The effect of lowered pH on the thermal gelation behavior of hen egg yolk was investigated over the temperature range of 58-72 °C using low-dose X-ray photon correlation spectroscopy in ultra-small-angle X-ray scattering geometry. Progressive structural and dynamical alterations were observed at room temperature with decreasing pH, indicative of acid-induced protein denaturation, which correlates with an increase in yolk viscosity. Temperature- and pH-dependent structural and dynamic investigation suggests an acceleration in gel formation with decreasing pH. The time-temperature superposition relationship observed in all samples suggests an identical mechanism underlying protein aggregation-gelation with a temperature-dependent reaction rate. The sol-gel transition time extracted from kinetic and dynamic information follows Arrhenius behavior, with no significant change in the activation energy (450 ± 20 kJ/mol) of gelation. However, the prefactor A systematically decreases with decreasing pH, indicating that acidification accelerates gelation primarily by increasing the frequency of productive encounters without altering the fundamental energy barrier of the process.

The molecular mechanisms governing internal fluctuations in intrinsically disordered protein (IDP) assemblies are crucial to the stability and dynamics of both regulated and aberrant toxic cellular aggregates, but remain poorly understood. By comprehensively combining high-resolution quasi-elastic neutron scattering with all-atom molecular dynamics simulations, we probe the motions of [Formula: see text]-casein, a model IDP, inside its assemblies. We uncover a previously unresolved slow relaxation process with phenomenological characteristics of anomalous non-Fickian diffusion. This anomalous signature emerges from a continuous mobility gradient governed by density and crowding within the assemblies; the core is denser and more compact, and mobility increases progressively toward the exterior. This dynamical heterogeneity underlies the non-Gaussian behavior and accounts for the observed spectral broadening. Our findings provide insight into how disorder and extreme local crowding within IDP assemblies can result in a fundamentally different behavior compared to, e.g., clusters of well-folded proteins. The deviations from Fickian diffusion arise from dynamic heterogeneity and can be captured within the framework by a model typically used for the jump diffusion observed in liquids, thereby extending its applicability.

The formation of donor-acceptor complexes (DACs) between the electron donor Dibenzotetrathiafulvalene (DBTTF) and the acceptor Hexaazatriphenylenehexacarbonitrile (HATCN) results in a separated phase with a distinctly different crystal structure as well as optical absorption bands below the energy gaps of the two pristine materials. X-ray scattering and atomic force microscopy provide detailed insights into the film structure and morphology by systematic variation of the mixing ratio from pristine DBTTF to pristine HATCN. The measured electrical conductivity of thin films depends in a highly nonmonotonic manner on the composition of the mixture and shows significantly improved charge transport compared to the pristine films. The temperature-dependent conductivity, charge carrier concentration, and mobility were investigated across these compositions. Surprisingly, all compositions exhibited n-type behavior, except for pristine DBTTF. This behavior is explained by the electronic structure of the mixtures, as revealed by ultraviolet photoelectron spectroscopy, which indicates that charge injection and transport occur via the lowest unoccupied molecular orbital of the DAC and HATCN. Additionally, the observed electrical conductivity is strongly influenced by the morphology and structural ordering of the films. These findings offer valuable insights for the design of advanced materials with enhanced electrical performance.

Advances in X-ray and neutron sources, as well as in area-detector technologies, enable the recording of several terabytes of raw two-dimensional detector data in a single experiment. While several efficient integration and conversion tools are available for data collected in transmission geometry, analogous solutions for grazing-incidence diffraction (including grazing-incidence X-ray diffraction and grazing-incidence wide-angle X-ray scattering) experiments have not yet achieved the same level of efficiency. The development of new data analysis tools, including machine-learning-based software for X-ray data, necessitates the establishment of a standardized format for the converted data. To address these challenges, we have developed a new Python library, pygid, which is designed to facilitate fast data processing while providing compatibility with various raw data formats, a standardized data storage format and an intuitive interface for straightforward use. pygid supports three types of coordinate systems and both transmission and grazing-incidence geometries. It is capable of handling large datasets, performing one-dimensional line cuts and simulating expected Bragg peak positions for given structures. The package facilitates sample and experimental metadata curation in accordance with the FAIR principles. As an integral part of the broader mlgid pipeline, pygid serves as the initial step linking raw scattering patterns with machine learning tools for data analysis. The pygid package is accessible at https://github.com/mlgid-project.

