On the analysis of two-time correlation functions: equilibrium versus non-equilibrium systems.

X-ray photon correlation spectroscopy (XPCS) is a powerful tool for the investigation of dynamics covering a broad range of timescales and length scales. The two-time correlation function (TTC) is commonly used to track non-equilibrium dynamical evolution in XPCS measurements, with subsequent extraction of one-time correlations. While the theoretical foundation for the quantitative analysis of TTCs is primarily established for equilibrium systems, where key parameters such as the diffusion coefficient remain constant, non-equilibrium systems pose a unique challenge. In such systems, different projections ('cuts') of the TTC may lead to divergent results if the underlying fundamental parameters themselves are subject to temporal variations. This article explores widely used approaches for TTC calculations and common methods for extracting relevant information from correlation functions, particularly in the light of comparing dynamics in equilibrium and non-equilibrium systems.

Accessing self-diffusion on nanosecond time and nanometre length scales with minute kinetic resolution.

Neutron spectroscopy uniquely and non-destructively accesses diffusive dynamics in soft and biological matter, including for instance proteins in hydrated powders or in solution, and more generally dynamic properties of condensed matter on the molecular level. Given the limited neutron flux resulting in long counting times, it is important to optimize data acquisition for the specific question, in particular for time-resolved (kinetic) studies. The required acquisition time was recently significantly reduced by measurements of discrete energy transfers rather than quasi-continuous neutron scattering spectra on neutron backscattering spectrometers. Besides this reduction in acquisition times, smaller amounts of samples can be measured with better statistics, and most importantly, kinetically changing samples, such as aggregating or crystallizing samples, can be followed. However, given the small number of discrete energy transfers probed in this mode, established analysis frameworks for full spectra can break down. Presented here are new approaches to analyze measurements of diffusive dynamics recorded within fixed windows in energy transfer, and these are compared with the analysis of full spectra. The new approaches are tested by both modeled scattering functions and a comparative analysis of fixed energy window data and full spectra on well understood reference samples. This new approach can be employed successfully for kinetic studies of the dynamics focusing on the short-time apparent center-of-mass diffusion.

Salt induced slowdown of kinetics and dynamics during thermal gelation of egg-yolk.

We investigated the effect of the NaCl concentration (0.3-2M) on the structure and dynamics of hen egg yolk at room temperature and during thermal gelation at temperatures in the range of 66-90 °C utilizing low-dose x-ray photon correlation spectroscopy in ultra-small angle x-ray scattering geometry. With an increase in the salt concentration, we observe progressive structural and dynamic changes at room temperature, indicating the disruption of yolk components such as yolk-granules and yolk-plasma proteins. Temperature- and salt-dependent structural and dynamic investigations suggest a delay in the gel formation and aggregation of yolk low-density lipoproteins with increasing ionic strength. However, 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's behavior, and the activation energy (460 kJ/mol) is found to be independent of the salt concentration.

From Chalcogen Bonding to S-π Interactions in Hybrid Perovskite Photovoltaics.

The stability of hybrid organic-inorganic halide perovskite semiconductors remains a significant obstacle to their application in photovoltaics. To this end, the use of low-dimensional (LD) perovskites, which incorporate hydrophobic organic moieties, provides an effective strategy to improve their stability, yet often at the expense of their performance. To address this limitation, supramolecular engineering of noncovalent interactions between organic and inorganic components has shown potential by relying on hydrogen bonding and conventional van der Waals interactions. Here, the capacity to access novel LD perovskite structures that uniquely assemble through unorthodox S-mediated interactions is explored by incorporating benzothiadiazole-based moieties. The formation of S-mediated LD structures is demonstrated, including one-dimensional (1D) and layered two-dimensional (2D) perovskite phases assembled via chalcogen bonding and S-π interactions, through a combination of techniques, such as single crystal and thin film X-ray diffraction, as well as solid-state NMR spectroscopy, complemented by molecular dynamics simulations, density functional theory calculations, and optoelectronic characterization, revealing superior conductivities of S-mediated LD perovskites. The resulting materials are applied in n-i-p and p-i-n perovskite solar cells, demonstrating enhancements in performance and operational stability that reveal a versatile supramolecular strategy in photovoltaics.

From adsorption to crystallization of proteins: Evidence for interface-assisted nucleation.

