Synchrotron Data Research Articles

Gradient Technique Theory: Tracing Magnetic Field and Obtaining Magnetic Field Strength

The gradient technique is a promising tool with theoretical foundations based on the fundamental properties of MHD turbulence and turbulent reconnection. Its various incarnations use spectroscopic, synchrotron, and intensity data to trace the magnetic field and measure the media magnetization in terms of Alfvén Mach number. We provide an analytical theory of gradient measurements and quantify the effects of averaging gradients along the line of sight and over the plane of the sky. We derive analytical expressions that relate the properties of gradient distribution with the Alfvén Mach number M A. We show that these measurements can be combined with measures of sonic Mach number or line broadening to obtain the magnetic field strength. The corresponding technique has advantages to the Davis–Chandrasekhar–Fermi way of obtaining the magnetic field strength.

Resveratrol enhances the antiliver cancer effect of cisplatin by targeting the cell membrane protein PLA2.

In this study, we aimed to explore the mechanism by which resveratrol promotes cisplatin-induced death of HepG2 cells and to provide a potential strategy for resveratrol in the treatment of cancer. HepG2 cells were exposed to a range of drug concentrations for 24 h: resveratrol (2.5 μg/mL [10.95 μM], 5 μg/mL [21.91 μM], 10 μg/mL [43.81 μM], 20 μg/mL [87.62 μM], 40 μg/mL [175.25 μM], and 80 μg/mL [350.50 μM]), cisplatin (0.625 μg/mL [2.08 μM], 1.25 μg/mL [4.17 μM], 2.5 μg/mL [8.33 μM], 4.5 μg/mL [15.00 μM], and 10 μg/mL [33.33 μM]), 24 μg/mL (105.15 μM) resveratrol + 9 μg/mL (30.00 μM) cisplatin, and 12 μg/mL (52.57 μM) resveratrol + 4.5 μg/mL (15.00 μM) cisplatin. The interaction of two drugs was evaluated by coefficient of drug interaction (CDI), which was based on the Pharmacological Additivity model. The MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay was used to detect the effect of different concentrations of drugs on cell viability, whiletranscriptome sequencing was used to identify pathways associated with higher gene enrichment. Synchrotron radiation FTIR microspectroscopy experiments and data analysis were conducted to obtain detailed spectral information. The second-derivative spectra were calculated using the Savitzky-Golay algorithm. Single-cell infrared spectral absorption matrices were constructed to analyze the spectral characteristics of individual cells. The Euclidean distance between cells was calculated to assess their spectral similarity. The cell-to-cell Euclidean distance was computed to evaluate the spatial relationships between cells. The target protein of resveratrol was verified by performing a Western blot analysis. After 24 h of treatment with resveratrol, HepG2 cell growth was inhibited in a dose-dependent manner. Resveratrol promotes cisplatin-induced HepG2 cell death through membrane-related pathways. It also significantly changes the membrane components of HepG2 cells. Additionally, resveratrol changes the morphology of the HepG2 cell membrane by decreasing the expression of PLA2G2. Resveratrol changes the morphology of the HepG2 cell membrane by decreasing the expression of PLA2G2 and promotes cisplatin-induced HepG2 cell death. The combination of cisplatin and resveratrol can play a synergistic therapeutic effect on HepG2 cells.

Exploring photoionization of gas-phase free radicals with a widely tunable VUV laser at moderate spectral resolution

The VUv Laser for Considering Astrophysical and Isolated Molecules (VULCAIMs) setup [Harper et al., Phys. Chem. Chem. Phys. 24, 2777 (2022)] integrates a narrow-bandwidth tunable vacuum ultraviolet (VUV) and extreme ultraviolet (XUV) nanosecond-pulsed laser system (6–16 eV) and a photoelectron spectrometer, designed for recording high-spectral-resolution (rotationally resolved) photoelectron spectra of gas-phase free radicals. This approach usually needs beforehand medium-resolution synchrotron data to guide the selection of specific spectral regions to be investigated at higher resolution with the VULCAIM setup. We present an upgraded version of the VUV laser system integrating an optical parametric oscillator for continuously scanned medium-resolution measurements (<3 cm−1) across the whole VUV and XUV spectral ranges. This innovation enables broader coverage without the need to access synchrotron facilities. Furthermore, rapid mode switching allows for maintaining optimized radical production conditions from mid-resolution to high-resolution operation mode, enhancing spectroscopy capabilities significantly. The new capabilities of the VULCAIM setup are illustrated on two showcases of photoionization studies: the nitric oxide (NO) stable molecular species and the benzyl (C6H5CH2) free radical produced by pyrolysis.