The ion-activated patchy particle model is an important theoretical framework to investigate the phase behavior of globular proteins in the presence of multivalent ions. In this study, we examine and highlight the influence of patch heterogeneity on the extension, appearance, and disappearance of the liquid-liquid coexistence region of the phase diagram. We demonstrate that within this model the binding energy between salt ions and patches of different types is a key factor in determining the phase behavior. Specifically, we show under which conditions liquid-liquid phase separation (LLPS) in these systems can appear or disappear for varying binding energy and ion-mediated attraction energy between ion-occupied and unoccupied patches. In particular, we address the influence of the patch type dependence of these energies on the (dis)appearance of LLPS. These results rationalize our new results on ion-dependent liquid-liquid phase separation in solutions of bovine serum albumin with trivalent cations. In comparison with models with non-activated patches, where the gas-liquid transition disappears when the number of patches approaches two, we find the complementary mechanism that ions may shift the attractions from stronger to weaker patches (with an accompanying disappearance of the transition) if their binding energy to the patches changes. The results have implications for the understanding of charge-driven LLPS in biological systems and its suppression.

The electronic and optical properties of organic semiconductors are strongly determined by their structural properties. Combining two or more semiconductor compounds in multicomponent blends is commonly exploited to tune the properties and meet the requirements for high-performance applications such as organic solar cells, light-emitting diodes, and transistors. Here, we discuss the structural and optical properties characteristic of binary systems containing the archetypal organic semiconductor pentacene. Typical examples are shown for the formation of a solid solution, a co-crystal, and phase separation. They not only allow the elucidation of the mixing behavior in more complicated binary systems but also broaden the understanding of binary blends in general. We highlight the importance of the local occupation configuration geometry and environment beyond the global thermodynamic mean-field considerations of mixing vs demixing. A thorough understanding of mixing in small organic molecule binary blends on the nanoscale is highly beneficial for capitalizing on the full power of organic semiconductors.

Thin film deposition on weakly interacting substrates exhibits a unique growth mode characterized by initially strong island formation and rapidly increasing roughness, which reaches a maximum and subsequently decreases as the film returns to a smooth morphology. Here we show this rough-to-smooth growth mode experimentally for two molecular systems with substantially different geometries, namely, the effectively spherical buckminsterfullerene (C_{60}) and the disk-like 1,4,5,8,9,11-hexaazatriphenylenehexacarbonitrile. This growth mode is explained by a geometrical model that captures the basic mechanisms of multilayer island growth, island coalescence, and formation of a continuous film. Additionally, kinetic Monte Carlo simulations with minimal ingredients demonstrate that this mode generally occurs for weakly interacting substrates, providing quantitative estimates of parameters that characterize adsorbate-adsorbate and adsorbate-substrate interactions. Both the model and simulations accurately describe the experimental data and highlight the generic nature of the phenomenon, independently of the details of the interactions and the molecular flux, which opens up a path for controlling nanoscale film roughness.

