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CoSb3, a skutterudite compound, is key in studying thermoelectric materials. Under compression, it undergoes a 'self-insertion' isostructural transition, redistributing large Sb atoms among crystallographic sites. We investigated CoSb3's structural stability up to 70 GPa using single crystal X-ray diffraction and high-resolution X-ray scattering, including Bragg Coherent Diffraction Imaging. We examined the material in three pressure transmitting media (PTMs), exploring how PTMs and nonhydrostatic stresses affect CoSb3. Notably, the 'self-insertion' transition may reduce or even make compressibility negative. Additionally, we report a previously unknown phase transformation from cubic Im-3 to trigonal R-3 above 40 GPa and discuss the phases' distinctive behaviors., Comment: Manuscript: 27 pages, 12 Figures

The self-assembly of anisotropic nanocrystals (stabilized by organic capping molecules) with pre-selected composition, size, and shape allows for the creation of nanostructured materials with unique structures and features. For such a material, the shape and packing of the individual nanoparticles play an important role. This work presents a synthesis procedure for {\omega}-thiol-terminated polystyrene (PS-SH) functionalized gold nanooctahedra of variable size (edge length 37, 46, 58, and 72 nm). The impact of polymer chain length (Mw: 11k, 22k, 43k, and 66k g/mol) on the growth of colloidal crystals (e.g. mesocrystals) and their resulting crystal structure is investigated. Small-angle X-ray scattering (SAXS) and scanning transmission electron microscopy (STEM) methods provide a detailed structural examination of the self-assembled faceted mesocrystals based on octahedral gold nanoparticles of different size and surface functionalization. Three-dimensional angular X-ray cross-correlation analysis (AXCCA) enables high-precision determination of the superlattice structure and relative orientation of nanoparticles in mesocrystals. This approach allows us to perform non-destructive characterization of mesocrystalline materials and reveals their structure with resolution down to the nanometer scale., Comment: 46 pages, 5 figures, 12 Supplementary Information figures, 1 Table in the main text, 1 Table in Supplementary Information

The study of the structure of viruses by X-ray free-electron lasers (XFEL) attracts more attention in recent decades. Such experiments are based on the collection of two-dimensional diffraction patterns measured at the detector after diffraction of femtosecond X-ray pulses on biological samples. In order to prepare the experiment at the European XFEL we simulated the diffraction data for the tick-borne encephalitis virus (TBEV) with different parameters and identified their optimal values. Following necessary steps of a well-established data processing pipeline, the structure of TBEV was obtained and the efficiency of the used methods was demonstrated., Comment: 24 pages, 7 figures

We show that the decomposition of caesium lead halide perovskite nanocrystals under continuous X-ray illumination depends on the surface ligand. For oleic acid/oleylamine, we observe a fast decay accompanied by the formation of elemental lead and halogen. Upon surface functionalization with a metal porphyrin derivate, the decay is markedly slower and involves the disproportionation of lead to Pb0 and Pb3+. In both cases, the decomposition is preceded by a contraction of the atomic lattice, which appears to initiate the decay. We find that the metal porphyrin derivative induces a strong surface dipole on the nanocrystals, which we hold responsible for the altered and slower decomposition pathway. These results are important for application of lead halide perovskite nanocrystals in X-ray scintillators., Comment: 31 pages, 14 Figures

Single particle imaging (SPI) at X-ray free electron lasers (XFELs) is particularly well suited to determine the 3D structure of particles in their native environment. For a successful reconstruction, diffraction patterns originating from a single hit must be isolated from a large number of acquired patterns. We propose to formulate this task as an image classification problem and solve it using convolutional neural network (CNN) architectures. Two CNN configurations are developed: one that maximises the F1-score and one that emphasises high recall. We also combine the CNNs with expectation maximization (EM) selection as well as size filtering. We observed that our CNN selections have lower contrast in power spectral density functions relative to the EM selection, used in our previous work. However, the reconstruction of our CNN-based selections gives similar results. Introducing CNNs into SPI experiments allows streamlining the reconstruction pipeline, enables researchers to classify patterns on the fly, and, as a consequence, enables them to tightly control the duration of their experiments. We think that bringing non-standard artificial intelligence (AI) based solutions in a well-described SPI analysis workflow may be beneficial for the future development of the SPI experiments., Comment: Main text: 28 pages, 7 figures, Supporting Information: 12 pages, 6 figures

Depending on the volume fraction and interparticle interactions, colloidal suspensions can form different phases, ranging from fluids, crystals, and glasses to gels. For soft microgels that are made from thermoresponsive polymers, the volume fraction can be tuned by temperature, making them excellent systems to experimentally study phase transitions in dense colloidal suspensions. However, investigations of phase transitions at high particle concentration and across the volume phase transition temperature in particular, are challenging due to the deformability and possibility for interpenetration between microgels. Here, we investigate the dense phases of composite core-shell microgels that have a small gold core and a thermoresponsive microgel shell. Employing Ultra Small Angle X-ray Scattering, we make use of the strong scattering signal from the gold cores with respect to the almost negligible signal from the shells. By changing the temperature we study the freezing and melting transitions of the system in-situ. Using Bragg peak analysis and the Williamson-Hall method, we characterize the phase transitions in detail. We show that the system crystallizes into an rhcp structure with different degrees of in-plane and out-of-plane stacking disorder that increase upon particle swelling. We further find that the melting process is distinctly different, where the system separates into two different crystal phases with different melting temperatures and interparticle interactions.