A distributed software system for integrating data-intensive imaging methods in a hard X-ray nanoprobe beamline at the SSRF.

The development of hard X-ray nanoprobe techniques has given rise to a number of experimental methods, like nano-XAS, nano-XRD, nano-XRF, ptychography and tomography. Each method has its own unique data processing algorithms. With the increase in data acquisition rate, the large amount of generated data is now a big challenge to these algorithms. In this work, an intuitive, user-friendly software system is introduced to integrate and manage these algorithms; by taking advantage of the loosely coupled, component-based design approach of the system, the data processing speed of the imaging algorithm is enhanced through optimization of the parallelism efficiency. This study provides meaningful solutions to tackle complexity challenges faced in synchrotron data processing.

Analyzing multispectral emission and synchrotron data to evaluate the quality of laser welds on copper

The validation of laser welding of metallic materials is challenging due to its highly dynamic processes and limited accessibility to the weld. The measurement of process emissions and the processing laser beam are one way to record highly dynamic process phenomena. However, these recordings always take place via the surface of the weld. Phenomena on the inside are only implicitly recognizable in the data and require further processing. To increase the validity of the diagnostic process, the multispectral emission data are synchronized with synchrotron data consisting of in situ high-speed images based on phase contrast videography. The welding process is transilluminated by synchrotron radiation and recorded during execution, providing clear contrasts between solid, liquid, and gaseous material phases. Thus, dynamics of the vapor capillary and the formation of defects such as pores can be recorded with high spatial and temporal resolution of <5 μm and >5 kHz. In this paper, laser welding of copper Cu-ETP and CuSn6 is investigated at the Deutsches Elektronen-Synchrotron (DESY). The synchronization is achieved by leveraging a three-stage deep learning approach. A preprocessing Mask-R-CNN, dimensionality reduction PCA/Autoencoders, and a final LSTM/Transformer stage provide end-to-end defect detection capabilities. Integrated gradients allow for the extraction of correlations between defects and emission data. The novel approach of correlating image and sensor data increases the informative value of the sensor data. It aims to characterize welds based on the sensor data not only according to IO/NIO but also to provide a quantitative description of the defects in the weld.

Investigation of fast and efficient lossless compression algorithms for macromolecular crystallography experiments.

Structural biology experiments benefit significantly from state-of-the-art synchrotron data collection. One can acquire macromolecular crystallography (MX) diffraction data on large-area photon-counting pixel-array detectors at framing rates exceeding 1000 frames per second, using 200 Gbps network connectivity, or higher when available. In extreme cases this represents a raw data throughput of about 25 GB s-1, which is nearly impossible to deliver at reasonable cost without compression. Our field has used lossless compression for decades to make such data collection manageable. Many MX beamlines are now fitted with DECTRIS Eiger detectors, all of which are delivered with optimized compression algorithms by default, and they perform well with current framing rates and typical diffraction data. However, better lossless compression algorithms have been developed and are now available to the research community. Here one of the latest and most promising lossless compression algorithms is investigated on a variety of diffraction data like those routinely acquired at state-of-the-art MX beamlines.

Mild-Temperature Supercritical Water Confined in Hydrophobic Metal-Organic Frameworks.

Fluids under extreme confinement show characteristics significantly different from those of their bulk counterpart. This work focuses on water confined within the complex cavities of highly hydrophobic metal-organic frameworks (MOFs) at high pressures. A combination of high-pressure intrusion-extrusion experiments with molecular dynamic simulations and synchrotron data reveals that supercritical transition for MOF-confined water takes place at a much lower temperature than in bulk water, ∼250 K below the reference values. This large shifting of the critical temperature (Tc) is attributed to the very large density of confined water vapor in the peculiar geometry and chemistry of the cavities of Cu2tebpz (tebpz = 3,3',5,5'-tetraethyl-4,4'-bipyrazolate) hydrophobic MOF. This is the first time the shift of Tc is investigated for water confined within highly hydrophobic nanoporous materials, which explains why such a large reduction of the critical temperature was never reported before, neither experimentally nor computationally.

INSIGHT: in situ heuristic tool for the efficient reduction of grazing-incidence X-ray scattering data.

