Enhanced catalytic activity of nanoshell carbon co-doped with boron and nitrogen in the oxygen reduction reaction

The use of carbon cathode catalysts in polymer electrolyte fuel cells instead of the current platinum catalysts is attracting increasing attention. We claim that two factors are important for enhancing the activity of carbon cathode catalysts in the oxygen reduction reaction (ORR): the formation of a nanoshell structure and co-doping with boron and nitrogen. Herein, we investigate the preparation and characterization of active ORR carbon catalysts that combine the above factors. Boron and nitrogen (BN)-doped nanoshell-containing carbon (BN-NSCC) was prepared by carbonizing a mixture of poly(furfuryl alcohol), cobalt phthalocyanine, melamine, and a trifluoroborane–methanol complex at 1000 °C. Transmission electron microscopy and X-ray photoelectron spectroscopy revealed the formation of nanoshell structures with distorted graphitic layers and the introduction of boron and nitrogen atoms, respectively. The ORR activity was evaluated in oxygen-saturated 0.5 mol dm^?3 H₂SO₄ using Koutecky–Levich analysis. The BN-NSCC showed an eight to ten times higher ORR activity than undoped NSCC, with an increased number of electrons participating in the reaction. Tafel analysis revealed a change in the rate-determining step caused by BN-doping. Thus, the combination of a nanoshell structure and co-doping with boron and nitrogen was found to improve the ORR activity of carbon catalysts.     

Grain Boundary Segregation Behavior of Boron in Low-Alloy Steel

The boron concentration profiles around prior austenite grain boundaries in Fe-0.05C-0.5Mo-0.001B (mass pct) are examined using aberration-corrected STEM-EELS. In order to obtain the precise distribution of boron around the boundaries, tilt series measurements with thin specimens (<30 nm) are performed and the EEL spectra are analyzed by principal component analysis (PCA) and multivariate curve resolution (MCR). The boron concentration profile changes with the cooling rate from the solid solution temperature. The concentration at grain boundaries is maximized at a medium rate (30 °C/s), where the concentration reaches 8 at. pct, and it decreases at a larger (250 °C/s) or smaller (5 °C/s) rate. On the other hand, the boron distribution becomes wider as the cooling rate becomes smaller. The current results suggest that the boron segregation in the alloy is formed by the “non-equilibrium segregation mechanism.”     

Modeling of quantitative relationships between physicochemical properties of active pharmaceutical ingredients and tensile strength of tablets using a boosted tree

Objectives: The aim of this study was to explore the potential of boosted tree (BT) to develop a correlation model between active pharmaceutical ingredient (API) characteristics and a tensile strength (TS) of tablets as critical quality attributes.

Methods: First, we evaluated 81 kinds of API characteristics, such as particle size distribution, bulk density, tapped density, Hausner ratio, moisture content, elastic recovery, molecular weight, and partition coefficient. Next, we prepared tablets containing 50% API, 49% microcrystalline cellulose, and 1% magnesium stearate using direct compression at 6, 8, and 10?kN, and measured TS. Then, we applied BT to our dataset to develop a correlation model. Finally, the constructed BT model was validated using k-fold cross-validation.

Results: Results showed that the BT model achieved high-performance statistics, whereas multiple regression analysis resulted in poor estimations. Sensitivity analysis of the BT model revealed that diameter of powder particles at the 10th percentile of the cumulative percentage size distribution was the most crucial factor for TS. In addition, the influences of moisture content, partition coefficients, and modal diameter were appreciably meaningful factors.

Conclusions: This study demonstrates that BT model could provide comprehensive understanding of the latent structure underlying APIs and TS of tablets.     

Interface control for resolved CFD-DEM with capillary interactions

In this work, a resolved CFD–DEM coupling model for the simulation of gas-liquid-solid flows is developed: the interface capturing method based on the colour function is employed for fluids (i.e. a gas and liquid) whilst Discrete Element Method (DEM) is used for particles. The Volume Penalisation (VP) method is adopted to consider the hydrodynamic interactions between fluids and particles along with the Immersed Free Surface (IFS) method, which artificially extends the gas-liquid interface into the interior of the particle to account for the wettability. The unique point of the proposed model is that the thickness of the gas-liquid interface can be controlled by using both interface compression and diffuse interface techniques simultaneously. From the simulation results, it is presented that the accurate evaluation of the surface tension force as well as the capillary force can be achieved by appropriately controlling the interface thickness. Moreover, the major two methods in the literature to calculate the capillary force are compared in this work. The validity of the proposed model is presented for both static and dynamic cases. The behaviour of two colliding particles with a dynamic liquid bridge is then simulated to demonstrate the applicability of the proposed model to a complex three-phase system.     