Protein crystallization is among the key processes in biomolecular research, but the underlying mechanisms are still elusive. Here, we address the role of inevitable interfaces for the nucleation process. Quartz crystal microbalance with dissipation monitoring (QCM-D) with simultaneously optical microscopy, confocal microscopy, and grazing-incidence small angle X-rays scattering (GISAXS) were employed to investigate the temporal behavior from the initial stage of protein adsorption to crystallization. Here we studied the crystallization of the Human Serum Albumin (HSA), the most abundant blood protein, in the presence of a charged surface and a trivalent salt. We found evidence for interface-assisted nucleation of crystals. The kinetic stages involved are initial adsorption followed by enhanced adsorption after longer times, subsequent nucleation, and finally crystal growth. The results highlight the importance of interfaces for protein phase behavior and in particular for nucleation.

The ion-activated attractive patchy particle model and its application to the liquid-vapor phase transitions.

Patchy particles are an intriguing subject of study and indeed a model system in the field of soft matter physics. In recent years, patchy particle models have been applied to describe a wide variety of systems, including colloidal crystals, macromolecular interactions, liquid crystals, and nanoparticle assemblies. Given the importance of the topic, rationalizing and capturing the basic features of these models is crucial to their correct application in specific systems. In this study, we extend the ion-activated attractive patchy particles model previously employed to elucidate the phase behavior of protein solutions in the presence of trivalent salts. Our extension incorporates the effect of repulsion between unoccupied and occupied binding sites, depicted as patches. Furthermore, we examine the influence of model parameters on the liquid-vapor coexistence region within the phase diagram, employing numerical methods. A deeper understanding of this model will facilitate a better comprehension of the effects observed in experiments.

Helical interfacial modulation for perovskite photovoltaics.

Hybrid metal halide perovskites have demonstrated remarkable performances in modern photovoltaics, although their stabilities remain limited. We assess the capacity to advance their properties by relying on interfacial modulators featuring helical chirality based on P,M-(1-methylene-3-methyl-imidazolium)[6]helicene iodides. We investigate their characteristics, demonstrating comparable charge injection for enantiomers and the racemic mixture. Overall, they maintain the resulting photovoltaic performance while improving operational stability, challenging the role of helical chirality in the interfacial modulation of perovskite solar cells.

Evolution of Defects, Morphology, and Strain during FAMAPbI3 Perovskite Vacuum Deposition: Insights from In Situ Photoluminescence and X-ray Scattering.

At present, the power conversion efficiency of single-junction perovskite-based solar cells reaches over 26%. The further efficiency increase of perovskite-based optoelectronic devices is limited mainly by defects, causing the nonradiative recombination of charge carriers. To improve efficiency and ensure reproducible fabrication of high-quality layers, it is crucial to understand the perovskite nucleation and growth mechanism along with associated process control to reduce the defect density. In this study, we investigate the growth kinetics of a promising narrow bandgap perovskite, formamidinium methylammonium lead iodide (FAMAPbI3), for high-performance single-junction solar cells. The temporal evolution of structural and optoelectronic properties during FAMAPbI3 vacuum codeposition was inspected in real time by grazing-incidence wide-angle X-ray scattering and photoluminescence. Such a combination of analytical techniques unravels the evolution of intrinsic defect density and layer morphology correlated with lattice strain from the early stages of the perovskite deposition.

Inferior Frontal Sulcal Hyperintensities on Brain MRI Are Associated with Amyloid Positivity beyond Age-Results from the Multicentre Observational DELCODE Study.

Inferior frontal sulcal hyperintensities (IFSHs) on fluid-attenuated inversion recovery (FLAIR) sequences have been proposed to be indicative of glymphatic dysfunction. Replication studies in large and diverse samples are nonetheless needed to confirm them as an imaging biomarker. We investigated whether IFSHs were tied to Alzheimer's disease (AD) pathology and cognitive performance. We used data from 361 participants along the AD continuum, who were enrolled in the multicentre DELCODE study. The IFSHs were rated visually based on FLAIR magnetic resonance imaging. We performed ordinal regression to examine the relationship between the IFSHs and cerebrospinal fluid-derived amyloid positivity and tau positivity (Aß42/40 ratio ≤ 0.08; pTau181 ≥ 73.65 pg/mL) and linear regression to examine the relationship between cognitive performance (i.e., Mini-Mental State Examination and global cognitive and domain-specific performance) and the IFSHs. We controlled the models for age, sex, years of education, and history of hypertension. The IFSH scores were higher in those participants with amyloid positivity (OR: 1.95, 95% CI: 1.05-3.59) but not tau positivity (OR: 1.12, 95% CI: 0.57-2.18). The IFSH scores were higher in older participants (OR: 1.05, 95% CI: 1.00-1.10) and lower in males compared to females (OR: 0.44, 95% CI: 0.26-0.76). We did not find sufficient evidence linking the IFSH scores with cognitive performance after correcting for demographics and AD biomarker positivity. IFSHs may reflect the aberrant accumulation of amyloid ß beyond age.

