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The complex nature of liquid water saturation of polymer electrolyte fuel cell (PEFC) catalyst layers (CLs) greatly affects the device performance. To investigate this problem, we present a method to quantify the presence of liquid water in a PEFC CL using small-angle X-ray scattering (SAXS). This method leverages the differences in electron densities between the solid catalyst matrix and the liquid water filled pores of the CL under both dry and wet conditions. This approach is validated using ex situ wetting experiments, which aid the study of the transient saturation of a CL in a flow cell configuration in situ. The azimuthally integrated scattering data are fitted using 3D morphology models of the CL under dry conditions. Different wetting scenarios are realized in silico, and the corresponding SAXS data are numerically simulated by a direct 3D Fourier transformation. The simulated SAXS profiles of the different wetting scenarios are used to interpret the measured SAXS data which allows the derivation of the most probable wetting mechanism within a flow cell electrode.
Though the reinforcing properties of inorganic particles in thermosetting nanocomposites, has been exploited, the integration of nanoparticles continues to be challenging in terms of their homogeneous distribution and their manipulation which can contribute to occupational hazards. Due to a second encapsulations of nanoparticles, electrospun nanocomposite fibers containing nanoparticles might be an alternative for overcoming these issues, as the fiber nonwovens contains the nanoparticles allowing for safer manipulation. Here, the morphology, and the thermal properties of electrospun polycarbonate fibers containing taurine modified boehmite nanoparticles (BNP) are investigated by means of small and wide-angle X-ray scattering as well as fast scanning and temperature modulated fast scanning calorimetry for the first time. The latter techniques allow the investigation of the thermal properties of single fibers at heating rates up to 10^4 K s^-1 keeping its structure intact. A quantitative analysis of the scattering data reveals a porous structure of the fibers. The porous structure is quantified regarding the pore volume and the pore size. A constant amount of aggregation is found even for the highly BNP loaded fibers. Thermal analysis on the fibers reveals a rigid amorphous fraction (RAF) where it is known that RAF determinates the properties of a nanocomposite to a large extent. For the fibers RAF amounts up to 40 wt%, which is essential higher compared to equally formulated PC/BNP composite cast films. The RAF in the case of the fibers, is not only due to the presence of particles in the polymer but also due to orientation effects induced by the electrospinning process.
Impact of organic phosphates on the structure and composition of short-range ordered iron nanophases
(2024)
Organic phosphates (OP) are important nutrient components for living cells in natural environments, where they readily interact with ubiquitous iron phases such as hydrous ferric oxide, ferrihydrite (FHY). FHY partakes in many key bio(geo)chemical reactions including iron-mediated carbon storage in soils, or iron-storage in living organisms. However, it is still unknown how OP affects the formation, structure and properties of FHY. Here, we document how β-glycerophosphate (GP), a model OP ligand, affects the structure and properties of GP–FHY nanoparticles synthesized by coprecipitation at variable nominal molar P/Fe ratios (0.01 to 0.5). All GP–FHY precipitates were characterized by a maximum solid P/Fe ratio of 0.22, irrespective of the nominal P/Fe ratio. With increasing nominal P/Fe ratio, the specific surface area of the GP–FHY precipitates decreased sharply from 290 to 3 m2 g−1, accompanied by the collapse of their pore structure. The Fe–P local bonding environment gradually transitioned from a bidentate binuclear geometry at low P/Fe ratios to monodentate mononuclear geometry at high P/Fe ratios. This transition was accompanied by a decrease in coordination number of edge-sharing Fe polyhedra, and the loss of the corner-sharing Fe polyhedra. We show that Fe(III) polymerization is impeded by GP, and that the GP–FHY structure is highly dependent on the P/Fe ratio. We discuss the role that natural OP-bearing Fe(III) nanophases have in biogeochemical reactions between Fe–P and C species in aquatic systems.
