Time-resolved Data Research Articles

Deep learning-based temporal deconvolution for photon time-of-flight distribution retrieval

The acquisition of the time of flight (ToF) of photons has found numerous applications in the biomedical field. Over the last decades, a few strategies have been proposed to deconvolve the temporal instrument response function (IRF) that distorts the experimental time-resolved data. However, these methods require burdensome computational strategies and regularization terms to mitigate noise contributions. Herein, we propose a deep learning model specifically to perform the deconvolution task in fluorescence lifetime imaging (FLI). The model is trained and validated with representative simulated FLI data with the goal of retrieving the true photon ToF distribution. Its performance and robustness are validated with well-controlled in vitro experiments using three time-resolved imaging modalities with markedly different temporal IRFs. The model aptitude is further established with in vivo preclinical investigation. Overall, these in vitro and in vivo validations demonstrate the flexibility and accuracy of deep learning model-based deconvolution in time-resolved FLI and diffuse optical imaging.

Scaling and merging time-resolved pink-beam diffraction with variational inference

Time-resolved x-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data.

RTF: an R package for modelling time course data.

The retarded transient function (RTF) approach serves as a complementary method to ordinary differential equations (ODEs) for modelling dynamics typically observed in cellular signalling processes. We introduce an R package that implements the RTF approach, originally implemented within the MATLAB-based Data2Dynamics modelling framework. This package facilitates the modelling of time and dose dependencies, and it includes the possibility of model reduction to minimize overfitting. It can be applied to experimental data or trajectories of ODE models to characterize their dynamics. Additionally, it can generate a low-dimensional representation based on the fitted RTF parameters of a set of time-resolved data, aiding in the identification of key targets of experimental perturbations. The R package RTF is available at https://github.com/kreutz-lab/RTF.

Combustion synthesis of the (Ti,Zr)B2-(Zr,Ti)C eutectic composites: Structure formation and properties

The macrokinetic characteristics of combustion of the quaternary Ti-Zr-B-C mixture as well as the mechanism and stages of phase formation for the synthesis products were investigated. The mechanical and thermophysical properties of the hot-pressed boride/carbide ceramics with eutectic composition (Ti,Zr)B2-43%at.(Zr,Ti)C were measured. Preliminary mechanical alloying (MA) of the (Zr + Ti) mixture was shown to yield Ti/Zr granules having a laminar structure and consisting of alternating layers of titanium, zirconium, and (Zr,Ti)ss solid solution. The method used to prepare reaction mixtures and the initial temperature T0 increased within the range of 20–370 °C have virtually no effect on combustion temperature, which is 2260–2400 °C, while higher T0 increases the combustion rate by a factor of 1.5–2. The use of MA Ti/Zr granules reduces the combustion rate as well as the specific heat release amount and the heat release rate. Time-resolved X-ray diffraction data showed that binary carbides (Zr1-xTix)C and diborides (Ti1-yZry)B2 of variable stoichiometry are formed in the combustion wave of the Ti-Zr-B-C reaction mixtures within less than 0.25 s. The carbide and diboride phases are formed simultaneously; the use of MA Ti/Zr granules in the reaction mixtures reduces the content of solid solutions of variable stoichiometry among the reaction products. The ceramics fabricated using a combination of combustion synthesis and hot pressing have a dense and homogeneous structure that consist of bonded grains of the diboride (Ti0.80Zr0.20)B2 and carbide (Zr0.83Ti0.17)C phases having the following properties: density, 5.3 g/cm3; hardness, 22.9 GPa; fracture toughness, 4.7 MPa m0.5; heat capacity, 0.52 J/(g·K); thermal diffusivity, 11.67 mm2/s; and thermal conductivity, 33.28 W/(m·K).

UniChromCD for Demultiplexing Time-Resolved Charge Detection-Mass Spectrometry Data.

