and because of the shape constraint and the crystal structure and simple thermal expansion, this index change will be nonuniform across the sample. In all but simple cubic crystal structures, this leads to a spatially nonuniform optical retardance induced on any polarized optical beam traversing the sample, and it is this retardance that can be monitored using standard polarimetric procedures.
The first important step in a structure-based virtual screening is the judicious selection of a receptor protein. In cases where the holo protein receptor structure is unavailable, significant reduction in virtual screening performance has been reported. In this work, we present a robust method to generate reliable holo protein structure conformations from apo structures using molecular dynamics (MD) simulation with restraints derived from holo structure binding-site templates. We perform benchmark tests on two different datasets: 40 structures from a directory of useful decoy-enhanced (DUD-E) and 84 structures from the Gunasekaran dataset. Our results show successful refinement of apo binding-site structures toward holo conformations in 82% of the test cases. In addition, virtual screening performance of 40 DUD-E structures is significantly improved using our MD-refined structures as receptors with an average enrichment factor (EF), an EF1% value of 6.2 compared to apo structures with 3.5. Docking of native ligands to the refined structures shows an average ligand root mean square deviation (RMSD) of 1.97 Å (DUD-E dataset and Gunasekaran dataset) relative to ligands in the holo crystal structures, which is comparable to the self-docking (i.e., docking of the native ligand back to its crystal structure receptor) average, 1.34 Å (DUD-E dataset) and 1.36 Å (Gunasekaran dataset). On the other hand, docking to the apo structures yields an average ligand RMSD of 3.65 Å (DUD-E) and 2.90 Å (Gunasekaran). These results indicate that our method is robust and can be useful to improve virtual screening performance of apo structures.
Symmetry-adapted distortion modes provide a natural way of describing distorted structures derived from higher-symmetry parent phases. Structural refinements using symmetry-mode amplitudes as fit variables have been used for at least ten years in Rietveld refinements of the average crystal structure from diffraction data; more recently, this approach has also been used for investigations of the local structure using real-space pair distribution function (PDF) data. Here, the value of performing symmetry-mode fits to PDF data is further demonstrated through the successful application of this method to two topical materials: TiSe2, where a subtle but long-range structural distortion driven by the formation of a charge-density wave is detected, and MnTe, where a large but highly localized structural distortion is characterized in terms of symmetry-lowering displacements of the Te atoms. Here, the analysis is performed using fully open-source code within the DiffPy framework via two packages developed for this work: isopydistort, which provides a scriptable interface to the ISODISTORT web application for group theoretical calculations, and isopytools, which converts the ISODISTORT output into a DiffPy-compatible format for subsequent fitting and analysis. These developments expand the potential impact of symmetry-adapted PDF analysis by enabling high-throughput analysis and removing the need for any commercial software.
Pb–Zr–Ti–O (PZT) perovskites span a large solid-solution range and have found widespread use due to their piezoelectric and ferroelectric properties that also span a large range. Crystal structure analysis via Rietveld refinement facilitates materials analysis via the extraction of the structural parameters. These parameters, often obtained as a function of an additional dimension (e.g., pressure), can help to diagnose materials response within a use environment. Often referred to as “ in-situ ” studies, these experiments provide an abundance of data. Viewing structural changes due to applied pressure conditions can give much-needed insight into materials performance. However, challenges exist for viewing/presenting results when the details are inherently three-dimensional (3D) in nature. For PZT perovskites, the use of polyhedra (e.g., Zr/Ti–O 6 octahedra) to view bonding/connectivity is beneficial; however, the visualization of the octahedra behavior with pressure dependence is less easily demonstrated due to the complexity of the added pressure dimension. We present a more intuitive visualization by projecting structural data into virtual reality (VR). We employ previously published structural data for Pb 0.99 (Zr 0.95 Ti 0.05 ) 0.98 Nb 0.02 O 3 as an exemplar for VR visualization of the PZT R3c crystal structure between ambient and 0.62 GPa pressure. This is accomplished via our in-house CAD2VR™ software platform and the new CrystalVR plugin. The use of the VR environment enables a more intuitive viewing experience, while enabling on-the-fly evaluation of crystal data, to form a detailed and comprehensive understanding of in-situ datasets. Discussion of methodology and tools for viewing are given, along with how recording results in video form can enable the viewing experience.