Hierarchically porous, high‐surface‐area silica materials are excellent candidates for multiple applications like catalysis and environmental remediation. Shaping these materials with additive manufacturing (AM) techniques, like robocasting, could enable their use with the benefit of on‐demand, customized shaping and maximizing performance. Herein, ordered mesoporous silica COK‐12 slurries were robocasted into monoliths, containing different ratios of uncalcined COK‐12 and sodium bentonite (0–25 wt.%). The rheology of the mixed slurries is characterized by lower flow indexes (0.69 vs. 0.32) and higher yield stresses (96 vs. 259 Pa) compared to pure COK‐12 ones. Monoliths were printed in woodpile structures and calcined at 600°C. Micro‐CT measurements showed a linear shrinkage of 25% after calcination. Mechanical characterization showed increased uniaxial strength (0.20 ± 0.07 to 1.0 ± 0.3 MPa) with increasing binder/solids ratio from 13 to 25%. The amorphous, mesoporous structure of COK‐12 was retained. The structures exhibited open porosities of 52 ± 4% and showed higher specific mesopore volumes, and increased average mesopore size (6 vs. 8 nm) compared to COK‐12. Small‐angle x‐ray scattering analysis revealed an increased lattice parameter (10.3 vs. 11.0 nm) and reduced wall thickness (3.1 nm vs. 4.1 nm) of the COK‐12 in the monoliths. These properties indicate suitability for their application as porous supports and adsorbents.
Metal carbides have shown great promise in a wide range of applications due to their unique catalytic, electrocatalytic and magnetic properties. However, the scalable production of dispersible metal carbide nanoparticles remains a challenge. Here, we report a simple and scalable route to dispersible iron carbide (Fe3C) nanoparticles. This uses MgO nanoparticles as a removable ‘cast’ to synthesize Fe3C nanoparticles from Prussian blue (KFeIII[FeII(CN)6]). Electron tomography demonstrates how nanoparticles of the MgO cast encase the Fe3C nanoparticles to prevent sintering and agglomeration during the high-temperature synthesis. The MgO cast is readily removed with ethylenediaminetetraacetic acid (EDTA) to generate Fe3C nanoparticles that can be used to produce a colloidal ferrofluid or dispersed on a support material.
Mesoporous glasses are a promising class of bioresorbable biomaterials characterized by high surface area and extended porosity in the range of 2 to 50 nm. These peculiar properties make them ideal materials for the controlled release of therapeutic ions and molecules. Whilst mesoporous silicate-based glasses (MSG) have been widely investigated, much less work has been done on mesoporous phosphate-based glasses (MPG). In the present study, MPG in the P2O5–CaO–Na2O system, undoped and doped with 1, 3, and 5 mol% of Cu ions were synthesized via a combination of the sol–gel method and supramolecular templating. The non-ionic triblock copolymer Pluronic P123 was used as a templating agent. The porous structure was studied via a combination of Scanning Electron Microscopy (SEM), Small-Angle X-ray Scattering (SAXS), and N2 adsorption–desorption analysis at 77 K. The structure of the phosphate network was investigated via solid state 31P Magic Angle Spinning Nuclear Magnetic Resonance (31P MAS-NMR) and Fourier Transform Infrared (FTIR) spectroscopy. Degradation studies, performed in water via Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), showed that phosphates, Ca2+, Na+ and Cu ions are released in a controlled manner over a 7 days period. The controlled release of Cu, proportional to the copper loading, imbues antibacterial properties to MPG. A significant statistical reduction of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacterial viability was observed over a 3 days period. E. coli appeared to be more resistant than S. aureus to the antibacterial effect of copper. This study shows that copper doped MPG have great potential as bioresorbable materials for controlled delivery of antibacterial ions.
Showcasing research from the Federal Institute for Material Research and Testing Berlin and Fraunhofer Institute for Celltherapy and Immunology Branch Bioanalytics and Bioprocesses Potsdam.
Bio-SAXS of single-stranded DNA-binding proteins: Radiation protection by the compatible solute ectoine.
We aimed to increase the possible undisturbed exposure time during bio-SAXS measurements of single-stranded DNA-binding proteins. Therefore small angle X-ray scattering was performed on Gene-V Protein (G5P/GVP), which is involved in DNA repair processes. To achieve this, irradiations were performed in presence and absence of the hydroxyl-radical scavenger and osmolyte Ectoine, which showed efficient radiation protection and prevented protein aggregation, thus allows for a non-disturbing way to improve structure-determination of biomolecules.