Charge detection mass spectrometry (CD-MS) enables characterization of large, heterogeneous analytes through the analysis of individual ion signals. Because hundreds to thousands of scans must be acquired to produce adequate ion statistics, CD-MS generally requires long analysis times. The slow acquisition speed of CD-MS complicates efforts to couple it with time-dispersive techniques, such as chromatography and ion mobility, because it is not always possible to acquire enough scans from a single sample injection to generate sufficient ion statistics. Multiplexing methods based on Hadamard and Fourier transforms offer an attractive solution to this problem by improving the duty cycle of the separation while preserving retention/drift time information. However, integrating multiplexing with CD-MS data processing is complex. Here, we present UniChromCD, a new module in the open-source UniDec package that incorporates CD-MS time-domain data processing with demultiplexing tools. Following a detailed description of the algorithm, we demonstrate its capabilities using two multiplexed CD-MS workflows: Hadamard-transform size-exclusion chromatography and Fourier-transform ion mobility. Overall, UniChromCD provides a user-friendly interface for analysis and visualization of time-resolved CD-MS data.

Numerical approach for the simulation of flow-induced noise around a structure with complex geometry: High-speed train bogie in a cavity

The bogie region is a significant source of aerodynamic noise on high-speed trains. Owing to its complex geometry and flow field, numerical simulations using computational fluid dynamics are especially challenging. The main challenge is to achieve a grid with adequate resolution, especially in the boundary layer, while ensuring computational affordability. This challenge is addressed here by employing a hybrid grid, integrating a structured hexahedral mesh near solid surfaces with an unstructured polyhedral mesh in the remaining volume. To limit the number of cells in the boundary layer region, the delayed detached eddy simulation method is adopted. Additionally, to achieve a further reduction in the cell count, the Reynolds number of the model is decreased by scaling down the model size and lowering the inflow speed. The hybrid grid generation and numerical settings are guided by validated simulations of flow over cylinders. A grid sensitivity study, conducted with a simplified half-width bogie model, reveals the meshing requirements for the full-width model. Aerodynamic results highlight the rear section of the cavity and bogie as primary noise sources, emphasizing the critical role of the detached shear layer from upstream components. Time-resolved surface pressure data are input into the Ffowcs Williams–Hawkings equation for far-field noise calculation. The results indicate that the sound energy is concentrated below 200 Hz in the full-scale model, with the cavity contributing more than the bogie. This study provides a practical numerical approach for simulating a structure with complex geometry, offering insights for realistic model simulations.

Investigation on the differences in unsteady film cooling behaviors of gas turbine blades between mainstream and cooling air pulsations for a cylindrical hole

In practice, film cooling on gas turbine blade inevitably works in an unsteady environment, which is introduced by periodical rotor/stator interaction and unsteady combustion. Previous studies have introduced two methods to simulate the realistic unsteady condition: 1) the pulsation of mainstream velocity; and 2) the pulsation of coolant injection. However, up to this point, the differences in instantaneous film cooling behaviors between these two methods remain unclear. This work presents a series of large eddy simulations to exhibit the unsteady flow and film cooling behaviors under steady and the two unsteady flow conditions. The numerical strategy is validated against our time-resolved experimental data. Time-averaged results show that the difference between the two pulsations is not significant if the averaged blowing ratio remains the same. However, the pulsation type plays a dominant role on the transient mode of film coverage. Under the steady condition, film coverage instability is induced by the unsteady trajectory of near-wall vortex structure; but with pulsed environments, the unsteadiness magnitude increases, and the area with high unsteadiness level enlarges. The pulsation of the mainstream velocity induces a more severe film coverage instability compared to the pulsation of the cooling air injection, because of the higher fluctuation energy of the mainstream bulk. Under mainstream pulsation, the probability distribution of instantaneous cooling effectiveness is the most scattered, and the corresponding fluctuation range is the largest.

In situ X-ray diffraction and thermal simulation of material extrusion additive manufacturing of polymer

Material extrusion additive manufacturing (AM) has gradually become a dominant technology for the fabrication of complex-designed thermoplastic polymers that require a higher level of control over the morphological and mechanical properties. The polymer internal crystal structure formed during the AM process can present significant impacts on the mechanical properties of the individual filaments, as well as the whole structure. Currently, limited details are known about the crystal structure evolution during the material extrusion AM processes of polymers. A novel in situ synchrotron X-ray diffraction (XRD) experimental configuration was developed enabling us to capture the material evolution data throughout the extrusion AM process. The in situ time-resolved data was analysed to reveal nucleation and crystallization sequences during the continuous deposition, with the aid of both complimentary numerical simulations and post-process (ex situ) characterisations. The thermal simulations supported the prediction of the filament temperature profile over time and location during the AM process, while ex situ characterisations validated the correlation between polymer crystallinity (resulting from printing parameters) and corresponding mechanical properties. The results obtained from varied process parameters suggest that the processing temperature has a dominant influence on the crystal microstructure evolution compared to the deposition velocity. A lower processing temperature just above the melting temperature permitted favourable crystallization conditions. The overall analysis demonstrated prospects for enhancing polymer AM, to engineering mechanically hierarchical structures through correlative investigations.