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Chalcogenides in perovskite and the related layered Ruddlesden-Popper crystal structures ( chalcogenide perovskites for brevity) are an exciting family of semiconductors but remain experimentally little studied. Chalcogenide perovskites share crystal structures and some physical properties with ionic compounds such as oxide and halide perovskites, but the metal-chalcogen bonds responsible for semiconducting behavior are substantially more covalent than in these more-studied perovskites. In this study, we use complementary experimental and theoretical methods to study how the mixed ionic-covalent Zr-S bonds support the electronic structure and physical properties of perovskite BaZrS 3 and Ruddlesden-Popper Ba 3 Zr 2 S 7 . We apply theoretical methods to assign features of experimentally measured x-ray absorption spectroscopy (XAS) to particular orbital transitions, enabling a clear physical interpretation of angle-dependent, polarized XAS data measured on single-crystal samples, and an atomistic view of the covalent bonding network that facilitates charge transport. Polarized Raman measurements identify signatures of crystalline anisotropy in Ba 3 Zr 2 S 7 and enable the first assignments of mode symmetry in this material. Infrared reflectivity reveals electronic transport properties that augur well for the use of chalcogenide perovskites in optoelectronic and energy-conversion technologies.
The honeycomb TbInO 3 has attracted wide research attention due to its fascinating physical properties. However, TbInO 3 single crystal was difficult to grow owing to the high melting point and serious volatilization of indium during the crystal growth. In this study, the volatilization of the indium element was effectively suppressed by controlling the growth atmosphere and pressure. The excess ratio of indium oxide was determined, and pure hexagonal TbInO 3 crystal was obtained by the laser floating zone method. Systematic studies on the crystal structure and optical and ferroelectric properties were carried out. The structure distortion resulted in the improper geometric ferroelectric revealed by single crystal diffraction and Raman spectrum measurements. The topological vortex domains and P-E hysteresis loop demonstrated the presence of ferroelectricity. TbInO 3 crystal has great potential application in vortex memory.
New synthetic hybrid materials and their increasing complexity have placed growing demands on crystal growth for single-crystal X-ray diffraction analysis. Unfortunately, not all chemical systems are conducive to the isolation of single crystals for traditional characterization. Here, small-molecule serial femtosecond crystallography (smSFX) at atomic resolution (0.833 Å) is employed to characterize microcrystalline silver n-alkanethiolates with various alkyl chain lengths at X-ray free electron laser facilities, resolving long-standing controversies regarding the atomic connectivity and odd–even effects of layer stacking. smSFX provides high-quality crystal structures directly from the powder of the true unknowns, a capability that is particularly useful for systems having notoriously small or defective crystals. We present crystal structures of silver n-butanethiolate (C4), silver n-hexanethiolate (C6), and silver n-nonanethiolate (C9). We show that an odd–even effect originates from the orientation of the terminal methyl group and its role in packing efficiency. We also propose a secondary odd–even effect involving multiple mosaic blocks in the crystals containing even-numbered chains, identified by selected-area electron diffraction measurements. Finally, we conclude with a discussion of the merits of the synthetic preparation for the preparation of microdiffraction specimens and compare the long-range order in these crystals to that of self-assembled monolayers.
The synthesis process is presented for experimentally simulating modifications in cosmic dust grains using sequential ion implantations or irradiations followed by thermal annealing. Cosmic silicate dust analogues were prepared via implantation of 20–80 keV Fe - , Mg - , and O - ions into commercially available p-type silicon (100)wafers. The as-implanted analogues are amorphous with a Mg/(Fe+Mg) ratio of 0.5 tailored to match theoretical abundances in circumstellar dusts. Before the ion implantations were performed, Monte-Carlo-based ion-solid interaction codes were used to model the dynamic redistribution of the implanted atoms in the silicon substrate. 600 keV helium ion irradiation was performed on one of the samples before thermal annealing. Two samples were thermally annealed at a temperature appropriate for an M-class stellar wind, 1000 K, for 8.3 h in a vacuum chamber with a pressure of 1 x 10 -7 torr. The elemental depth profiles were extracted utilizing Rutherford Backscattering Spectrometry (RBS) in the samples before and after thermal annealing. X-ray diffraction (XRD)analysis was employed for the identification of various phases in crystalline minerals in the annealed analogues. Transmission electron microscopy (TEM) analysis was utilized to identify specific crystal structures. RBS analysis shows redistribution of the implanted Fe, Mg, and O after thermal annealing due to incorporation into the crystal structures for each sample type. XRD patterns along with TEM analysis showed nanocrystalline Mg and Fe oxides with possible incorporation of additional silicate minerals.
