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At least 163 records · Page 9

Using Complementary Methods of Synchrotron Radiation Powder Diffraction and Pair Distribution Function to Refine Crystal Structures with High Quality Parameters—A Review

Determination of the atomic-scale structures of certain fine-grained minerals using single-crystal X-ray diffraction (XRD) has been challenging because they commonly occur as submicron and nanocrystals in the geological environment. Synchrotron powder diffraction and scattering techniques are useful complementary methods for studying this type of minerals. In this review, we discussed three example studies investigated by combined methods of synchrotron radiation XRD and pair distribution function (PDF) techniques: (1) low-temperature cristobalite; (2) kaolinite; and (3) vernadite. Powder XRD is useful to determine the average structure including unit-cell parameters, fractional atomic coordinates, occupancies and isotropic atomic displacement parameters. X-ray/Neutron PDF methods are sensitive to study the local structure with anisotropic atomic displacement parameters (ADP). The results and case studies suggest that the crystal structure and high-quality ADP values can be obtained using the combined methods. The method can be useful to characterize crystals and minerals that are not suitable for single-crystal XRD.

58 GEOSCIENCES↗

Crystal structure of calcium L-5-methyltetrahydrofolate trihydrate type I, C 20 H 23 N 7 O 6 Ca(H 2 O) 3

The crystal structure of L-5-methyltetrahydrofolate calcium trihydrate has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional techniques. Calcium levomefolate trihydrate crystallizes in space group P2 1 2 1 2 1 (#19) with a = 7.1706(6), b = 6.5371(5), c = 53.8357(41) Å, V = 2523.58(26) Å 3 , and Z = 4. The structure is characterized by alternating hydrophobic and hydrophilic layers along the c-axis. The Ca cations are 7-coordinate, and share edges to form chains along the b-axis. Each of the water molecules acts as a donor in two hydrogen bonds. The coordinated water molecule makes two strong intermolecular O–H∙∙∙O hydrogen bonds to carboxyl and carbonyl groups. The two zeolitic water molecules form weaker hydrogen bonds, to carbonyl O atoms, ring N atoms, and aromatic C atoms. Several N–H∙∙∙O/N hydrogen bonds, as well as C–H∙∙∙O hydrogen bonds, also contribute to the lattice energy.

36 MATERIALS SCIENCE↗

Crystal structure of meglumine diatrizoate, (C 7 H 18 NO 5 )(C 11 H 8 I 3 N 2 O 4 )

The crystal structure of meglumine diatrizoate has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Meglumine diatrizoate crystallizes in space group P2 1 (#4) with a = 10.74697(4), b = 6.49364(2), c = 18.52774(7) Å, β = 90.2263(3), V = 1292.985(5) Å 3 , and Z = 2. Two different crystal structures, which yielded essentially identical refinement residuals and positions of the non-H atoms, were obtained. The differences were in the H atom positions and the hydrogen bonding. One structure was 123.0 kJ/mol/cell lower in energy than the other and was adopted for the final description. The crystal structure consists of alternating double layers of cations and anions along the c-axis. The hydrogen bonds link the cations and anions into a three-dimensional framework. Each of the hydrogen atoms on the ammonium nitrogen of the cation acts as a donor in a strong N–H∙∙∙O hydrogen bond. One of these is to a hydroxyl group of another cation, and the other is to the carboxylate group of the anion. Each of the amide nitrogen atoms of the anion forms a strong N–H∙∙∙O intermolecular hydrogen bond, one to a carbonyl and the other to a carboxylate group. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

36 MATERIALS SCIENCE↗

Crystal structure of elvitegravir Form II, C 23 H 23 ClFNO 5

The crystal structure of elvitegravir Form II has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional theory techniques. Elvitegravir Form II crystallizes in space group P2 1 (#4) with a = 11.54842(7), b = 14.04367(5), c = 13.33333(8) Å, β = 90.0330(6)°, V = 2162.427(14) Å 3 , and Z = 4. The crystal structure consists of alternating layers of parallel molecules perpendicular to the b-axis. The mean planes of the oxoquinoline ring systems in molecules 1 and 2 are 1(22)-1 and -1(22)1. Between the stacks are layers of the halogenated phenyl rings. These exhibit herringbone stacking. In each molecule, the carboxylic acid group forms a strong intramolecular O–H∙∙∙O hydrogen bond to the nearby carbonyl group. The hydroxyl group of each molecule forms a strong hydrogen bond to the carbonyl group of the carboxylic acid of the other molecule. These O–H∙∙∙O hydrogen bonds link the molecules into dimers, with a graph set R2,2(18) > a > c. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