Understanding X-ray-induced isomerisation in photoswitchable surfactant assemblies.

Dynamic, responsive materials can be built using photosurfactants (PS) that self-assemble into ordered nanostructures, such as micelles or liquid crystals. These PS contain photoswitchable groups, such as azobenzene (Azo) or, more recently, arylazopyrazoles (AAPs), which change shape and polarity on photoisomerisation between the E and Z states, thus changing the self-assembled structure. Small-angle X-ray scattering (SAXS) is a powerful technique to probe the morphology of PS and can be used to measure the mechanisms of structural changes using in-situ light irradiation with rapid, time-resolved data collection. However, X-ray irradiation has been shown previously to induce Z-to-E isomerisation of Azo-PS, which can lead to inaccuracies in the measured photostationary state. Here, we investigate the effect of light and X-ray irradiation on micelles formed from two different PS, containing either an Azo or AAP photoswitch using SAXS with in-situ light irradiation. The effect of X-ray irradiation on the Z isomer is shown to depend on the photoswitch, solvent, concentration and morphology. We use this to create guidelines for future X-ray experiments using photoswitchable molecules, which can aid more accurate understanding of these materials for application in solar energy storage, catalysis or controlled drug delivery.

Turning the attention to time-resolved EPID-images: treatment error classification with transformer multiple instance learning

Objective. The aim of this work was to develop a novel artificial intelligence-assisted in vivo dosimetry method using time-resolved (TR) dose verification data to improve quality of external beam radiotherapy. Approach. Although threshold classification methods are commonly used in error classification, they may lead to missing errors due to the loss of information resulting from the compression of multi-dimensional electronic portal imaging device (EPID) data into one or a few numbers. Recent research has investigated the classification of errors on time-integrated (TI) in vivo EPID images, with convolutional neural networks showing promise. However, it has been observed previously that TI approaches may cancel out the error presence on γ-maps during dynamic treatments. To address this limitation, simulated TR γ-maps for each volumetric modulated arc radiotherapy angle were used to detect treatment errors caused by complex patient geometries and beam arrangements. Typically, such images can be interpreted as a set of segments where only set class labels are provided. Inspired by recent weakly supervised approaches on histopathology images, we implemented a transformer based multiple instance learning approach and utilized transfer learning from TI to TR γ-maps. Main results. The proposed algorithm performed well on classification of error type and error magnitude. The accuracy in the test set was up to 0.94 and 0.81 for 11 (error type) and 22 (error magnitude) classes of treatment errors, respectively. Significance. TR dose distributions can enhance treatment delivery decision-making, however manual data analysis is nearly impossible due to the complexity and quantity of this data. Our proposed model efficiently handles data complexity, substantially improving treatment error classification compared to models that leverage TI data.

Modeling Stochastic Kinetics of Cathodic Cu Surface Corrosion and Ionic Interaction in Nanoscopic Water Pools