The role of ribonucleic acid (RNA) in biology continues to grow, but insight into important aspects of RNA behavior is lacking, such as dynamic structural ensembles in different environments, how flexibility is coupled to function, and how function might be modulated by small molecule binding. In the case of proteins, much progress in these areas has been made by complementing experiments with atomistic simulations, but RNA simulation methods and force fields are less mature. It remains challenging to generate stable RNA simulations, even for small systems where well-defined, thermostable structures have been established by experiments. Further many different aspects of RNA energetics have been adjusted in force fields, seeking improvements that are transferable across a variety of RNA structural motifs. In this work, the role of weak CH···O interactions is explored, which are ubiquitous in RNA structure but have received less attention in RNA force field development. By comparing data extracted from high-resolution RNA crystal structures to energy profiles from quantum mechanics and force field calculations, it is shown that CH···O interactions are overly repulsive in the widely used Amber RNA force fields. A simple, targeted adjustment of CH···O repulsion that leaves the remainder of the force field unchanged was developed. Then, the standard and modified force fields were tested using molecular dynamics (MD) simulations with explicit water and salt, amassing over 300 μs of data for multiple RNA systems containing important features such as the presence of loops, base stacking interactions as well as canonical and noncanonical base pairing. In this work and others, standard force fields lead to reproducible unfolding of the NMR-based structures. Including a targeted CH···O adjustment in an otherwise identical protocol dramatically improves the outcome, leading to stable simulations for all RNA systems tested.
H7N9 avian influenza virus is a zoonotic influenza virus of public health concern, with a 39% mortality rate in humans. H7N9-specific prevention or treatments for humans have not been approved. We previously isolated a human monoclonal antibody (mAb) designated H7-235 that broadly reacts to diverse H7 viruses and neutralizes H7N9 viruses in vitro. Here, we report the crystal structure of H7 HA1 bound to the fragment antigen-binding region (Fab) of recombinant H7-235 (rH7-235). The crystal structure revealed that rH7-235 recognizes residues near but outside of the receptor binding site (RBS). Nevertheless, the rH7-235 IgG potently inhibits hemagglutination mediated by H7N9 viruses due to avidity effect and Fc steric hindrance. This mAb prophylactically protects mice against weight loss and death caused by challenge with lethal H7N9 viruses in vivo. rH7-235 mAb neutralizing activity alone is sufficient for protection when used at a high dose in a prophylactic setting. This study provides insights into mechanisms of viral neutralization by protective, broadly reactive anti-H7 antibodies, informing the rational design of therapeutics and vaccines against H7N9 influenza virus.
A new method for in-situ Sb doping of CdTe that uses a modified vapor transport deposition system is described. This modification enables control of the Sb concentration with a pyrolysis stage to enhance the doping efficiency. CdTe:Sb films under different deposition conditions are characterized by SEM, XRD, and CV measurements for determining morphology, crystal structure, and hole concentration. Variations of the Sb dopant heater and pyrolyzer temperatures do not affect the CdTe morphology and crystal structure. However, CV measurements show that a higher dopant heater or pyrolyzer temperature leads to higher hole concentration. In this study, CdTe: Sb films achieve a hole concentration of 1016 cm-3 and 10% doping efficiency when the dopant heater is 600C and the pyrolyzer temperature is 1100C. This demonstrates a path to produce high hole concentration polycrystalline CdTe film with a low concentration of dopant-induced defect.
Erythritol has been proposed as an inert surrogate for developing theoretical and computational models to study aging in energetic materials. In this work, we present a comparison of mechanical and shock properties of erythritol computed using the ReaxFF reactive force field and from ab initio calculations employing density functional theory (DFT). We screened eight different ReaxFF parameterizations, of which the CHO parameters developed for hydrocarbon oxidation provide the most accurate predictions of mechanical properties and the crystal structure of erythritol. Further validation of the applicability of this ReaxFF parameterization for modeling erythritol is demonstrated by comparing predictions of the elastic constants, crystal structure, vibrational density of states, and Hugoniot curves against DFT calculations. The ReaxFF predictions are in close agreement with the DFT simulations for the elastic constants and shock Hugoniot when the crystal is loaded along its c axis but show as much as 30% disagreement in the elastic constants in the ab plane and 12% difference in shock pressures when shocked along the a or b crystal axes. Last, we compare thermomechanical properties predicted from classical molecular dynamics with those calculated using the quasi-harmonic approximation and show that quantum mechanical effects produce large discrepancies in the computed values of heat capacity and thermal expansion coefficients compared with classical assumptions. Combining classical molecular dynamics predictions of mechanical behavior with phonon-based calculations of thermal behaviors, we show that predicted shock-induced temperatures for pressures up to 6.5 GPa do not exceed the pressure-dependent melting point of erythritol.