Small-angle X-ray scattering (SAXS) can be used for structural determination of biological macromolecules and polymers in their native states (e.g. liquid phase). This means that the structural changes of (bio-)polymers, such as proteins and DNA, can be monitored in situ to understand their sensitivity to changes in chemical environments. In an attempt to improve the reliability of such experiments, the reduction of radiation damage occurring from exposure to X-rays is required. One such method, is to use scavenger molecules to protect macromolecules against radicals produced during radiation exposure, such as reactive oxygen species (ROS). In this study we investigate the feasibility of applying the compatible solute, osmolyte and radiation protector Ectoine (THP(B)), as a scavenger molecule during SAXS measurements of the single-stranded DNA-binding protein Gene-V Protein (G5P/GVP). In this case, we monitor the radiation induced changes of G5P during bio-SAXS measurments and the resulting microscopic energy-damage relation was determined from microdosimetric calculations by Monte-Carlo based particle scattering simulations with TOPAS/Geant4 and a custom target-model. This resulted in a median-lethal energy deposit of pure G5P at 4 mg mL−1 of E1/2 = 7 ± 5 eV, whereas a threefold increase of energy-deposit was needed under the presence of Ectoine to reach the same level of damage. This indicates that Ectoine increases the possible exposure time before radiation-damage to G5P is observed. Furthermore, the dominant type of damage shifted from aggregation in pure solutions towards a fragmentation for solutions containing Ectoine as a cosolute. These results are interpreted in terms of indirect radiation damage by reactive secondary species, as well as post-irradiation effects, related to preferential-exclusion of the cosolute from the protein surface. Hence, Ectoine is shown to provide a non-disturbing way to improve structure-determination of proteins via bio-SAXS in future studies.
Mechanically stable structures with interconnected hierarchical porosity combine the benefits of both small
and large pores, such as high surface area, pore volume, and good mass transport capabilities. Hence, lightweight micro-/meso-/macroporous monoliths are prepared from ordered mesoporous silica COK-12 by means of spark plasma sintering (SPS, S-sintering) and compared to conventionally (C-) sintered monoliths. A multi-scale model is developed to fit the small angle X-ray scattering data and obtain information on the hexagonal lattice parameters, pore sizes from the macro to the micro range, as well as the dimensions of the silica population. For both sintering techniques, the overall mesoporosity, hexagonal pore ordering, and amorphous character are preserved. The monoliths' porosity (77–49%), mesopore size (6.2–5.2 nm), pore volume (0.50–0.22 g cm-3
), and specific surface area (451–180 m2 g-1) decrease with increasing processing temperature and pressure. While the difference in porosity is enhanced, the
structural parameters between the C-and S-sintered monoliths are largely converging at 900 C, except for the mesopore size and lattice parameter, whose dimensions are more extensively preserved in the
S-sintered monoliths, however, coming along with larger deviations from the theoretical lattice. Their higher mechanical properties (biaxial strength up to 49 MPa, 724 MPa HV 9.807 N) at comparable porosities and ability to withstand ultrasonic treatment and dead-end filtration up to 7 bar allow S-sintered monoliths to reach a high permeance (2634 L m-2 h-1 bar-1), permeability (1.25 x 10^-14 m2), and ability to reduce the chemical oxygen demand by 90% during filtration of a surfactant-stabilized oil in water emulsion, while indicating reasonable resistance towards fouling.
he main objective of the nPSize project is to improve the measurement capabilities for nanoparticle size based on both measurement methods traceable to SI units and new reference materials. Two basic approaches have been used in order to develop measurement procedures resulting in traceable results of the nanoparticle size distribution: physical modelling for the methods used in the project (TSEM, SEM, AFM and SAXS) and machine learning.
Physical modelling: In this part, the physical models associated with different shape measurements for the techniques TSEM, SEM, AFM and SAXS have been collected and further developed with the aim to simulate the resulting signal as measured by the individual methods. Uncertainties and traceability associated with each model were investigated and evaluated. In the following, the progress on these physical models is reported for each individual method.
Machine Learning modelling: The aim of this part is to use machine learning to enable automatic measurement of nanoparticle shape from expert a-priori information only. No physical model will be used as a-priori information in this task.
The accuracy and traceability of the size results obtained by each technique will be analyzed and compared with the physical modelling. A machine learning database will then be used to create automatic detection algorithms.