Cathodic Cu corrosion has been reported to occur in both the presence and absence of carbon dioxide in aqueous electrolytes and while the mechanism is not understood well it implies carbide-, hydride- and hydroxide-formation mediated pathways. Corrosion leads to roughening, which creates local pockets of electrolyte that are somewhat disconnected from the bulk. In this talk, we describe a combination of theoretical studies to identify reaction pathways, and kinetics modeling of them to obtain a working description of corrosion in water. Corrosion at metal surfaces is both influenced by and influences the formation of nanoscopic aqueous pools by trapping electrolyte solution in microscopic pockets. Such electrolyte nano-pools exhibit non-bulk behavior, and the lifetime of locally trapped ions can be significantly different than in the bulk. This can potentially have an effect on the chemistry in the local microenvironment. Stochastic reaction-diffusion models can be used to model kinetics of electrochemical processes at length and time scales relevant to laboratory experiments, allowing a direct comparison of transient observable quantities to time-resolved experimental data. Atomistic simulations employ methods of electronic structure theory (such as density functional theory (DFT)) and molecular dynamics (both classical and ab initio) to describe a detailed picture of the (electro-)chemistry at microscopic time and length scales. Scaling up these methods to macroscopic levels is not trivial but required for direct comparison to experiment. By using Gibbs free energies obtained from atomistic simulations it is possible to calculate rate constants for individual elementary steps in reaction schemes describing kinetics of relevant processes. We use Kinetiscope to implement stochastic kinetics models of two reaction schemes describing: 1. cathodic Cu surface corrosion through formation of copper hydroxides, through which we aim to describe essential steps in the cathodic corrosion mechanism of metal surfaces; 2. interactions between bicarbonate and hydronium ions, both present in the bicarbonate salt buffers used routinely in electrochemical reduction at copper surfaces, in a nanoscopic water droplet to understand time-dependent changes in the local concentrations of electrolytes trapped at or near metal surfaces. Figure 1

Integrative spatiotemporal modeling of biomolecular processes: application to the assembly of the Nuclear Pore Complex.

Dynamic processes involving biomolecules are essential for the function of the cell. Here, we introduce an integrative method for computing models of these processes based on multiple heterogeneous sources of information, including time-resolved experimental data and physical models of dynamic processes. We first compute integrative structure models at fixed time points and then optimally select and connect these snapshots into a series of trajectories that optimize the likelihood of both the snapshots and transitions between them. The method is demonstrated by application to the assembly process of the human Nuclear Pore Complex in the context of the reforming nuclear envelope during mitotic cell division, based on live-cell correlated electron tomography, bulk fluorescence correlation spectroscopy-calibrated quantitative live imaging, and a structural model of the fully-assembled Nuclear Pore Complex. Modeling of the assembly process improves the model precision over static integrative structure modeling alone. The method is applicable to a wide range of time-dependent systems in cell biology, and is available to the broader scientific community through an implementation in the open source Integrative Modeling Platform software.

Jet collimation and acceleration in the flat spectrum radio quasar 1928+738

Using time-resolved multifrequency Very Long Baseline Array data and new KaVA (KVN and VERA Array) observations, we study the structure and kinematics of the jet of the flat spectrum radio quasar (FSRQ) 1928+738. We find two distinct jet geometries as a function of distance from the central black hole, with the inner jet having a parabolic shape, indicating collimation, and the outer jet having a conical shape, indicating free expansion of the jet plasma. Jet component speeds display a gradual outward acceleration up to a bulk Lorentz factor Γmax ≈ 10 followed by a deceleration further downstream. The location of the acceleration zone matches the region where the jet collimation occurs. Therefore, this is the first direct observation of an acceleration and collimation zone (ACZ) in an FSRQ. The ACZ terminates approximately at a distance of 5.6 × 106 gravitational radii, which is in good agreement with the sphere of gravitational influence of the supermassive black hole, implying that the physical extent of the ACZ is controlled by the black hole gravity. Our results suggest that confinement by an external medium is responsible for the jet collimation and that the jet is accelerated by converting Poynting flux energy to kinetic energy.

Scaling and Merging Time-Resolved Laue Data with Variational Inference.

Time-resolved X-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data.

Revealing static and dynamic biomarkers from postprandial metabolomics data through coupled matrix and tensor factorizations.

