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Herein, we report the design and synthesis of a layered redox-active, antiferromagnetic metal organic semiconductor crystals with the chemical formula [Cu(H2O)2V(µ-O)(PPA)2] (where PPA is phenylphosphonate). The crystal structure of [Cu(H2O)2V(µ-O)(PPA)2] shows that the metal phosphonate layers are separated by phenyl groups of the phenyl phosphonate linker. Tauc plotting of diffuse reflectance spectra indicates that [Cu(H2O)2V(µ-O)(PPA)2] has an indirect band gap of 2.19 eV. Photoluminescence (PL) spectra indicate a complex landscape of energy states with PL peaks at 1.8 and 2.2 eV. [Cu(H2O)2V(µ-O)(PPA)2] has estimated hybrid ionic and electronic conductivity values between 0.13 and 0.6 S m−1. Temperature-dependent magnetization measurements show that [Cu(H2O)2V(µ-O)(PPA)2] exhibits short range antiferromagnetic order between Cu(II) and V(IV) ions. [Cu(H2O)2V(µ-O)(PPA)2] is also photoluminescent with photoluminescence quantum yield of 0.02%. [Cu(H2O)2V(µ-O)(PPA)2] shows high electrochemical, and thermal stability.
We report on the colloidal stability of nanoparticles with alkanethiol shells in apolar solvents. Small angle X-ray scattering and molecular dynamics simulations were used to characterize the interaction between nanoparticles in linear alkane solvents ranging from hexane to hexadecane, including \SI{4}{\nano\meter} gold cores with hexadecanethiol shells and \SI{6}{\nano\meter} cadmium selenide cores with octadecanethiol shells. We find that the agglomeration is enthalpically driven and that, contrary to what one would expect from classical colloid theory, the temperature at which the particles agglomerate increases with increasing solvent chain length. We demonstrate that the inverted trend correlates with the temperatures at which the ligands order in the different solvents, and show that the inversion is due to a combination of enthalpic and entropic effects that enhance the stability of the ordered ligand state as the solvent length increases. We also explain why cyclohexane is a better solvent than hexane, despite having very similar solvation parameters to hexadecane.
We report the synthesis of AgNP@PEDOT:PSS hybrid conductive particles with silver cores and polythiophene shells that can be used to formulate sinter-free inks for printing electronics. First, Ag nanocrystals capped with the weakly bound ligand aminohexanoic acid (ε-Ahx) are prepared. The ligand shell is exchanged by reacting the dispersion with the polymer ionomer mixture poly(3,4-ethylene dioxythiophene):polystyrene sulfonate (PEDOT:PSS). The particles are characterized by electron microscopy, dynamic light scattering, Z potential, and Raman spectroscopy, confirming the replacement of the ligands on the metal particle surface. The resulting dispersion is colloidally stable as confirmed by DLS. Inks with a solid content of the hybrid particles of 300 mg mL−1 were prepared and deposited on different substrates. The new particles are components for hybrid inks that become electrically conductive without any chemical or thermal post-deposition treatment. We show that silver-based hybrid inks can be deposited on different substrates and possess an average conductivity after 24 h of drying at room temperature of 1.726 × 106 S m−1 ± 0.326 × 106 S m−1, only one order of magnitude lower than elemental silver and within the same order of magnitude as their gold ink counterpart.
Electrochemical desalination shows promise for ion-selective, energy-efficient water desalination. This work reviews performance metrics commonly used for electrochemical desalination. We provide a step-by-step guide on acquiring, processing, and calculating raw desalination data, emphasizing informative and reliable figures of merit. A typical experiment uses calibrated conductivity probes to relate measured conductivity to concentration. Using a standard electrochemical desalination cell with activated carbon electrodes, we demonstrate the calculation of desalination capacity, charge efficiency, energy consumption, and ion selectivity metrics. We address potential pitfalls in performance metric calculations, including leakage current (charge) considerations and aging of conductivity probes, which can lead to inaccurate results. The relationships between pH, temperature, and conductivity are explored, highlighting their influence on final concentrations. Finally, we provide a checklist for calculating performance metrics and planning electrochemical desalination tests to ensure accuracy and reliability. Additionally, we offer simplified spreadsheet tools to aid data processing, system design, estimations, and upscaling.
In this study, polyetheretherketone composites were compounded using a two-screw extruder followed by injection moulding. The effects of multi-fillers on the mechanical properties and crystallization performances were investigated. Differential scanning calorimetry results indicate that the addition of fillers slightly increases the crystallization temperature and crystallinity. Compared to neat polyetheretherketone, the incorporation of inorganic filler leads to a significant improvement in matrix hardness, matrix stiffness and a slight increase in tensile strength. However, the material ductility, the impact strength and the fracture toughness of polyetheretherketone composites decrease. Fractography analyses show that the addition of fillers restraints the ductile deformation of polymers, which is responsible for the reduction of material ductility, impact strength as well as fracture toughness of polyetheretherketone composites.