Abstract We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning (ML) models for predicting properties of inorganic bulk materials. The test suite, Matbench, is a set of 13 ML tasks that range in size from 312 to 132k samples and contain data from 10 density functional theory-derived and experimental sources. Tasks include predicting optical, thermal, electronic, thermodynamic, tensile, and elastic properties given a material’s composition and/or crystal structure. The reference algorithm, Automatminer, is a highly-extensible, fully automated ML pipeline for predicting materials properties from materials primitives (such as composition and crystal structure) without user intervention or hyperparameter tuning. We test Automatminer on the Matbench test suite and compare its predictive power with state-of-the-art crystal graph neural networks and a traditional descriptor-based Random Forest model. We find Automatminer achieves the best performance on 8 of 13 tasks in the benchmark. We also show our test suite is capable of exposing predictive advantages of each algorithm—namely, that crystal graph methods appear to outperform traditional machine learning methods given ~10 4 or greater data points. We encourage evaluating materials ML algorithms on the Matbench benchmark and comparing them against the latest version of Automatminer.
As a powerful analytical technique, atom probe tomography (APT) has the capacity to acquire the spatial distribution of millions of atoms from a complex sample. However, extracting information at the Ångstrom-scale on atomic ordering remains a challenge due to the limits of the APT experiment and data analysis algorithms. The development of new computational tools enable visualization of the data and aid understanding of the physical phenomena such as disorder of complex crystalline structures. Here, we report progress towards this goal using two steps. We describe a computational approach to evaluate atomic ordering in the crystal structure by generating radial distribution functions (RDF). Atomic ordering is rendered as the Fractional Cumulative Radial Distribution Function (FCRDF) which allows for greater visibility of local compositions at short range in the structure. Further, we accommodate in the analysis additional parameters such as uncertainty in the atomic coordinates and the atomic abundance to ascertain short-range ordering in APT data sets. We applied the FCRDF analysis to synthetic and experimental APT data sets for Ni 3 Al. The ability to observe a signal of atomic ordering consistent with the known L1 2 crystal structure is heavily dependent on spatial uncertainty, irrespective of abundance. Detection of atomic ordering is subject to an upper limit of spatial uncertainty of atoms described with Gaussian distributions with a standard deviation of 1.3 Å. The FCRDF analysis was also applied to the APT data set for a six-component alloy, Al 1.3 CoCrCuFeNi. In this case, we are currently able to visualize elemental segregation at the nanoscale, though unambiguous identification of atomic ordering at the Ångstrom (nearest-neighbor) scale remains a goal.
Introduction: Numerous X-ray crystal structures of the c-Src SH3 domain have provideda large sampling of atomic-level information for this important signaling domain. Multiple crystalforms have been reported, with variable crystal lattice contacts and chemical crystallizationconditions. Materials and Methods: We crystallized the c-Src SH3 domain in a crystallization buffercontaining NiCl2. Results: A unique crystal structure of the Src SH3 domain in the trigonal space group H32 isdetermined to 1.45 Å resolution. Crystal packing and anomalous scattering reveal that this crystalform is mediated by two ordered nickel ions provided by the crystallization buffer. Nickelcoordination occurs in a 2:2 stoichiometry, which dimerizes two SH3 domain monomers across apseudo-twofold rotation axis and involves the native N-terminal c-Src SH3 amino acid sequence, asurface-exposed histidine residue, and ordered water molecules. Discussion: This study provides an example of metal-mediated crystallization and metal binding byN-terminal protein residues, contrasting with the Amino-Terminal Copper and Nickel Binding(ATCUN) motif. Conclusion: Alternative avenues help widen the potential for future crystallography-based studiesof the c-Src SH3 domain.
Here we examined the effect of the lattice compression on the crystal structure of the Bi 2 Sr 2 CaCu 2 O 8+σ superconductor with nearly optimally doped and overdoped composition using X-ray diffraction technique. Our studies show that at high pressures (up to 30 GPa ) the doping level does not affect the crystal structure of this superconductor. Along with this, structural anomalies in ratio appear at a pressure that corresponds to that at which T c begins to decrease. This fact indicates a close connection between the observed anomalies and superconductivity. We also studied the effect of doping and pressure on the T c (P) and on the Raman active lattice modes of the Bi 2 Sr 2 CaCu 2 O 8+σ superconductors. We find universal suppression of the T c by the pressure starting from the critical pressure P c in the range from 9 to 16 GPa, depending on the doping level of the Bi 2 Sr 2 CaCu 2 O 8+σ samples. Concomitantly, we observe phonon anomalies around 10 to 20 GPa, which indicate possible pressure-induced charge redistribution in BiO layers. These newly detected anomalies may be related to the changes in the electronic structure which compete with the superconductivity.