36 MATERIALS SCIENCE↗

Crystal structure of danofloxacin mesylate (C 19 H 21 FN 3 O 3 )(CH 3 O 3 S)

The crystal structure of danofloxacin mesylate has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Danofloxacin mesylate crystallizes in space group P1 (#1) with a = 6.77474(8), b = 12.4973(4), c = 12.82826(28) Å, α = 84.8709(29), β = 87.7501(10), γ = 74.9916(4)°, V = 1044.723(11) Å 3 , and Z = 2. The protonation of the danofloxacin cations was established by the analysis of potential intermolecular interactions and differs from that expected from isolated-cation calculations. The crystal structure consists of alternating layers of cations and anions parallel to the ac-plane. There is parallel stacking of the oxoquinoline rings along the a-axis. The expected N–H∙∙∙O hydrogen bonds between the cations and anions are not present. Each cation makes an N–H∙∙∙O hydrogen bond with the other cation, resulting in zig-zag chains along the a-axis. Both cations have strong intramolecular O–H∙∙∙O hydrogen bonds. There are several C–H∙∙∙O hydrogen bonds between the danofloxacin cations and mesylate anions. The powder pattern has been submitted to ICDD® for inclusion in the Powder Diffraction File™ (PDF®).

36 MATERIALS SCIENCE↗

Crystal structure of aminopentamide hydrogen sulfate, (C 19 H 25 N 2 O)(HSO 4 )

The crystal structure of aminopentamide hydrogen sulfate has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional techniques. Aminopentamide hydrogen sulfate crystallizes in space group P2 1 /c (#14) with a = 17.62255(14), b = 6.35534(4), c = 17.82499(10) Å, β = 96.4005(6)°, V = 1983.906(14) Å 3 , and Z = 4. The structure consists of layers parallel to the bc-plane with hydrogen sulfate anions at the core and aminopentamide cations on the outside. There is a strong charge-assisted O49–H53∙∙∙O52 hydrogen bond between the hydrogen sulfate anions. This hydrogen bond links the anions in a chain parallel to the b-axis. The cation forms a discrete N–H∙∙∙O hydrogen bond to the anion. The amide group also forms two weaker discrete hydrogen bonds to the anion. The three N–H∙∙∙O hydrogen bonds link the cations and anions into columns parallel to the b-axis. This commercial material from USP contained an unidentified impurity, the powder pattern of which could be indexed on a monoclinic unit cell. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

36 MATERIALS SCIENCE↗

Consequences of long-term water exposure for bulk crystal structure and surface composition/chemistry of nickel-rich layered oxide materials for Li-ion batteries

Water exposure of layered nickel-rich transition metal oxide electrodes, widely used in high-energy lithium-ion batteries, has detrimental effects on the electrochemical performance, which complicates electrode handling and prevents implementation of environmentally benign aqueous processing procedures. Elucidating the degradation mechanisms in play may help rationally mitigate/circumvent key challenges. Here, the bulk structural consequences of long-term (>2.5 years) deuterated water (D2O) exposure of intercalation materials with compositions Li x Ni 0.5 Co 0.2 Mn 0.3 O 2 (NCM523) and Li x Ni 0.8 Co 0.1 Mn 0.1 O 2 (NCM811) are studied by neutron powder diffraction (NPD). Detailed inspection of the NPD data reveals gradual formation of a secondary crystalline phase in all exposed samples, not previously reported for this system. This unknown phase forms faster in liquid- compared to vapor-exposed compounds. Structural modelling of the NPD data shows a stable level of Li/Ni anti-site defects and does not indicate any significant changes in lattice parameters or hydrogen-lithium (D + /Li + ) exchange in the structure. Consequently, the secondary phase formation must take place via transformation rather than modification of the parent material. X-ray photoelectron spectroscopy data indicate formation of LiHCO 3 /Li 2 CO 3 at the surface and a Li-deficient oxide in the sub-surface region of the pristine compounds, and the presence of adsorbed water and transition metal hydroxides at the exposed sample surfaces.