INSIGHT is a Python-based software tool for processing and reducing 2D grazing-incidence wide- and small-angle X-ray scattering (GIWAXS/GISAXS) data. It offers the geometric transformation of the 2D GIWAXS/GISAXS detector image to reciprocal space, including vectorized and parallelized pixel-wise intensity correction calculations. An explicit focus on efficient data management and batch processing enables full control of large time-resolved synchrotron and laboratory data sets for a detailed analysis of kinetic GIWAXS/GISAXS studies of thin films. It processes data acquired with arbitrarily rotated detectors and performs vertical, horizontal, azimuthal and radial cuts in reciprocal space. It further allows crystallographic indexing and GIWAXS pattern simulation, and provides various plotting and export functionalities. Customized scripting offers a one-step solution to reduce, process, analyze and export findings of large in situ and operando data sets.

Electrochemistry and Electronic Structure of the Deuterium-Grown Boron-Doped Diamond Interfaces

Integration of the first principles quantum mechanical simulations with electrochemistry represents a difficult research area due to the complexity and large size of real systems and computational limitations. On the one hand it is highly desirable to be able to predict electrochemical properties of materials and systems from simulations to limit the money expenditure for experimental work and accelerate applications [1]. On the other hand, utilization of ab-initio simulations to understand the experimentally observed phenomena is also required to embed them into a solid theoretical framework.To fulfill this task, several multiscale approaches are used with the density functional theory (DFT) being fundamental tool for investigation of electronic structure. DFT results can be further extended to build forcefields used in molecular dynamics (MD) [2] for larger scale simulations and non-equillibrium Green's functions for investigations of electronics and spintronics of nanodevices [3]. Semiconductor electrochemistry is one of the most important areas to explore this experiment-theory interface because of the necessity to develop new materials for photovoltaics, photoelectrochemistry, energy storage and conversion. The purpose of the following talk is to show the power of this paradigm by elucidation of the deuterium-grown boron doped diamond (BDD-D) material [4].A brief introduction to the material synthesis, chemical and physical properties is provided exploiting the synchrotron data of X-Ray absorption spectroscopy and X-Ray photoelectron spectroscopy. Then, a strong emphasis is put into merging the (photo)electrochemical data with the first principle results for better understanding of charge transfer phenomena in the nanoscale. Specifically, DFT calculations of projected local density of states clearly show the presence of highly occupied surface states on the (111) plane of BDD-D in contrast to its standard hydrogen-grown counterpart (BDD-H). The resulting surface states are capable of photocurrent generation in the visible light, which is strongly magnified in BDD-D. Moreover, photoelectrochemical measurements evidenced that photocurrents can be positive or negative depending on the bias - despite BDD being a p-type semiconductor. These confirm a profound role of surface states in the semiconductor electrochemistry and capability of photoinduced charge transfer in the modified materials. The proposed picture shines some new light on the commonly established paradigm of band bending as the key factor driving surface properties of the nanodiamond surfaces [5]. Figure. SEM images of a) BDD@D and b) BDD@H; c) grain size distribution among two samples; d) XRD patterns of the diamond films deposited in the D2/CH4 and H2/CH4 gas mixtures. Reflections at 2θ around 44°, 75°, and 91° correspond to the (111), (220), and (311) diamond lattice planes, respectively. Doubling of the reflections is related to the presence of Kα1 and Kα2 wavelengths in the X-ray radiation [4]. Acknowledgements: M.S., M.B., and M.F. thank Helmholtz-Zentrum Berlin (HZB) for the allocation of synchrotron radiation beamtime at HZB (Germany). M.S. gratefully acknowledges the financial support of these studies fromthe Gdansk University of Technology through the DEC-02/2021/IDUB/ II.1/AMERICIUM grant under the Americium – “Excellence Initiative – Research University” program. R.B. acknowledges the funding from the National Science Centre, Poland under the OPUS call in the Weave programme (Project number: 2021/43/I/ST7/03205).