Macromolecular crowding plays a crucial role in modulating protein dynamics in cellular and in vitro environments. Polymeric crowders such as dextran and Ficoll are known to induce entropic forces, including depletion interactions, that promote structural organization, yet their nanoscale consequences for protein dynamics remain poorly understood. Here, we employ megahertz X-ray photon correlation spectroscopy (MHz-XPCS) at the European X-ray Free Electron Laser (XFEL) to probe the dynamics of the protein ferritin in solutions containing sucrose, dextran, and Ficoll. We find pronounced changes in collective protein dynamics in polymeric crowders, revealing depletion-driven short-range attractions that, combined with long-range repulsions, give rise to intermediate-range organization. These mesoscale correlations undergo collective relaxation on microsecond to millisecond timescales, as directly resolved by XPCS through the decay of ferritin density fluctuations. The magnitude of this depends sensitively on crowder molecular weight and type. Normalizing the crowder concentration by c* reveals scaling behavior of ferritin self-diffusion with a crossover near 2c*, marking a transition from depletion-enhanced mobility to viscosity-dominated slowing. Our results demonstrate that bulk properties alone are insufficient to describe protein dynamics in crowded solutions, highlighting the need to include polymer-specific interactions and depletion theory in models of crowded environments.

Flat colloidal PbSe QDs (fQDs) represent an innovative class of 2D near-infrared (NIR) photoluminescent QDs, which combine extreme thickness with additional lateral confinement. PbSe fQDs exhibit efficient NIR photoluminescence (860-1550 nm) that is adjustable to the low-loss transmission windows of (optical) fibers and makes them highly promising nanoemitters for fiber-based applications. Here, we demonstrate the incorporation of PbSe fQDs into easy-to-handle functional and stable jet electrospun poly(methyl methacrylate) (PMMA) fibers. Within these electrospun nanocomposites, we find perpendicularly alignedstacks of PbSe fQDs, which give rise to a narrowed and bathochromically shifted photoluminescence (e.g., at 1073 nm, with a quantum yield of 5%) that is caused by an energy transfer into the smallest band gap tail of the PbSe fQD thickness distribution. Embedding PbSe fQDs into solid-state nanocomposite fibers represents an important step forward for implementing near-infrared (NIR)-emitting 2D PbX nanocrystals in fiber optics.

Low-density lipoproteins (LDLs) are central to nutrient transport in egg yolk and have emerged as natural nanocarriers for drug delivery. Their biological function critically depends on mobility within densely crowded environments, yet the mechanisms governing their motion remain elusive, largely because conventional techniques cannot access the relevant microsecond timescales. Here, we employ megahertz X-ray photon correlation spectroscopy at the European X-ray Free Electron Laser facility to resolve LDL dynamics in native yolk-plasma. This approach reveals transient caging and memory effects and shows that the combined influence of particle softness and hydrodynamic coupling slows diffusion by nearly two orders of magnitude compared to dilute solutions. However, this reduction could not be scaled with an increase in macroscopic viscosity obtained from rheometry, indicating deviations from the Stokes-Einstein relation. Despite this slowdown, yolk-plasma remains a "sluggish yet liquid state", balancing dense packing and the fluidity required for lipid release during embryonic development. These results establish a quantitative framework connecting microstructure, hydrodynamics, and transport in crowded soft-matter systems, with implications for developmental biology and nanomedicine.

In this article, we present the experimental protocol and data-processing framework for megahertz X-ray Photon Correlation Spectroscopy (MHz-XPCS) experiments on soft matter samples implemented at the Materials Imaging and Dynamics (MID) instrument of the European X-ray Free-Electron Laser (EuXFEL). Due to the introduction of a standard configuration and the implementation of a highly automated data-processing pipeline, MHz-XPCS measurements can now be conducted and analyzed with minimal user intervention. A key challenge lies in managing the extremely large data volumes generated by the Adaptive Gain Integrating Pixel Detector (AGIPD) - often reaching several petabytes within a single experiment. We describe the technical implementation, discuss the hardware requirements related to effective parallel data processing and propose strategies to enhance data quality, in particular related to data reduction strategies and an improvement of the signal-to-noise ratio. Finally, we address strategies for making the processed data FAIR (Findable, Accessible, Interoperable, Reusable), in alignment with the goals of the DAPHNE4NFDI project.