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.     

Local structure and photocatalytic property of sol–gel synthesized ZnO doped with transition metal oxides

ZnO nanoparticles doped with up to 5 at% of Co and Mn were prepared using a co-precipitation method. The location of dopant ions and the effect of doping on the photocatalytic activity were investigated. The crystal structure of nanoparticles and local atomic arrangements around dopant ions were analyzed by X-ray absorption spectroscopy. The results showed that the Co ions substituted the Zn ions in the ZnO wurtzite phase structure and induced lattice shrinkage, while Mn ions were not completely incorporated in the crystal lattice. The photocatalytic activity under simulated sunlight was characterized by the decomposition of Rhodamine B dye molecules. It was revealed that Co-doping strongly reduced the photocatalytic activity but Mn-doping showed a weaker effect on the reduction of the photoactivity.     

Development of a simple capillary electrophoretic determination of glucosamine in nutritional supplements using in-capillary derivatisation with o-phthalaldehyde

A simple capillary electrophoretic method was developed for the determination of glucosamine using in-capillary derivatisation. Glucosamine in commercial products was extracted with purified water. The CE separation was achieved on an uncoated fused-silica capillary using a 20 mM borate buffer (pH 9.2) containing 5 mM o-phthalaldehyde (OPA) and 5 mM 3-mercaptopropionic acid (MPA) at 25 kV, followed by UV detection at 340 nm. The detector response was linear (r² > 0.999) in the concentration range 10–1000 μg/mL. The limit of detection (LOD) was 1.3 mg/g. Spiked glucosamine recoveries at 50 and 100 mg/g level were 95.1% and 104.3%, respectively. The method was applied to 16 commercial products. The concentrations of glucosamine were 109–705 mg/g, and the ratios of detected glucosamine content to the labelled value were 88.8–124%. No significant bias was observed (r² = 0.989, p < 0.01), between results obtained by the proposed CE method and an official colorimetric method (Japanese Health Food & Nutrition Food Association).     

Antitermitic activity of extracts from Chamaecyparis obtusa branch heartwood

The antitermitic activity of extracts from the branch heartwood of Chamaecyparis obtusa (hinoki) against Japanese termites (Reticulitermes speratus) was compared with that of the trunk. Samples of branch and trunk heartwood were extracted with n-hexane, ethyl acetate, and methanol successively. n-Hexane extracts of branch and trunk heartwood were strongly antitermitic, and branch heartwood contained greater quantities of active n-hexane extracts than trunk heartwood. Germacra-1-(10), 5-dien-4β-ol, t-cadinol, α-cadinol, hinokiresinol, and hinokinin were separated from the branch extracts and the termiticidal and antifeedant activity of these compounds was tested by no-choice and dual-choice test methods. The sesquiterpenoids, germacra-1-(10), 5-dien-4β-ol, t-cadinol and α-cadinol were strongly termiticidal. The norlignan hinokiresinol and lignan hinokinin had weak termiticidal, and strong antifeedant and repellent activity. High concentrations of germacra-1-(10), 5-dien-4β-ol and hinokiresinol were present in branch heartwood. These compounds protect hinoki branches from termites and other harmful organisms. Hinoki branch heartwood, which is usually unused, is a potential source of active antitermitic compounds.     

Connection‐Strength Estimation of Neuronal Networks by Fitting for Izhikevich Model

Recently, there has been abundant research using multineuron recording, but there are many problems with extracting the features from the obtained spike time series, which are huge in volume and complex. Here we introduce a new method of estimating synaptic connection strengths between neurons by fitting to the Izhikevich model by maximum likelihood estimation. We demonstrate that our method can estimate connection strengths from spike time series given by a simulated neural ensemble and can estimate nonconnectivity between two independent cultured neuronal networks. These results suggest that our method is applicable to network and plasticity analysis of neuronal networks.