Exploring high-throughput synchrotron X-Ray powder diffraction for the structural analysis of pharmaceuticals

Synchrotron radiation offers a host of advanced properties, surpassing conventional laboratory sources with its high brightness, tunable phonon energy, photon beam coherence for advanced X-ray imaging, and a structured time profile, ideal for capturing dynamic atomic and molecular processes. However, these benefits come at the cost of operational complexity and expenses. Three decades ago, synchrotron radiation facilities, while technically open to all scientists, primarily served a limited community. Despite substantial accessibility improvements over the past two decades, synchrotron measurements still do not qualify as routine analyses. The intrinsic complexity of synchrotron science means experiments are pursued only when no alternatives suffice. In recent years, strides have been made in technology transfer offices, intermediate synchrotron-based analytical service companies, and the development of high-throughput synchrotron systems at various facilities, reshaping the perception of synchrotron science. This article investigates the practical application of synchrotron X-Ray Powder Diffraction (s-XRPD) techniques in pharmaceutical analysis. By utilizing concrete examples, we demonstrate how high-throughput systems have the potential to revolutionize s-XRPD applications in the pharmaceutical industry, rapidly generating XRPD patterns of comparable or superior quality to those obtained in state-of-the-art laboratory XRPD, all in less than 5 s. Additional cases featuring well-established pharmaceutical active ingredients (API) and excipients substantiate the concept of high throughput in pharmaceuticals, affirming data quality through structural refinements aligned with literature-derived unit cell parameters. Synchrotron data need not always be state-of-the-art to compete with lab-XRPD data. The key lies in ensuring user-friendliness, reproducibility, accessibility, cost-effectiveness, and the streamlined efforts associated with synchrotron instrumentation to remain highly competitive with their laboratory counterparts.

Comparative study of conventional and synchrotron X-ray electron densities on molecular crystals.

Five different electron density datasets obtained from conventional and synchrotron single crystal X-ray diffraction experiments are compared. The general aim of the study is to investigate the quality of data for electron density analysis from current state-of-the-art conventional sources, and to see how the data perform in comparison with high-quality synchrotron data. A molecular crystal of melamine was selected as the test compound due to its ability to form excellent single crystals, the light atom content, and an advantageous suitability factor of 3.6 for electron density modeling. These features make melamine an optimal system for conventional X-ray diffractometers since the inherent advantages of synchrotron sources such as short wavelength and high intensity are less critical in this case. Data were obtained at 100 K from new in-house diffractometers Rigaku Synergy-S (Mo and Ag source, HyPix100 detector) and Stoe Stadivari (Mo source, EIGER2 1M CdTe detector), and an older Oxford Diffraction Supernova (Mo source, Atlas CCD detector). The synchrotron data were obtained at 25 K from BL02B1 beamline at SPring-8 in Japan (λ = 0.2480 Å, Pilatus3 X 1M CdTe detector). The five datasets were compared on general quality parameters such as resolution, ⟨I/σ⟩, redundancy and R factors, as well as the more model specific fractal dimension plot and residual density maps. Comparison of the extracted electron densities reveals that all datasets can provide reliable multipole models, which overall convey similar chemical information. However, the new laboratory X-ray diffractometers with advanced pixel detector technology clearly measure data with significantly less noise and much higher reliability giving densities of higher quality, compared to the older instrument. The synchrotron data have higher resolution and lower measurement temperature, and they allow for finer details to be modeled (e.g. hydrogen κ parameters).

Structure of the Hexadecane Rotator Phase: Combination of X-ray Spectra and Molecular Dynamics Simulation.

Rotator phases are rotationally disordered plastic crystals, some of which can form upon freezing of alkane at alkane-water interfaces. Existing X-ray diffraction studies show only partial unit cell information for rotator phases of some alkanes. This includes the rotator phase of n-hexadecane, which is a transient metastable phase in pure alkane systems, but shows remarkable stability at interfaces when mediated by a surfactant. Here, we combine synchrotron X-ray diffraction data and molecular dynamics (MD) simulations, reporting clear evidence of the face-centered orthorhombic RI rotator phase from spectra for two hexadecane emulsions, one stabilized by Brij C10 and another by Tween 40 surfactants. MD simulations of pure hexadecane use the recently developed Williams 7B force field, which is capable of reproducing crystal-to-rotator phase transitions, and it also predicts the crystal structure of the RI phase. Full unit cell information is obtained by combining unit cell dimensions from synchrotron data and molecular orientations from MD simulations. A unit cell model of the RI phase is produced in the crystallographic information file (CIF) format, with each molecule represented by a superposition of four rotational positions, each with 25% occupancy. Powder diffraction spectra computed using this model are in good agreement with the experimental spectra.

The AXEAP2 program for Kβ X-ray emission spectra analysis using artificial intelligence.

