Crystal structure of beta-Mg2SiO4 - Crystal-chemical and geophysical implications
Crystal-chemical and geophysical implications concerning earth mantle phase transitions from beta magnesium silicate crystal structure
Moore, P. B.↗
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CSD 2078665: Experimental Crystal Structure Determination
An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Cell Parameters↗
CSD 2312746: Experimental Crystal Structure Determination
An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Cell Parameters↗
CSD 2374310: Experimental Crystal Structure Determination
An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Cell Parameters↗
The crystal structure of dipotassium tetranitroethide.
Crystal structure of dipotassium tetranitroethide determined by single crystal X ray diffraction
Dyke, M.↗
The crystal structure of strontium bromide monohydrate.
Crystal structure of strontium bromide monohydrate by X-ray single crystal diffraction techniques
STRONTIUM BROMIDE↗
Ab Initio Crystal Structure Prediction of the Energetic Materials LLM-105, RDX, and HMX
Not Available
36 MATERIALS SCIENCE↗
Accurate Crystal Structure Prediction of New 2D Hybrid Organic–Inorganic Perovskites
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Theoretical studies on the relationship between the thermionic work functions of refractory-metal intermetallic compounds and their electronic and crystal structures Final summary report
The Group VIA-Re binary systems are characterized by the presence of several intermediate phases. The u phase is present in all of the systems, but the a-Mn phases occur in only the Mo-Re and W-Re systems. The occurrence of these intermediate phases appears to be governed largely by electronic factors and is predictable on the basis of electron/atom ratio. The thermionic work functions of the intermediate phase materials were experimentally determined. function and the screening of the outermost electrons in the Group VIA metals was found. A correlation between the work As might be expected for purely metallic substances, the work functions were relatively high, in the range 4. 5 to 5. 0 eV, and in each case were bracketed by the work functions of the pure constituents. A discontinuous change in the average work function with composition is proposed, based on a thermodynamical treatment of the electron vapor.
REFRACTORY METAL↗
Synthesis and Crystal Structures of Alkali (Na, Rb, Cs) Iron Phosphate Crystals
Three alkali-containing diphosphate crystals of A FeP 2 O 7 (A = Na, Rb, Cs) were synthesized through melt-crystallization. The crystal structures were determined using single-crystal X-ray diffraction (XRD) data. The synthesized diphosphates crystallized within the P 2 1 /c space group, and the structural parameters were compared to literature data of other A FeP 2 O 7 crystals within the P 2 1 /c space group.
36 MATERIALS SCIENCE↗
How Accurate Can Crystal Structure Predictions Be for High-Energy Molecular Crystals?
Molecular crystals have shallow potential energy landscapes, with multiple local minima separated by very small differences in total energy. Predicting molecular packing and molecular conformation in the crystal generally requires ab initio methods of high accuracy, especially when polymorphs are involved. We used dispersion-corrected density functional theory (DFT-D) to assess the capabilities of an evolutionary algorithm (EA) for the crystal structure prediction (CSP) of well-known but challenging high-energy molecular crystals (HMX, RDX, CL-20, and FOX-7). While providing the EA with the experimental conformation of the molecule quickly re-discovers the experimental packing, it is more realistic to start instead from a naïve, flat, or neutral initial conformation, which reflects the limited experimental knowledge we generally have in the computational design of molecular crystals. By doing so, and using fully flexible molecules in fully variable unit cells, we show that the experimental structures can be predicted in fewer than 20 generations. Nonetheless, one must be aware that some molecular crystals have naturally hindered evolutions, requiring as many attempts as there are space groups of interest to predict their structures, and some may require the accuracy of all-electron calculations to discriminate between closely ranked structures. To save resources in this computationally demanding process, we showed that a hybrid xTB/DFT-D approach could be considered in a subsequent study to push the limits of CSP beyond 200+ atoms and for cocrystals.
42 ENGINEERING↗
Data-centric framework for crystal structure identification in atomistic simulations using machine learning
Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale simulations renders them unsuitable for simple human visual inspection. Instead, specialized structure characterization techniques are required to aid interpretation. These have historically been challenging to construct, requiring significant intuition and effort. Here we propose an alternative framework for a fundamental structural characterization task: classifying atoms according to the crystal structure to which they belong. Our approach is data-centric and favors the employment of Machine Learning over heuristic rules of classification. A group of data-science tools and simple local descriptors of atomic structure are employed together with an efficient synthetic training set. We also introduce the first standard and publicly available benchmark data set for evaluation of algorithms for crystal-structure classification. Further, it is demonstrated that our data-centric framework outperforms all of the most popular heuristic methods—especially at high temperatures when lattices are the most distorted—while introducing a systematic route for generalization to new crystal structures. Moreover, through the use of outlier detection algorithms our approach is capable of discerning between amorphous atomic motifs (i.e., noncrystalline phases) and unknown crystal structures, making it uniquely suited for exploratory materials synthesis simulations.