Understanding Stimulation of Conjugal Gene Transfer by Nonantibiotic Compounds: How Far Are We?

A myriad of nonantibiotic compounds is released into the environment, some of which may contribute to the dissemination of antimicrobial resistance by stimulating conjugation. Here, we analyzed a collection of studies to (i) identify patterns of transfer stimulation across groups and concentrations of chemicals, (ii) evaluate the strength of evidence for the proposed mechanisms behind conjugal stimulation, and (iii) examine the plausibility of alternative mechanisms. We show that stimulatory nonantibiotic compounds act at concentrations from 1/1000 to 1/10 of the minimal inhibitory concentration for the donor strain but that stimulation is always modest (less than 8-fold). The main proposed mechanisms for stimulation via the reactive oxygen species/SOS cascade and/or an increase in cell membrane permeability are not unequivocally supported by the literature. However, we identify the reactive oxygen species/SOS cascade as the most likely mechanism. This remains to be confirmed by firm molecular evidence. Such evidence and more standardized and high-throughput conjugation assays are needed to create technologies and solutions to limit the stimulation of conjugal gene transfer and contribute to mitigating global antibiotic resistance.

Resistive switching memories with enhanced durability enabled by mixed-dimensional perfluoroarene perovskite heterostructures.

Hybrid halide perovskites are attractive candidates for resistive switching memories in neuromorphic computing applications due to their mixed ionic-electronic conductivity. Moreover, their exceptional optoelectronic characteristics make them effective as semiconductors in photovoltaics, opening perspectives for self-powered memory elements. These devices, however, remain unexploited, which is related to the variability in their switching characteristics, weak endurance, and retention, which limit their performance and practical use. To address this challenge, we applied low-dimensional perovskite capping layers onto 3D mixed halide perovskites using two perfluoroarene organic cations, namely (perfluorobenzyl)ammonium and (perfluoro-1,4-phenylene)dimethylammonium iodide, forming Ruddlesden-Popper and Dion-Jacobson 2D perovskite phases, respectively. The corresponding mixed-dimensional perovskite heterostructures were used to fabricate resistive switching memories based on perovskite solar cell architectures, showing that the devices based on perfluoroarene heterostructures exhibited enhanced performance and stability in inert and ambient air atmosphere. This opens perspectives for multidimensional perovskite materials in durable self-powered memory elements in the future.

Neural network analysis of neutron and X-ray reflectivity data incorporating prior knowledge.

Due to the ambiguity related to the lack of phase information, determining the physical parameters of multilayer thin films from measured neutron and X-ray reflectivity curves is, on a fundamental level, an underdetermined inverse problem. This ambiguity poses limitations on standard neural networks, constraining the range and number of considered parameters in previous machine learning solutions. To overcome this challenge, a novel training procedure has been designed which incorporates dynamic prior boundaries for each physical parameter as additional inputs to the neural network. In this manner, the neural network can be trained simultaneously on all well-posed subintervals of a larger parameter space in which the inverse problem is underdetermined. During inference, users can flexibly input their own prior knowledge about the physical system to constrain the neural network prediction to distinct target subintervals in the parameter space. The effectiveness of the method is demonstrated in various scenarios, including multilayer structures with a box model parameterization and a physics-inspired special parameterization of the scattering length density profile for a multilayer structure. In contrast to previous methods, this approach scales favourably when increasing the complexity of the inverse problem, working properly even for a five-layer multilayer model and a periodic multilayer model with up to 17 open parameters.

Halide Segregated Crystallization of Mixed-Halide Perovskites Revealed by In Situ GIWAXS.

Mixed-halide perovskites of the composition MAPb(BrxI1-x)3, which seem to exhibit a random and uniform distribution of halide ions in the absence of light, segregate into bromide- and iodide-rich phases under illumination. This phenomenon of halide segregation has been widely investigated in the photovoltaics context since it is detrimental for the material properties and ultimately the device performance of these otherwise very attractive materials. A full understanding of the mechanisms and driving forces has remained elusive. In this work, a study of the crystallization pathways and the mixing behavior during deposition of MAPb(BrxI1-x)3 thin films with varying halide ratios is presented. In situ grazing incidence wide-angle scattering (GIWAXS) reveals the distinct crystallization behavior of mixed-halide perovskite compositions during two different fabrication routes: nitrogen gas-quenching and the lead acetate route. The perovskite phase formation of mixed-halide thin films hints toward a segregation tendency since separate crystallization pathways are observed for iodide- and bromide-rich phases within the mixed compositions. Crystallization of the bromide perovskite phase (MAPbBr3) is already observed during spin coating, while the iodide-based fraction of the composition forms solvent complexes as an intermediate phase, only converting into the perovskite phase upon thermal annealing. These parallel crystallization pathways result in mixed-halide perovskites forming from initially halide-segregated phases only under the influence of heating.