The processing and analysis of synchrotron data can be a complex task, requiring specialized expertise and knowledge. Our previous work addressed the challenge of X-ray emission spectrum (XES) data processing by developing a standalone application using unsupervised machine learning. However, the task of analyzing the processed spectra remains another challenge. Although the non-resonant Kβ XES of 3d transition metals are known to provide electronic structure information such as oxidation and spin state, finding appropriate parameters to match experimental data is a time-consuming and labor-intensive process. Here, a new XES data analysis method based on the genetic algorithm is demonstrated, applying it to Mn, Co and Ni oxides. This approach is also implemented as a standalone application, Argonne X-ray Emission Analysis 2 (AXEAP2), which finds a set of parameters that result in a high-quality fit of the experimental spectrum with minimal intervention. AXEAP2 is able to find a set of parameters that reproduce the experimental spectrum, and provide insights into the 3d electron spin state, 3d-3p electron exchange force and Kβ emission core-hole lifetime.

MILK: a Python scripting interface to MAUD for automation of Rietveld analysis.

Modern diffraction experiments (e.g. in situ parametric studies) present scientists with many diffraction patterns to analyze. Interactive analyses via graphical user interfaces tend to slow down obtaining quantitative results such as lattice parameters and phase fractions. Furthermore, Rietveld refinement strategies (i.e. the parameter turn-on-off sequences) tend to be instrument specific or even specific to a given dataset, such that selection of strategies can become a bottleneck for efficient data analysis. Managing multi-histogram datasets such as from multi-bank neutron diffractometers or caked 2D synchrotron data presents additional challenges due to the large number of histogram-specific parameters. To overcome these challenges in the Rietveld software Material Analysis Using Diffraction (MAUD), the MAUD Interface Language Kit (MILK) is developed along with an updated text batch interface for MAUD. The open-source software MILK is computer-platform independent and is packaged as a Python library that interfaces with MAUD. Using MILK, model selection (e.g. various texture or peak-broadening models), Rietveld parameter manipulation and distributed parallel batch computing can be performed through a high-level Python interface. A high-level interface enables analysis workflows to be easily programmed, shared and applied to large datasets, and external tools to be integrated with MAUD. Through modification to the MAUD batch interface, plot and data exports have been improved. The resulting hierarchical folders from Rietveld refinements with MILK are compatible with Cinema: Debye-Scherrer, a tool for visualizing and inspecting the results of multi-parameter analyses of large quantities of diffraction data. In this manuscript, the combined Python scripting and visualization capability of MILK is demonstrated with a quantitative texture and phase analysis of data collected at the HIPPO neutron diffractometer.

The elasto-plastic nano- and microscale compressive behaviour of rehydrated mineralised collagen fibres.

The hierarchical design of bio-based nanostructured materials such as bone enables them to combine unique structure-mechanical properties. As one of its main components, water plays an important role in bone's material multiscale mechanical interplay. However, its influence has not been quantified at the length-scale of a mineralised collagen fibre. Here, we couple in situ micropillar compression, and simultaneous synchrotron small angle X-ray scattering (SAXS) and X-ray diffraction (XRD) with a statistical constitutive model. Since the synchrotron data contain statistical information on the nanostructure, we establish a direct connection between experiment and model to identify the rehydrated elasto-plastic micro- and nanomechanical fibre behaviour. Rehydration led to a decrease of 65%-75% in fibre yield stress and compressive strength, and 70% in stiffness with a 3x higher effect on stresses than strains. While in agreement with bone extracellular matrix, the decrease is 1.5-3x higher compared to micro-indentation and macro-compression. Hydration influences mineral more than fibril strain with the highest difference to the macroscale when comparing mineral and tissue levels. The effect of hydration seems to be strongly mediated by ultrastructural interfaces while results provide insights towards mechanical consequences of reported water-mediated structuring of bone apatite. The missing reinforcing capacity of surrounding tissue for an excised fibril array is more pronounced in wet than dry conditions, mainly related to fibril swelling. Differences leading to higher compressive strength between mineralised tissues seem not to depend on rehydration while the lack of kink bands supports the role of water as an elastic embedding influencing energy-absorption mechanisms. STATEMENT OF SIGNIFICANCE: Characterising structure-property-function relationships in hierarchical biological materials helps us to elucidate mechanisms that enable their unique properties. Experimental and computational methods can advance our understanding of their complex behaviour with the potential to inform bio-inspired material development. In this study, we close a gap for bone's fundamental mechanical building block at micro- and nanometre length scales. We establish a direct connection between experiments and simulations by coupling in situ synchrotron tests with a statistical model and quantify the behaviour of rehydrated single mineralised collagen fibres. Results suggest a high influence of hydration on structural interfaces, and the role of water as an elastic embedding by outlining important differences between wet and dry elasto-plastic properties of mineral nanocrystals, fibrils and fibres.