36 MATERIALS SCIENCE↗
The crystal structure of lead chloride
Single crystal and x-ray diffraction methods for studing crystal structure of lead chloride
LEAD CHLORIDE↗
Crystal structure analysis of intermetallic compounds
Study concerns crystal structures and lattice parameters for a number of new intermetallic compounds. Crystal structure data have been collected on equiatomic compounds, formed between an element of the Sc, Ti, V, or Cr group and an element of the Co or Ni group. The data, obtained by conventional methods, are presented in an easily usable tabular form.
Conner, R. A., Jr.↗
Quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) of zwitterionic organic HCl salts
In this work, we benchmark quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) for determining the crystal structures of two zwitterionic organic HCl salts, L-ornithine HCl ( Orn ) and L-histidine HCl·H 2 O ( Hist ). These salts present an interesting challenge for QNMRX-CSP, as gas-phase geometry optimizations used to generate starting structures for the organic zwitterionic fragments fail to capture their correct solid-state geometries. To overcome this limitation, geometry optimizations using the COSMO water-solvation model are employed to generate initial structural models. Using this approach, QNMRX-CSP yields structural models of the two zwitterionic organic HCl salts that closely match experimentally determined crystal structures. In addition, the application of QNMRX-CSP to Hist represents a further step toward the de novo structural determination of solvated organic HCl salts, as Hist is the first benchmark system of this type to include a water molecule as a component of its crystal structure. This work is significant for its potential application to the structural determination of active pharmaceutical ingredients, which often feature complex organic components and solvated solid forms.
Fleischer, Carl H. [Florida State Univ., Tallahass↗
Crystal structures and functional analysis of the ZnF5-WWE1-WWE2 region of PARP13/ZAP define a distinctive mode of engaging poly(ADP-ribose)
PARP13/ZAP (zinc-finger antiviral protein) acts against multiple viruses by promoting degradation of viral mRNA. PARP13 has four N-terminal zinc (Zn) fingers that bind CG-rich nucleotide sequences, a C-terminal ADP ribosyltransferase fold, and a central region with a fifth Zn finger and tandem WWE domains. The central PARP13 region, ZnF5-WWE1-WWE2, is implicated in binding poly(ADP-ribose); however, there are limited insights into its structure and function. We present crystal structures of ZnF5-WWE1-WWE2 from mouse PARP13 in complex with ADP-ribose and in complex with ATP. The crystal structures and binding studies demonstrate that WWE2 interacts with ADP-ribose and ATP, whereas WWE1 does not have a functional binding site. Binding studies with poly(ADP-ribose) ligands indicate that WWE2 serves as an anchor for preferential binding to the terminal end of poly(ADP-ribose) chains. The composite ZnF5-WWE1-WWE2 structure forms an extended surface to engage ADP-ribose chains, representing a distinctive mode of recognition that provides a framework for investigating the impact of poly(ADP-ribose) on PARP13 function.
59 BASIC BIOLOGICAL SCIENCES↗
Review on crystal structures and magnetic properties of RTX 3 materials
The structural and compositional diversity of the RTX 3 family of materials offers various magnetic and thermodynamic properties such as complex magnetic structure, vibronic bound states, heavy-fermions, valence fluctuations, metamagnetism, spin glass behavior, quantum criticality, and unconventional superconductivity. In this study we present an overview of the crystal structures, crystal growth and magnetic properties of RTX 3 compounds as well as a discussion of the relevant physics. The magnetic properties of several compounds of the RTX 3 family still remain unexplored. The compounds with a complex magnetic structure could potentially host exotic topological phases. This review article may help explore exotic magnetic properties such as the vibron state and topological spin textures.
quantum materials↗
Random forest prediction of crystal structure from electron diffraction patterns incorporating multiple scattering
Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here, in this study, we train an architecture of hierarchical random forest models capable of predicting the crystal system, space group, and lattice parameters from one or more unknown two-dimensional electron diffraction patterns. Our initial model correctly identifies the crystal system of a simulated electron diffraction pattern from a 20-nm-thick specimen of arbitrary orientation 67% of the time. We achieve a topline accuracy of 79% when aggregating predictions from ten patterns of the same material but different zone axes. The space group and lattice predictions range from 70% to 90% accuracy and median errors of 0.01-0.5Å, respectively, for cubic, hexagonal, trigonal, and tetragonal crystal systems while being less reliable on orthorhombic and monoclinic systems. We apply this architecture to a four-dimensional scanning transmission electron microscopy scan of gold nanoparticles, where it accurately predicts the crystal structure and lattice constants. These random forest models can be used to significantly accelerate the analysis of electron diffraction patterns, particularly in the case of unknown crystal structures. Additionally, due to the speed of inference, these models could be integrated into live transmission electron microscopy experiments, allowing real-Time labeling of a specimen.
36 MATERIALS SCIENCE↗