25 ENERGY STORAGE↗

Carbonated apatite lattice parameter variation across incremental growth lines in teeth

Here, results of microbeam mapping (x-ray excited x-ray fluorescence and transmission x-ray diffraction) of Beluga whale cementum and of beaver dentin reveal growth bands are defined by variation in mineral content (carbonated hydroxyapatite, cAp), by variation in Zn content and by variation in cAp lattice parameter a. For both tissues, diffraction and fluorescence data show that Zn signal and a are anti-correlated, that is high Zn signal is co-located with low a, and vice versa. In cementum and bone, treatment with acid removes Ca, Zn and cAp. The data are strong evidence that Zn is incorporated into the cAp lattice in these tissues and that the amount of Zn incorporated varies across two very different types of growth bands, annual bands in Beluga cementum and daily incremental bands in beaver dentin. To the best of the authors’ knowledge, this is the first observation of spatial variation of lattice parameter within growth bands.

36 MATERIALS SCIENCE↗

Crystalline phase transitions and water-soluble complexes of copper(Ⅰ) 2-hydroxyethanethiolate

We report the coordination polymer copper(I) 2-hydroxyethanethiolate, (CuSCH 2 CH 2 OH) n , though insoluble in all common solvents, dissolved readily in basic aqueous solutions of the thiolate anion (HOCH 2 CH 2 S – ) of 2-mercaptoethanol to form a single species: the tetranuclear cluster [Cu 4 (μ-SCH 2 CH 2 OH) 6 ] 2– . From this solution were grown X-ray quality single crystals of copper(I) 2-hydroxyethanethiolate. This compound underwent a hitherto unknown crystal phase transition at ca. 6 °C, from point group P2 1 2 1 2 1 to Pna2 1 , with noticeable changes in the geometry of the Cu-S layer and in the orientation of the alkylthiolate side chains. When the bulky base tetrabutylammonium hydroxide was employed in the aqueous thiolate solution used to dissolve (CuSCH 2 CH 2 OH) n , the water-soluble polynuclear copper(I) complex bis(tetrabutylammonium) hexakis(μ-2-hydroxyethanethiolato) tetracuprate(I), [(C 4 H 9 ) 4 N] 2 [Cu 4 (μ-SCH 2 CH 2 OH) 6 ], could be isolated as X-ray quality crystals. Structural characterization of this complex revealed a tetrahedral arrangement of copper(I) centers with thiolates bridging the edges of the tetrahedra. On standing, this complex degraded to a larger polynuclear Cu(I) sulfide cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dara: Automated Multiple-Hypothesis Phase Identification and Refinement from Powder X-ray Diffraction

Powder X-ray diffraction (XRD) is a foundational technique for characterizing crystalline materials. However, the reliable interpretation of XRD patterns, particularly in multiphase systems, remains a manual and expertise-demanding task. As a characterization method that only provides structural information, multiple reference phases can often be fit to a single pattern, leading to potential misinterpretation when alternative solutions are overlooked. To ease humans’ efforts and address the challenge, we introduce Dara (data-driven automated Rietveld analysis), a framework designed to automate the robust identification and refinement of multiple phases from powder XRD data. Dara performs an exhaustive tree search over all plausible phase combinations within a given chemical space and validates each hypothesis using the BGMN Rietveld refinement routine. Key features include structural database filtering, automatic clustering of isostructural phases during tree expansion, and peak-matching-based scoring to identify promising phases for refinement. When ambiguity exists, Dara generates multiple hypothesis which can then be decided between by human experts or with further characterization tools. By enhancing the reliability and accuracy of phase identification, Dara enables scalable analysis of realistic complex XRD patterns and provides a foundation for integration into multimodal characterization workflows, moving toward fully self-driving materials discovery.