Machine learning assists in increasing the time resolution of X-ray computed tomography applied to mineral precipitation in porous media

Many subsurface engineering technologies or natural processes cause porous medium properties, such as porosity or permeability, to evolve in time. Studying and understanding such processes on the pore scale is strongly aided by visualizing the details of geometric and morphological changes in the pores. For realistic 3D porous media, X-Ray Computed Tomography (XRCT) is the method of choice for visualization. However, the necessary high spatial resolution requires either access to limited high-energy synchrotron facilities or data acquisition times which are considerably longer (e.g. hours) than the time scales of the processes causing the pore geometry change (e.g. minutes). Thus, so far, conventional benchtop XRCT technologies are often too slow to allow for studying dynamic processes. Interrupting experiments for performing XRCT scans is also in many instances no viable approach. We propose a novel workflow for investigating dynamic precipitation processes in porous media systems in 3D using a conventional XRCT technology. Our workflow is based on limiting the data acquisition time by reducing the number of projections and enhancing the lower-quality reconstructed images using machine-learning algorithms trained on images reconstructed from high-quality initial- and final-stage scans. We apply the proposed workflow to induced carbonate precipitation within a porous-media sample of sintered glass-beads. So we were able to increase the temporal resolution sufficiently to study the temporal evolution of the precipitate accumulation using an available benchtop XRCT device.

Review of Current Software for Analyzing Total X-ray Scattering Data from Liquids

The popularity of the pair distribution function (PDF) analysis of X-ray total scattering data has steadily grown as access to ex situ synchrotron data has expanded. Due to the broadening of the PDF user community, there is a growing demand for software that can be used to extract PDFs and is accessible to non-expert users. While user-friendly options have been developed over the past decade for fast, streamlined data analysis, care must be taken in both processing the data and understanding any limitations, especially in the case of liquids. In this review, the same scattering data are analyzed using different total X-ray scattering software, in order to compare the accuracy of the extracted structure factors and associated pair distribution functions. The goal is to assess the best practices for extracting the most accurate liquid data for each software package. The importance of absolute normalization and the application of the most appropriate corrections are emphasized via quantitative comparisons between liquid sulfur and water. Additionally, an awareness of the competing conventions used to define the PDF in crystallography and liquids/glasses is crucial for both the downstream analyses of the data and a comparison with the previous results in the literature.

Human lung virtual histology by multi-scale x-ray phase-contrast computed tomography

Objectives. As the central organ of the respiratory system, the human lung is responsible for supplying oxygen to the blood, which reaches the erythrocytes by diffusion through the alveolar walls and is then distributed throughout the body. By exploiting the difference in electron density detected by a phase shift in soft tissue, high-resolution x-ray phase-contrast computed tomography (XPCT) can resolve biological structures in a sub-μm range, shedding new light on the three-dimensional structure of the lungs, physiological functions and pathological mechanisms. Approach. This work presents both synchrotron and laboratory XPCT results of postmortem tissue from autopsies and biopsies embedded with various preparation protocols such as precision-cut lung slices, cryogenically fixed lung tissue, as well as paraffin and alcohol fixed tissue. The selection of pathological abnormalities includes channel of Lambert, bronchus-associated lymphoid tissue and alveolar capillary dysplasia with misalignment of pulmonary veins. Subsequently, quantification and visualization approaches are presented. Main results. The overall high image quality even of in-house XPCT scans for the case of FFPE biopsies can be exploited for a wide range of pulmonary pathologies and translated to dedicated and optimized instrumentation which could be operated in clinical setting. By using synchrotron radiation, contrast can be further increased to resolve sub-μm sized features down to the sub-cellular level. The results demonstrate that a wide range of preparation protocols including sample mounting in liquids can be used. Significance. With XPCT, poorly understood 3D structures can be identified in larger volume overview and subsequently studied in more detail at higher resolution. With the full 3D structure, the respective physiological functions of airways or vascular networks, and the different pathophysiologic mechanisms can be elucidated or at least underpinned with structural data. Moreover, synchrotron data can be used to validate laboratory protocols and provide ground truth for standardizing the method.