Longitudinal metabolomics data from a meal challenge test contains both fasting and dynamic signals, that may be related to metabolic health and diseases. Recent work has explored the multiway structure of time-resolved metabolomics data by arranging it as a three-way array with modes: subjects, metabolites, and time. The analysis of such dynamic data (where the fasting data is subtracted from postprandial states) reveals dynamic markers of various phenotypes, and differences between fasting and dynamic states. However, there is still limited success in terms of extracting static and dynamic biomarkers for the same subject stratifications. Through joint analysis of fasting and dynamic metabolomics data, our goal is to capture static and dynamic biomarkers of a phenotype for the same subject stratifications providing a complete picture, that will be more effective for precision health. We jointly analyze fasting and dynamic metabolomics data collected during a meal challenge test from the COPSAC cohort using coupled matrix and tensor factorizations (CMTF), where the dynamic data (subjects by metabolites by time) is coupled with the fasting data (subjects by metabolites) in the subjects mode. The proposed data fusion approach extracts shared subject stratifications in terms of BMI (body mass index) from fasting and dynamic signals as well as the static and dynamic metabolic biomarker patterns corresponding to those stratifications. Specifically, we observe a subject stratification showing the positive association with all fasting VLDLs and higher BMI. For the same subject stratification, a subset of dynamic VLDLs (mainly the smaller sizes) correlates negatively with higher BMI. Higher correlations of the subject quantifications with the phenotype of interest are observed using such a data fusion approach compared to individual analyses of the fasting and postprandial state. The CMTF-based approach provides a complete picture of static and dynamic biomarkers for the same subject stratifications-when markers are present in both fasting and dynamic states.

Resolving DJ-1 Glyoxalase Catalysis Using Mix-and-Inject Serial Crystallography at a Synchrotron.

DJ-1 (PARK7) is an intensively studied protein whose cytoprotective activities are dysregulated in multiple diseases. DJ-1 has been reported as having two distinct enzymatic activities in defense against reactive carbonyl species that are difficult to distinguish in conventional biochemical experiments. Here, we establish the mechanism of DJ-1 using a synchrotron-compatible version of mix-and-inject-serial crystallography (MISC), which was previously performed only at XFELs, to directly observe DJ-1 catalysis. We designed and used new diffusive mixers to collect time-resolved Laue diffraction data of DJ-1 catalysis at a pink beam synchrotron beamline. Analysis of structurally similar methylglyoxal-derived intermediates formed through the DJ-1 catalytic cycle shows that the enzyme catalyzes nearly two turnovers in the crystal and defines key aspects of its glyoxalase mechanism. In addition, DJ-1 shows allosteric communication between a distal site at the dimer interface and the active site that changes during catalysis. Our results rule out the widely cited deglycase mechanism for DJ-1 action and provide an explanation for how DJ-1 produces L-lactate with high chiral purity.

Direct mechanistic connection between acoustic signals and melt pool morphology during laser powder bed fusion

Various nondestructive diagnostic techniques have been proposed for in situ process monitoring of laser powder bed fusion (LPBF), including melt pool pyrometry, whole-layer optical imaging, acoustic emission, atomic emission spectroscopy, high speed melt pool imaging, and thermionic emission. Correlations between these in situ monitoring signals and defect formation have been demonstrated with acoustic signals having been shown to predict pore formation with especially high confidence in recent machine learning studies. In this work, time-resolved acoustic data are collected in both the conduction and keyhole welding regimes of LPBF-processed Ti-6Al-4V alloy. A non-dimensionalized Strouhal number analysis, used in whistle aeroacoustics, is applied to demonstrate that the acoustic signals recorded in the keyhole regimes can be directly associated with the vapor depression morphology. This mechanistic understanding developed from whistle aeroacoustics shows that acoustic monitoring during the LPBF process can provide a direct probe into the vapor depression dynamics and defect occurrence, especially in the keyhole regimes relevant to printing and defect formation.

Improved Impingement Cooling Using Flow Enhancing Structural Elements

This investigation is part of a study seeking to improve impingement cooling in internal combustion turbomachinery using flow modifying elements within the cooling channel. A simplified geometry of a jet impingement cooling configuration is chosen for well-defined numerical simulations and complementary experiments. The generic cooling channel setup features of a square cross-section that is closed on one end and is supplied by 9 inline jets that are directed toward a heated plate. Using RANS, the presence of an arc-conic placed immediately downstream of each jet nozzle was found to increase the heat transfer and prompted the present experimental study to elucidate the fluid mechanical mechanisms leading to the improved performance. Central to the study is an extensive data base of time-resolved 2d-2c PIV data for both channel configurations, with and without installed arc-conics, on a field of view that simultaneously captures up to 3 jets. Using two-point correlations, an interaction or modal coupling between the jets is not observed, suggesting that each jet may be treated individually. The arc-conics tend to stabilize the jets by capturing and redirecting the bulk cross-flow, thereby increasing the self-similarity of the jet impingement pattern, in particular toward the channel exit. Modal analysis using both proper orthogonal decomposition (POD) and spectral proper orthogonal decomposition (SPOD) capture the dynamics of the flow, ideally to achieve a dimensionality reduction for reduced order modeling. However, the fully turbulent flow with highly stochastic dynamics exhibits only weak spatial or temporal signatures, with the energy content spread across a large number of modes. Among the dominant modes are pulsations of the jet onto the surface along with spanwise sweeping motions. The stabilization of the jet by the arc-conic results in a more defined impingement flow with the signature of the jet’s shear layer visible in the higher modes of the energy spectrum and is considered the main mechanism of improved heat transfer.