Biological databases↗

Powder diffraction

Powder diffraction is a non-destructive technique, which is experimentally simple in principle. Because the physics behind diffraction is well understood, an exceptionally large amount of information can be obtained from a single measurement. The positions and relative intensities of the peaks yield a fingerprint that can be used for qualitative phase analysis. Quantitative phase analysis can be obtained by detailed analysis of the intensities. Unit cells can be derived from the peak positions. Crystal structures can be solved using powder diffraction data and refined by the Rietveld method. The peak profiles contain information about crystallite size, strain and nanostructure. Non-idealities in the intensities give information on texture. Abandoning the crystallographic model provides information about local structure, by pair distribution function analysis. For powder diffraction, everything is a sample; the technique is commonly applied to characterize minerals, ceramics, metals and alloys, catalysts, polymers, pharmaceuticals, organic compounds, environmental and forensic samples, among others. The major features of contemporary laboratory powder diffractometers are described. Methods for obtaining suitable powder specimens are summarized. Major applications of qualitative and quantitative phase analysis, structure solution, size/strain/nanostructure analysis using peak profiles, texture analysis and pair distribution function analysis are introduced.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Phase evolution of U-Zr system in a thermal cycling neutron diffraction experiment: as-cast U-35Zr and U-50Zr

Here, phase evolution of as-cast U-35 wt% Zr and U-50 wt% Zr alloys during thermal cycling (303–1073 K) was investigated using in-situ neutron diffraction. Analysis was performed using Rietveld crystal and microstructure refinements from time-of-flight neutron diffraction data, with a focus on evolution of lattice parameter, atom ordering, unit cell volume, and weight fractions during the thermal cycling. Disordered δ-UZr 2 and residual γ-(U,Zr) phase are retained in the field of δ of the U-Zr equilibrium phase diagram for the U-50Zr sample, and in the field between δ and α-U for the U-35Zr sample. The α phase that is present in the reported phase diagrams of U-Zr was not observed in the diffraction patterns. The evolutions of lattice parameter and unit cell volume of δ and γ are affected by both thermal expansion and chemistry.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Microstructure Evolution of U–Zr System in A Thermal Cycling Neutron Diffraction Experiment: Extruded U–10Zr (wt. %)

Microstructure evolution of 1073 K extruded U–10Zr (wt. %) fuel during thermal cycling (303–1073 K with a ~9 hour hold at 873 K during cooling) was investigated using in situ neutron diffraction. Analysis was performed using Rietveld texture and crystal structure refinements from time–of–flight neutron diffraction data, with a focus on the evolution of textures and lattice parameters as a function of temperature. The α–U phase exhibits lattice contraction with increasing temperature along the b lattice direction and lattice expansion in the other directions while the other phases exhibit lattice expansion with temperature in all directions. Contrary to the established phase diagram, the β–U phase is absent at the temperatures of the thermal cycling. (001) α and (110) γ plane normals are observed with a strong preferred orientation along the extrusion direction. Finally, the variant selection of (001) α ||(110) γ is observed for the first time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Strength of tantalum to 276 GPa determined by two x-ray diffraction techniques using diamond anvil cells

Tantalum (Ta) is a metal that has useful properties that make it useful in extreme environments. It is therefore important to understand how Ta performs in such extreme conditions by accurately measuring its properties. In this work, the yield strength of tantalum has been measured at pressures up to 276 GPa using axial and radial x-ray diffraction (XRD) methods in diamond anvil cells (DAC). We measured strength using XRD in a radial DAC to 50 GPa, in an axial DAC to 60 GPa using diamonds with standard flat culets, and in a final experiment to 276 GPa using toroidal diamond anvils. The radial XRD data were refined using the Material Analysis Using Diffraction (MAUD) Rietveld software package to extract lattice strain and the yield strength. The axial data were refined using the General Structure Analysis System (GSAS) II and a linewidth method was used to calculate the yield strength. The yield strength measured near ambient pressure was found to be 0.5 GPa and increased with pressure up to 50 GPa, where the yield strength plateaued at a value of 2.4 GPa. At pressures above 60 GPa, the strength increased again to a maximum value of 9 GPa at the highest pressure of 276 GPa. Here, the data from the three experiments show good agreement between the methods and previously reported experimental data. This agreement illustrates the value of axial diffraction data for material strength determination and allows for measurements at multihundreds of GPa using toroidal DACs.