Optical Absorption Properties in Pentacene/Tetracene Solid Solutions.

Modifying the optical and electronic properties of crystalline organic thin films is of great interest for improving the performance of modern organic semiconductor devices. Therein, the statistical mixing of molecules to form a solid solution provides an opportunity to fine-tune optical and electronic properties. Unfortunately, the diversity of intermolecular interactions renders mixed organic crystals highly complex, and a holistic picture is still lacking. Here, we report a study of the optical absorption properties in solid solutions of pentacene and tetracene, two prototypical organic semiconductors. In the mixtures, the optical properties can be continuously modified by statistical mixing at the molecular level. Comparison with time-dependent density functional theory calculations on occupationally disordered clusters unravels the electronic origin of the low energy optical transitions. The disorder partially relaxes the selection rules, leading to additional optical transitions that manifest as optical broadening. Furthermore, the contribution of diabatic charge-transfer states is modified in the mixtures, reducing the observed splitting in the 0-0 vibronic transition. Additional comparisons with other blended systems generalize our results and indicate that changes in the polarizability of the molecular environment in organic thin-film blends induce shifts in the absorption spectrum.

Minimizing Interfacial Recombination in 1.8 eV Triple-Halide Perovskites for 27.5% Efficient All-Perovskite Tandems.

All-perovskite tandem solar cells show great potential to enable the highest performance at reasonable costs for a viable market entry in the near future. In particular, wide-bandgap (WBG) perovskites with higher open-circuit voltage (VOC ) are essential to further improve the tandem solar cells' performance. Here, a new 1.8 eV bandgap triple-halide perovskite composition in conjunction with a piperazinium iodide (PI) surface treatment is developed. With structural analysis, it is found that the PI modifies the surface through a reduction of excess lead iodide in the perovskite and additionally penetrates the bulk. Constant light-induced magneto-transport measurements are applied to separately resolve charge carrier properties of electrons and holes. These measurements reveal a reduced deep trap state density, and improved steady-state carrier lifetime (factor 2.6) and diffusion lengths (factor 1.6). As a result, WBG PSCs achieve 1.36 V VOC , reaching 90% of the radiative limit. Combined with a 1.26 eV narrow bandgap (NBG) perovskite with a rubidium iodide additive, this enables a tandem cell with a certified scan efficiency of 27.5%.

Effective interactions and phase behavior of protein solutions in the presence of hexamine cobalt(III) chloride.

It is well established that deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) exhibit a reentrant condensation (RC) phase behavior in the presence of the trivalent hexamine cobalt(III) cations (Hac) which can be important for their packing and folding. A similar behavior can be observed for negatively charged globular proteins in the presence of trivalent metal cations, such as Y3+ or La3+. This phase behavior is mainly driven by charge inversion upon an increasing salt concentration for a fixed protein concentration (cp). However, as Hac exhibits structural differences compared to other multivalent metal cations, with six ammonia ligands (NH3) covalently bonded to the central cobalt atom, it is not clear that Hac can induce a similar phase behavior for proteins. In this work, we systematically investigate whether negatively charged globular proteins ß-lactoglobulin (BLG), bovine serum albumin (BSA), human serum albumin (HSA) and ovalbumin (OVA) feature Hac-induced RC. Effective protein-protein interactions were investigated by small-angle X-ray scattering. The reduced second virial coefficient (B2/B2HS) was obtained as a function of salt concentration. The virial coefficient analysis performed confirms the reentrant interaction (RI) behavior for BLG without actually inducing RC, given the insufficient strengths of the interactions for the latter to occur. In contrast, the strength of attraction for BSA, HSA and OVA are too weak to show RC. Model free analysis of the inverse intensity [Formula: see text] also supports this finding. Looking at different q-range by employing static (SLS) and dynamic light scattering experiments, the presence of RI behavior can be confirmed. The results are further discussed in view of metal cation binding sites in nucleic acids (DNA and RNA), where Hac induced RC phase behavior.

Cluster-Based Approach Utilizing Optimally Tuned TD-DFT to Calculate Absorption Spectra of Organic Semiconductor Thin Films.