Driekopite, Ideally PtBi, a New Mineral Species from the Driekop Platinum Pipe, Republic of South Africa

Abstract The new mineral driekopite, ideally PtBi, was found in a concentrate from the Driekop mine, one of three zoned Pt pipes (mined from 1925 to 1930) that crosscut the layered mafic and ultramafic sequences of the eastern Bushveld Complex, Republic of South Africa. The holotype grain of driekopite (∼ 22 × 13 μm) occurs in a complex, rounded aggregate ∼120 μm in diameter, in association with isoferroplatinum (Pt3Fe), hollingworthite (RhAsS), geversite (PtSb2), insizwaite (PtBi2), andrieslombaardite (RhSbS), stibiopalladinite (Pd5Sb2), sobolevskite (PdBi), possible tatyanaite (Pt9Cu3Sn4), osmium-bearing tulameenite (Pt2FeCu), and Pt-Fe alloy (∼Pt2Fe). Driekopite appears slightly orange under reflected light compared to Pt-Fe alloys. It shows moderate to strong bireflectance, varying from light yellow to brownish yellow, no pleochroism or internal reflections, and moderate to strong anisotropism. The empirical formula, calculated from the average of six wavelength-dispersive spectrometry analyses made on five grains, on the basis of two atoms, is (Pt0.68Pd0.31Fe0.01)Σ1.00(Bi0.53Sb0.43As0.02Sn0.02S0.01)Σ1.01. The mineral is hexagonal, space group P63/mmc (#194) with the refined unit-cell dimensions a = 4.1993(5), c = 5.6194(6) Å, V = 85.82 Å3, Z = 2, and Dcalc = 12.91 g/cm3. Driekopite is isostructural with NiAs, with mixed compositions of Pt and Pd at the 2a site (0.55:0.45, respectively) and Bi and Sb at the 2c site (0.63:0.37, respectively). Its crystal structure was refined to wR = 6.3% using 13 unique Laue reflections obtained using synchrotron radiation. The six strongest lines for the powder X-ray diffraction pattern calculated from the crystal structure refined from synchrotron data is [d in Å (I) (hkl)]: 3.0531 (92) (101), 2.2234 (100) (102), 2.0997 (77) , 1.5266 (28) (202), 1.2347 (24) , 1.1676 (18) . The holotype grain of driekopite is observed to be paragenetically later than isoferroplatinum and hollingworthite and is considered to be synformational with Bi-bearing geversite, insizwaite, andrieslombaardite, and sobolevskite. The entire aggregate containing these platinum-group minerals is overgrown by a rim of tulameenite and Pt-Fe alloy (∼Pt2Fe), indicating they are paragenetically the last minerals to form. Experiments designed to synthesize PtBi over the range of 200 to 500 °C were all successful. Synthetic PtBi melts congruently at 765 °C, suggesting that driekopite likely crystallized at sub-magmatic temperatures.

The heterometallic one-dimensional solvated coordination polymer [NiPt2Cl6(TRIP-Py)4]n.

The ditopic ligand 10-[4-(pyridin-4-yl)phenyl]-9-phospha-10-silatriptycene (TRIP-Py, C29H20NPSi) binds as a pyridine donor to NiII and as a phosphatriptycene donor towards PtII. The selectivity relies entirely on the Pearson character of the donor sites and the matching hardness of the respective metal cations. The product is the one-dimensional coordination polymer catena-poly[[[dichloridonickel(II)]-bis{μ-10-[4-(pyridin-4-yl)phenyl]-9-phospha-10-silatriptycene}-bis[dichloridoplatinum(II)]-bis{μ-10-[4-(pyridin-4-yl)phenyl]-9-phospha-10-silatriptycene}] dichloromethane pentasolvate ethanol icosasolvate], {[NiPt2Cl6(TRIP-Py)4]·5CH2Cl2·20EtOH}n (1), which retains large pores due to the inherent rigidity of the ligand. This is enabled by the caged triptycene scaffold which fixes the direction of the phosphorus donor with respect to the remaining molecule and especially the pyridyl moiety. In its crystal structure, which was determined from synchrotron data, the pores of the polymer are filled with dichloromethane and ethanol molecules. Finding a suitable model for the pore content is complicated as it is too disordered to give a reasonable atomic model but too ordered to be described by an electron gas solvent mask. This article presents an in-depth description of this polymer, as well as a discussion on the use of the bypass algorithm for solvent masks.