Interference of silica nanoparticles with the traditional Limulus amebocyte lysate gel clot assay
(2014)
Endotoxin contaminations of engineered nanomaterials can be responsible for observed biological responses, especially for misleading results in in vitro test systems, as well as in vivo studies. Therefore, endotoxin testing of nanomaterials is necessary to benchmark their influence on cells. Here, we tested the traditional Limulus amebocyte lysate gel clot assay for the detection of endotoxins in nanoparticle suspensions with a focus on possible interference of the particles with the test system. We systematically investigated the effects of nanomaterials made of, or covered by, the same material. Different types of bare or PEGylated silica nanoparticles, as well as iron oxide-silica core shell nanoparticles, were tested. Detailed inhibition/enhancement controls revealed enhanced activity in the Limulus coagulation cascade for all particles with bare silica surface. In comparison, PEGylation led to a lower degree of enhancement. These results indicate that the protein-particle interactions are the basis for the observed inhibition and enhancement effects. The enhancement activity of a particle type was positively related to the calculated particle surface area. For most silica particles tested, a dilution of the sample within the maximum valid dilution was sufficient to overcome non-valid enhancement, enabling semi-quantification of the endotoxin contamination.
Purpose: A powerful principle in nature is the presence of surface patterns to improve specific characteristics or to enable completely new functions. Here, we present two case studies where bioinspired surface patterns based on the adhesive system of geckos may be applied for biomedical applications: residue-free adhesion to skin and gecko-inspired suture threads for knot-free wound closure. Methods: Gecko-inspired skin adhesives were fabricated by soft lithography of polydimethylsiloxane with successive inking and dipping steps. Their adhesion was measured using a home built adhesion tester designed for patterned surfaces. Preliminary lap shear tests on the back of a human hand were also performed. Commercial suture threads from different materials were patterned in the group of A. del Campo at the Max-Planck-Institute for Polymer Research (Mainz, Germany) using oxygen plasma. The treated threads were pulled through artificial skin in both directions measuring the peak force and the pull through force. Results and Conclusions: Unpatterned reference samples of the skin adhesive did not stick to human skin, while the patterned samples all showed notable adhesion up to 1.2 Newton for a sample size of approximately 3 cm². First results with the patterned suture threads indicated that the surface patterning of the thread has only a minor effect on the pull-through forces. To achieve knot-free sewing the surface geometry of the suture threads needs to be optimized and more realistic testing procedures, e.g. testing on human skin, are necessary.
Chemical and Structural Comparison of Different Commercial Food Supplements for Silicon Uptake
(2023)
Various food supplements for silicon uptake were compared in terms of their structures and chemical compositions. In particular, we analyzed the silanol group content, which can be an indicator of the uptake of the siliceous species in the human body. We analyzed the commercial products Original Silicea Balsam®, Flügge Siliceous Earth Powder, Pure Colloidal Silicon, and BioSil® by applying various methods such as FTIR, 29Si NMR, and TGA. The Si-OH group content of the samples containing pure silica was the highest for the Original Silicea Balsam followed by the Pure Colloidal Silicon. The siliceous earth powder revealed the lowest content of such groups and the densest structure. BioSil® contained a considerable concentration of organic molecules that stabilized orthosilicic acid. The study may help to understand the silicon uptake behavior of different food supplements depending on their chemical structure.
An unresolved issue in contemporary biomedicine is the overwhelming
number and diversity of complex images that require annotation, analysis and interpretation. Recent advances in Deep Learning have revolutionized the field of computer vision, creating algorithms that compete with human experts in image segmentation tasks. However, these frameworks require large human-annotated datasets for training and the resulting “black box” models are difficult to interpret. In this study, we introduce Kartezio, a modular Cartesian Genetic Programming-based computational strategy that generates fully transparent and easily interpretable image processing pipelines by iteratively assembling and parameterizing computer vision functions. The pipelines thus generated exhibit comparable precision to state-of-the-art Deep Learning approaches on instance segmentation tasks, while requiring drastically smaller training datasets. This Few-Shot Learning method confers tremendous flexibility, speed, and functionality to this approach. We then deploy Kartezio to solve a series of semantic and instance segmentation problems, and demonstrate its utility across diverse images ranging from multiplexed tissue histo-pathology images to high resolution microscopy images. While the flexibility, robustness and practical utility of Kartezio make this fully explicable evolutionary designer a potential game-changer in the field of biomedical image processing, Kartezio remains complementary and potentially auxiliary to mainstream Deep Learning approaches.
Herein an assay toward a rapid and reliable profiling of extracellular matrix of Escherichia coli (E. coli) utilizing a tandem of GC-MS as a tool for definition of the exact chemical nature of low molecular weight compounds and cyclic voltammetry for their high throughput detection is presented. Briefly, during a set of investigations the formation of glycerol in the extracellular matrix (ECM) of E. coli at physiological relevant conditions of cells was revealed. Based on the obtained knowledge, the electrochemical protocol allowing both qualitative and quantitative analyses of glycerol in E. coli ECMs at palladium ink-modified screen printed electrodes with precision values (RSD) <10 % and recovery rates ranged from 98 % to 102 % was proposed. The provided protocol for a rapid electrochemical profiling of the bacterial ECMs can readily be used as a guideline for the controlled electroanalysis of target electroactive signaling analytes in complex biological samples.