Protein crystallization is key to determining the structure of proteins at atomic resolution. It can occur naturally, including in pathological pathways, for instance with aquaporin and γ-crystallin proteins. A fundamental understanding of the underlying crystallization process is both technologically and biologically relevant. A multitechnique approach is employed here to investigate protein crystallization in situ, allowing us to assess the evolution of the liquid suspension and crystallite structure as well as protein diffusion during the crystallization process. The wide range of methods probe the sample on ångström to millimetre length scales, accessing nanosecond to millisecond dynamics information while acquiring data with minute-timescale kinetic resolution during crystallization. This process takes several hours from an initial state of monomers or small clusters until the presence of large crystallites. Employing neutron spectroscopy allows us to distinguish different crystallization pathways and to reveal the presence of coexisting clusters during the entire crystallization process. We demonstrate the multitechnique approach on human serum albumin (HSA) proteins crystallized from aqueous solution in the presence of LaCl3. For this system, the crystallization kinetics can be consistently described by a sigmoid function across all methods, and the kinetics can be controlled by the salt concentration. Moreover, we compare the HSA-LaCl3 model system with the crystallization behavior of β-lactoglobulin-CdCl2, which includes a metastable intermediate state.

We investigate the effects of D2O (heavy water) versus H2O (normal water) on protein adsorption and crystallization using human serum albumin (HSA) as a model protein in the presence of lanthanum chloride (LaCl3). We use optical microscopy to investigate the crystallization, quartz crystal microbalance with dissipation monitoring (QCM-D) to follow protein adsorption, and dynamic light scattering (DLS) to study cluster formation prior to crystallization. The results show that D2O induces a higher crystallization density (number of crystals) and the formation of larger crystals; furthermore, D2O significantly slows down the crystallization kinetics. HSA adsorbs more mass at the surface when the solvent is heavy water, which contributes to the higher crystallization density. Additionally, we find that in heavy water, larger clusters are stabilized prior to crystal growth, which delays the kinetics of crystallization. We speculate that this is due to the modified effective solvent interactions.

Ordered arrays of nanocrystals, called supercrystals, have attracted significant attention owing to the collective quantum effects arising from the coupling between neighboring nanocrystals. In particular, lead halide perovskite nanocrystals are widely used because of the combination of the optical properties and faceted cubic shape, which enables the formation of highly ordered supercrystals. The most frequently used method for the fabrication of perovskite supercrystals is based on the self-assembly of nanocrystals from solution via slow evaporation of the solvent. However, the supercrystals produced with this technique grow in random positions on the substrate. Moreover, they are mechanically soft due to the presence of organic ligands around the individual nanocrystals. Therefore, such supercrystals cannot be easily manipulated with microgrippers, which hinders their use in applications. In this work, we synthesize mechanically robust supercrystals built from cubic lead halide perovskite nanocrystals by a two-layer phase diffusion self-assembly with acetonitrile as the antisolvent. This method yields highly faceted thick supercrystals, which are robust enough to be picked up and relocated by microgrippers. We employed X-ray nanodiffraction together with high-resolution scanning electron microscopy and atomic force microscopy to reveal the structure of CsPbBr3, CsPbBr2Cl, and CsPbCl3 supercrystals assembled using the two-layer phase diffusion technique and explain their unusual mechanical robustness. Our findings are crucial for further experiments and applications in which supercrystals need to be placed in a precise location, for example, between the electrodes in an electro-optical modulator.