A comparative investigation of release kinetics of paclitaxel from natural protein and macromolecular nanocarriers in nanoscale drug delivery systems

Understanding the release behaviour of nanodrugs is a crucial step to better assess and control therapeutic outcomes and unfavourable side effects. Herein, we report a systematic study comparing the release kinetics and thermodynamics of paclitaxel (PTX) from supramolecularly assembled sub-micron particles based on natural macromolecules such as zein, whey, casein, bovine serum albumin (BSA) and conventional stabilizers such as pluronic F-127 (poloxamer 407), and β-cyclodextrin (β-CD) to gain insights into the role of carrier chemistry. For this purpose, nanomedicines with statistically indifferent sizes —in the range of 191.0 ± 0.8 nm (BSA) to 243.3 ± 11.6 nm (zein) were prepared (p > 0.05). The zeta potential values ranged from −3.2 ± 1.1 mV (pluronic F-127) to −17.2 ± 1.8 mV (whey) in phosphate buffered saline. The type of nanocarrier significantly influenced the long-term steady-state plateau of the release, resulting in a cumulative release of 70.3 ± 2.0 % of PTX from casein (the highest) and 46.8 ± 4.7 % of PTX from zein (the lowest). Time-resolved release data were analysed with various kinetical models, encompassing zero-order, first-order, Higuchi, Peppas-Sahlin, and Korsmeyer-Peppas kinetics. The analysis revealed that the Korsmeyer-Peppas model best captured the data. For these nanomedicines, the half-life of the encapsulated drugs was found to be 106.4 ± 31.3 h (zein), 4.7 ± 1.2 h (whey), 10.7 ± 1.8 h (pluronic F-127), 6.4 ± 0.9 h (casein), 10.8 ± 3.2 h (β-CD), and 4.0 ± 1.0 h (BSA). TEM characterization revealed differences in the macromolecular arrangement of the active ingredient within these nanocarriers, in addition to the structural differences among the various encapsulating agents. These differences manifested as variations in the internal nanostructures, leading to the creation of distinct microenvironments that could either facilitate or impede the movement of PTX molecules through the encapsulant matrices. In clinical settings, such fine details of nanocarrier design are important: by choosing the most appropriate nanocarrier (or their mixtures), clinicians can fine-tune drug administration to obtain the intended therapeutic window while mitigating the risk of potential negative reactions.

Structure and Reactivity of Active Oxygen Species on Silver Surfaces for Ethylene Epoxidation.

The epoxidation of ethylene stands as one of the most important industrial catalytic reactions, and silver-based catalysts show superior activity and selectivity. Oxygen is activated on the surface of silver during the reaction and exerts a substantial impact on product selectivity. Notably, the oxygen species residing in the topmost atomic layers profoundly influence the reactivity of a catalyst. However, their characterization under in situ reaction conditions remains a huge challenge, and specific structures have not been identified yet. In this study, we employ in situ X-ray photoelectron spectroscopy and density functional theory calculations to determine the oxygen species formed at the topmost atomic layers of a silver foil and to assign them a structure. Three different groups of oxygen species activated on silver are identified: (i) surface lattice oxygen and two oxygen species originating from associatively adsorbed dioxygen and (ii) top and (iii) subsurface oxygen. Transient in situ photoelectron spectroscopy experiments are carried out to reveal the dynamic evolution and thus reactivity of the different oxygen species under ethylene epoxidation reaction environments. The top oxygen atom from the adsorbed associated dioxygen is the most active. Meanwhile, a frequency-selective data analysis method, developed to process time-resolved data, provides insights into the evolving trends of peak intensities for different oxygen species. The versatility of this method suggests its potential application in future time-resolved characterization studies.