36 MATERIALS SCIENCE↗

Crystal Structure of Moganite and Its Anisotropic Atomic Displacement Parameters Determined by Synchrotron X-ray Diffraction and X-ray/Neutron Pair Distribution Function Analyses

The crystal structure of moganite from the Mogán formation on Gran Canaria has been re-investigated using high-resolution synchrotron X-ray diffraction (XRD) and X-ray/neutron pair distribution function (PDF) analyses. Our study for the first time reports the anisotropic atomic displacement parameters (ADPs) of a natural moganite. Rietveld analysis of synchrotron XRD data determined the crystal structure of moganite with the space group I2/a. The refined unit-cell parameters are a = 8.7363(8), b = 4.8688(5), c = 10.7203(9) Å, and β = 90.212(4)°. The ADPs of Si and O in moganite were obtained from X-ray and neutron PDF analyses. The shapes and orientations of the anisotropic ellipsoids determined from X-ray and neutron measurements are similar. The anisotropic ellipsoids for O extend along planes perpendicular to the Si-Si axis of corner-sharing SiO4 tetrahedra, suggesting precession-like movement. Neutron PDF result confirms the occurrence of OH over some of the tetrahedral sites. We postulate that moganite nanomineral is stable with respect to quartz in hypersaline water. The ADPs of moganite show a similar trend as those of quartz determined by single-crystal XRD. In short, the combined methods can provide high-quality structural parameters of moganite nanomineral, including its ADPs and extra OH position at the surface. This approach can be used as an alternative means for solving the structures of crystals that are not large enough for single-crystal XRD measurements, such as fine-grained and nanocrystalline minerals formed in various geological environments.

58 GEOSCIENCES↗

Algorithms in Diffraction Profile Analysis

This chapter introduces several approaches to crystallographic structure refinement from diffraction profile data including the Rietveld method, global optimization methods, and Bayesian modeling. First, the Rietveld method and related nonlinear least squares approaches to analyzing diffraction profiles are briefly discussed. We then review the most common algorithms within global optimization as alternative methods of structure solution: grid search, simulated annealing, and genetic algorithms. As the Rietveld method is the standard tool for analyzing diffraction profile data, we catalogue its challenges and limitations. A Bayesian approach to diffraction profile analysis is presented as an alternative, along with several sampling algorithms including Gibbs sampling, variants of Metropolis sampling, Hamiltonian Monte Carlo, and approximate Bayesian computing. These sampling algorithms are applied to the fitting of a neutron diffraction profile from a National Institute of Standards and Technology silicon standard reference material, and their results are compared.

Singh, Susheela↗

Spotlight: efficient automated global optimization in rietveld analysis of diffraction data

Performing reliable Rietveld analysis on tens or hundreds of powder diffraction datasets from parametric or time-resolved experiments often poses a bottleneck in extracting meaningful results from the data. While automated analysis of data has recently been demonstrated, high temperature annealing studies, during which phase transformations occur and lattice parameters may change due to repartitioning of elements, are prime examples where automation by a simple phase identification from a database of room temperature structures or automation by sequential refinements is likely to fail. To enable reliable, efficient, automated Rietveld analysis, we present a Python package named Spotlight , building on established Rietveld packages such as MAUD, GSAS , or GSAS-II , which extends the refinement of best fit parameters to a global optimization using an ensemble of optimizers leveraging hierarchical parallel execution on high-performance computing clusters. Spotlight further enables the efficient design of refinement plans through the iterative automated machine-learning of a surrogate for the refinement on which the global optimizations are performed until results from the surrogate converge to the response surface data. We demonstrate Spotlight with the analysis of uranium molybdenum and Ti–6Al–4V datasets, as well as in two open-source tutorials analyzing aluminium oxide and lead sulphate.

36 MATERIALS SCIENCE↗