We correlate spatially resolved fluorescence (-lifetime) measurements with X-ray nanodiffraction to reveal surface defects in supercrystals of self-assembled caesium lead halide perovskite nanocrystals and study their effect on the fluorescence properties. Upon comparison with density functional modelling, we show that a loss in structural coherence, an increasing atomic misalignment between adjacent nanocrystals, and growing compressive strain near the surface of the supercrystal are responsible for the observed fluorescence blueshift and decreased fluorescence lifetimes. Such surface defect-related optical properties extend the frequently assumed analogy between atoms and nanocrystals as so-called quasi-atoms. Our results emphasize the importance of minimizing strain during the self-assembly of perovskite nanocrystals into supercrystals for lighting application such as superfluorescent emitters., Comment: 61 pages, 34 figures

Second-order intensity interferometry was employed to study the spatial and temporal properties of the European X-ray Free-Electron Laser (EuXFEL). Measurements were performed at the soft X-ray SASE3 undulator beamline at a photon energy of 1.2 keV in the Self-Amplified Spontaneous Emission (SASE) mode. Two high-power regimes of the SASE3 undulator settings, i.e. linear and quadratic tapering at saturation, were studied in detail and compared with the linear gain regime. The statistical analysis showed an exceptionally high degree of spatial coherence up to 90% for the linear undulator tapering. Analysis of the measured data in spectral and spatial domains provided an average pulse duration of about 10 fs in our measurements. The obtained results will be valuable for the experiments requiring and exploiting short pulse duration and utilizing high coherence properties of the EuXFEL., Comment: 12 pages, 6 figures, 2 tables

Single particle imaging (SPI) is a promising method for native structure determination which has undergone a fast progress with the development of X-ray Free-Electron Lasers. Large amounts of data are collected during SPI experiments, driving the need for automated data analysis. The necessary data analysis pipeline has a number of steps including binary object classification (single versus multiple hits). Classification and object detection are areas where deep neural networks currently outperform other approaches. In this work, we use the fast object detector networks YOLOv2 and YOLOv3. By exploiting transfer learning, a moderate amount of data is sufficient for training of the neural network. We demonstrate here that a convolutional neural network (CNN) can be successfully used to classify data from SPI experiments. We compare the results of classification for the two different networks, with different depth and architecture, by applying them to the same SPI data with different data representation. The best results are obtained for YOLOv2 color images linear scale classification, which shows an accuracy of about 97% with the precision and recall of about 52% and 61%, respectively, which is in comparison to manual data classification., Comment: 23 pages, 6 figures, 3 tables

An improved analysis for single particle imaging (SPI) experiments, using the limited data, is presented here. Results are based on a study of bacteriophage PR772 performed at the AMO instrument at the Linac Coherent Light Source (LCLS) as part of the SPI initiative. Existing methods were modified to cope with the shortcomings of the experimental data: inaccessibility of information from the half of the detector and small fraction of single hits. General SPI analysis workflow was upgraded with the expectation-maximization based classification of diffraction patterns and mode decomposition on the final virus structure determination step. The presented processing pipeline allowed us to determine the three-dimensional structure of the bacteriophage PR772 without symmetry constraints with a spatial resolution of 6.9 nm. The obtained resolution was limited by the scattering intensity during the experiment and the relatively small number of single hits., Comment: 40 pages, 7 figures (main text), 2 tables (main text), 14 figures (supplementary information), 1 table (supplementary information)

Semiconductive nanocrystals (NCs) can be self-assembled into ordered superlattices (SLs) to create artificial solids with emerging collective properties. Computational studies have predicted that properties such as electronic coupling or charge transport are determined not only by the individual NCs but also by the degree of their organization and structure. However, experimental proof for a correlation between structure and charge transport in NC SLs is still pending. Here, we perform X-ray nano-diffraction and apply Angular X-ray Cross-Correlation Analysis (AXCCA) to characterize the structures of coupled PbS NC SLs, which are directly correlated with the electronic properties of the same SL microdomains. We find strong evidence for the effect of SL crystallinity on charge transport and reveal anisotropic charge transport in highly ordered monocrystalline hexagonal close-packed PbS NC SLs, caused by the dominant effect of shortest interparticle distance. This implies that transport anisotropy should be a general feature of weakly coupled NC SLs., Comment: 49 pages, 20 Figures