The photophysics of organic semiconductor (OSC) thin films or crystals has garnered significant attention in recent years since a comprehensive theoretical understanding of the various processes occurring upon photoexcitation is crucial for assessing the efficiency of OSC materials. To date, research in this area has relied on methods using Frenkel-Holstein Hamiltonians, calculations of the GW-Bethe-Salpeter equation with periodic boundaries, or cluster-based approaches using quantum chemical methods, with each of the three approaches having distinct advantages and disadvantages. In this work, we introduce an optimally tuned, range-separated time-dependent density functional theory approach to accurately reproduce the total and polarization-resolved absorption spectra of pentacene, tetracene, and perylene thin films, all representative OSC materials. Our approach achieves excellent agreement with experimental data (mostly ≤0.1 eV) when combined with the utilization of clusters comprising multiple monomers and a standard polarizable continuum model to simulate the thin-film environment. Our protocol therefore addresses a major drawback of cluster-based approaches and makes them attractive tools for OSC investigations. Its key advantages include its independence from external, system-specific fitting parameters and its straightforward application with well-known quantum chemical program codes. It demonstrates how chemical intuition can help to reduce computational cost and still arrive at chemically meaningful and almost quantitative results.

The Onset of Molecule-Spanning Dynamics in Heat Shock Protein Hsp90.

Protein dynamics have been investigated on a wide range of time scales. Nano- and picosecond dynamics have been assigned to local fluctuations, while slower dynamics have been attributed to larger conformational changes. However, it is largely unknown how fast (local) fluctuations can lead to slow global (allosteric) changes. Here, fast molecule-spanning dynamics on the 100 to 200 ns time scale in the heat shock protein 90 (Hsp90) are shown. Global real-space movements are assigned to dynamic modes on this time scale, which is possible by a combination of single-molecule fluorescence, quasi-elastic neutron scattering and all-atom molecular dynamics (MD) simulations. The time scale of these dynamic modes depends on the conformational state of the Hsp90 dimer. In addition, the dynamic modes are affected to various degrees by Sba1, a co-chaperone of Hsp90, depending on the location within Hsp90, which is in very good agreement with MD simulations. Altogether, this data is best described by fast molecule-spanning dynamics, which precede larger conformational changes in Hsp90 and might be the molecular basis for allostery. This integrative approach provides comprehensive insights into molecule-spanning dynamics on the nanosecond time scale for a multi-domain protein.

Blend Sign and Haemorrhage Location and Volume Predict Late Recurrence and Mortality in Intracerebral Haemorrhage Patients.

BACKGROUND: Studies on risk factors for primary intracerebral haemorrhage (ICH) focus on short-term predictive values of distinct clinical parameters or computed tomography (CT) markers and disregard the others. We, therefore, studied independent predictive values of demographic, clinical, and CT markers regarding ICH expansion, late ICH recurrence, and late mortality. METHODS: In a retrospective study of 288 patients with primary ICH, ICH localization (158 lobar, 81 deep, and 49 cerebellar), volume, blend sign, spot sign, finger-like projections, and subarachnoid haemorrhages were evaluated. ICH localization-specific differences for demographic (age, sex), clinical parameters (vascular risk factors, antiplatelet, and anticoagulation therapy), and CT markers were evaluated using logistic regression. We applied Cox proportional hazards modelling using these parameters to predict risk factors for ICH expansion, late ICH recurrence, and late mortality. RESULTS: The blend sign in lobar ICH relates to increased risk of ICH expansion (HR2.3), late ICH recurrence (HR2.3), and mortality (HR1.6). Age, conditions requiring antiplatelet medication, deep ICH localization, volume, and blend sign represented the most important independent factors impacting overall mortality. CONCLUSIONS: Blend sign at baseline ICH is a manifestation of underlying detrimental vascular processes that signal increased ICH expansion risk, although is also indicative of long-term risks for late recurrent ICH and late mortality.

Closing the loop: autonomous experiments enabled by machine-learning-based online data analysis in synchrotron beamline environments.

Recently, there has been significant interest in applying machine-learning (ML) techniques to the automated analysis of X-ray scattering experiments, due to the increasing speed and size at which datasets are generated. ML-based analysis presents an important opportunity to establish a closed-loop feedback system, enabling monitoring and real-time decision-making based on online data analysis. In this study, the incorporation of a combined one-dimensional convolutional neural network (CNN) and multilayer perceptron that is trained to extract physical thin-film parameters (thickness, density, roughness) and capable of taking into account prior knowledge is described. ML-based online analysis results are processed in a closed-loop workflow for X-ray reflectometry (XRR), using the growth of organic thin films as an example. Our focus lies on the beamline integration of ML-based online data analysis and closed-loop feedback. Our data demonstrate the accuracy and robustness of ML methods for analyzing XRR curves and Bragg reflections and its autonomous control over a vacuum deposition setup.