The crystallization conditions of proteins are sensitive to the prevailing interactions. Even the two similar proteins, bovine and human serum albumin (BSA and HSA), exhibit different crystallization conditions despite their comparable function, biophysical properties, shape, and size (approximate to 60 kDa and a 75.8% sequence identity). In this work, we provide a comparison of specific and nonspecific interactions regarding the crystallization behavior of BSA and HSA. The results of the analysis of crystal packing interfaces indicate that HSA uses a relatively larger part of its surface area to establish crystal contacts compared to its bovine counterpart. Likewise, HSA utilizes more of its residues for crystal contact formation, offering a broader range of options to establish attractive interactions. Phase diagrams of the BSA-PEG and HSA-PEG systems were established in order to gain more precise insights into the nonspecific depletion interactions. It turns out that BSA crystallizes predominantly via depletion interactions, whereas HSA does not. Subsequent systematic small-angle scattering (SAXS) measurements of the two systems in combination with quantitative modeling provide insights into the induced effective interactions, allowing for a better understanding of the two protein-PEG systems. The results obtained were compared to the previously established reentrant condensation (RC) phase behavior of BSA and HSA. The RC phase behavior is caused by the specific interaction of proteins with added multivalent cations. In this case, HSA crystallizes, but BSA does not. This comparison emphasizes the different roles of specific and nonspecific interactions for the crystallization behavior of BSA and HSA.

Neutrons, owing to their unique properties, serve as indispensable probes for investigating the structure and dynamics of materials across various length scales. The scientific community utilizing neutron research infrastructures encompasses a diverse range of disciplines, making it challenging to quantify its scientific and societal impact. To address this challenge, we apply Natural Language Processing (NLP) and machine learning techniques to analyze the scientific output of the European neutron science community. Leveraging open-source software toolkits, our method allows for the quantitative assessment of community evolution and research focus. Our analysis reveals consistent growth in the neutron community despite a reduction in sources, underscoring the enduring significance of neutron methods in scientific research. Furthermore, an increase in unique authors and an even distribution of publications across diverse scientific topics highlight the community’s interdisciplinary nature and collaborative spirit. While this study emphasizes neutron scattering, our methodology holds promise for a broad range of scientific communities reliant on Large Research Infrastructures (LRIs), offering opportunities for collaboration, optimization of experimental approaches, and informed decision-making by governmental and funding bodies.

Metal halide perovskites have shown exceptional potential in converting solar energy to electric power in photovoltaics, yet their application is hampered by limited operational stability. This stimulated the development of hybrid layered (two-dimensional, 2D) halide perovskites based on hydrophobic organic spacers, templating perovskite slabs, as a more stable alternative. However, conventional organic spacer cations are electronically insulating, resulting in charge confinement within the inorganic slabs, thus limiting their functionality. This can be ameliorated by extending the π-conjugation of the spacer cations. We demonstrate the capacity to access Ruddlesden-Popper and Dion-Jacobson 2D perovskites incorporating for the first time aryl-acetylene-based (4-ethynylphenyl)methylammonium (BMAA) and buta-1,3-diyne-1,4-diylbis(4,1-phenylene)dimethylammonium (BDAA) spacers, respectively. We assess their unique opto(electro)ionic characteristics by a combination of techniques and apply them in mixed-dimensional perovskite solar cells that show superior device performances with a power conversion efficiency of up to 23 % and higher operational stability, opening the way for multifunctionality in layered hybrid materials and their application.

Understanding protein motion within the cell is crucial for predicting reaction rates and macromolecular transport in the cytoplasm. A key question is how crowded environments affect protein dynamics through hydrodynamic and direct interactions at molecular length scales. Using megahertz X-ray Photon Correlation Spectroscopy (MHz-XPCS) at the European X-ray Free Electron Laser (EuXFEL), we investigate ferritin diffusion at microsecond time scales. Our results reveal anomalous diffusion, indicated by the non-exponential decay of the intensity autocorrelation function g 2 ( q , t ) at high concentrations. This behavior is consistent with the presence of cage-trapping between the short- and long-time protein diffusion regimes. Modeling with the δ γ -theory of hydrodynamically interacting colloidal spheres successfully reproduces the experimental data by including a scaling factor linked to the protein direct interactions. These findings offer insights into the complex molecular motion in crowded protein solutions, with potential applications for optimizing ferritin-based drug delivery, where protein diffusion is the rate-limiting step.