A study of laser generated Rayleigh and Lamb waves in graphite/epoxy composites

The application of laser generated ultrasonics was first demonstrated in the mid-seventies and has shown good potential when applied to isotropic materials. However, its use with composite materials is still in the early stages of development. This study explores the potential for application of laser generated Rayleigh and Lamb waves in graphite/epoxy composites. Numerical results are obtained by the solution of the wave equations using assumed solutions, and enforcing the boundary conditions. Experimentally, Rayleigh and Lamb waves were generated by a Q-switched ruby laser in the ablation regime and detected by piezoelectric pinducers which permitted accurate phase velocity measurements. The Rayleigh wave velocity was measured at various directions relative to the fiber direction and results were found to agree closely with numerical predictions. The increase of surface wave velocity using thin plates could be useful for the application of delamination detection in thick composites and an increase of Rayleigh wave attenuation could indicate damages caused by impact. Also, surface waves can reflect from small surface cracks. Therefore, laser generated surface waves, particularly along the fiber direction, have high potential for application in non-destructive testing. Lamb wave experiments were conducted in aluminum plates and gave distinctive signals, but there were some difficulties in detecting the precise arrival of each Lamb wave mode for the graphite/epoxy composite plates

Donepezil Regulates LPS and Aβ-Stimulated Neuroinflammation through MAPK/NLRP3 Inflammasome/STAT3 Signaling

The acetylcholinesterase inhibitors donepezil and rivastigmine have been used as therapeutic drugs for Alzheimer’s disease (AD), but their effects on LPS-and Aβ-induced neuroinflam-matory responses and the underlying molecular pathways have not been studied in detail in vitro and in vivo. In the present study, we found that 10 or 50 μM donepezil significantly decreased the LPS-induced increases in the mRNA levels of a number of proinflammatory cytokines in BV2 mi-croglial cells, whereas 50 μM rivastigmine significantly diminished only LPS-stimulated IL-6 mRNA levels. In subsequent experiments in primary astrocytes, donepezil suppressed only LPS-stimulated iNOS mRNA levels. To identify the molecular mechanisms by which donepezil regulates LPS-induced neuroinflammation, we examined whether donepezil alters LPS-stimulated proin-flammatory responses by modulating LPS-induced downstream signaling and the NLRP3 inflam-masome. Importantly, we found that donepezil suppressed LPS-induced AKT/MAPK signaling, the NLRP3 inflammasome, and transcription factor NF-kB/STAT3 phosphorylation to reduce neuroin-flammatory responses. In LPS-treated wild-type mice, a model of neuroinflammatory disease, donepezil significantly attenuated LPS-induced microglial activation, microglial density/morphol-ogy, and proinflammatory cytokine COX-2 and IL-6 levels. In a mouse model of AD (5xFAD mice), donepezil significantly reduced Aβ-induced microglial and astrocytic activation, density, and mor-phology. Taken together, our findings indicate that donepezil significantly downregulates LPS-and Aβ-evoked neuroinflammatory responses in vitro and in vivo and may be a therapeutic agent for neuroinflammation-associated diseases such as AD. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.1

NMR studies of Hydrothermal Carbon Materials as Electrocatalytic Electrodes for Water Splitting

Hydrogen has emerged as an essential part of the green energy system needed to ensure a sustainable future. The production of clean hydrogen using water-splitting with renewable energy, combined with the urgency to reduce greenhouse gas emissions, has received unprecedented interest in politics and business. In this regard, carbon-based materials that own unique advantages, including structure diversity, good electrical conductivity, and mechanical strength, have been widely investigated in water-splitting. One of the synthetic techniques for producing carbon materials, the hydrothermal carbonization, allow tailoring the desired morphology, chemical composition, and structure. The main focus of this work is to understand the properties of Hydrothermal Carbon (HTC) materials for the application as an electrocatalytic electrode for water-splitting, using various NMR techniques (i.e., Solid state NMR techniques, NMR dynamics techniques, and Dynamic Nuclear Polarization (DNP) NMR techniques, etc.). The fundamental understanding regarding the chemical structure of materials and the water interaction with its surface is essential in applying a knowledge-based approach to the development of electrodes for water-splitting. NMR methods to investigate the water interaction behavior of various HTC types was developed using water dynamics, and it was confirmed that the information regarding water interaction was straight correlated to the electrochemical properties in water-splitting. It was also investigated if the introduction of nitrogen into HTC improves water interaction. The presence of N-functional groups influences the water interaction with (N)-HTC (HTC and nitrogen-functionalized HTC(N-HTC)) more strongly than surface area, pore size distribution, or oxygenated functional groups. Furthermore, the degree of water interaction can be tuned by adjusting the synthesis temperature and the precursor ratio of glucose and urotropine. Due to the high hydrophilicity, N-HTC can have internal water in a near-surface layer inside the particles, whereas HTC has no internal water. Surprisingly, the main difference of HTC compared to conventional carbon materials, such as graphene or carbon nanotubes, is the much greater incorporation of oxygen functional groups, but the oxygenated functionalities in HTC play a minor role in the interaction with water. The cause of poor water interaction behavior for HTC was revealed through NMR experiments with non-degassed and degassed water. HTC, as revealed by longitudinal (T1) relaxation time and diffusion NMR, can adsorb O2 from non-degassed water, which leads to a decrease in the degree of water interaction. On the other hand, when HTC is present in degassed water without O2, the water interaction with HTC increases dramatically. It suggests that the sites related to O2 adsorption in HTC are connected to that involved in the water interaction. Interestingly, contact with water activates the ability of O2 adsorption in HTC. This suggests the application of the HTC material as O2 scavenger in water, but not from air; therefore, it can easily be handled in air. This could be another HTC application. The use of NaOH as an activating agent for the manufacture of activated carbon has attracted great interest due to the valuable properties of the materials produced by this process. NMR was applied to reveal not only why a NaOH-activated carbon (Na-AC) exhibits a high catalytic activity (current density of up to 30 mA/cm2) and excellent stability (lifetime test: 48 h) compared to non-treated one (Non-AC), but also the mechanism of chemical activation by NaOH. The treatment with NaOH was found to induce changes on the surface oxygen functionalities, leading to a higher amount of carboxylic acid and lactone functional groups, thereby improving water interaction, which plays a key role in the catalytic process. In the non-washed Na-AC electrode, sodium exists in the structure of sodium carbonate, whereas, in the washed Na-AC electrode, residual Na was presented as complex Na-containing surface groups at the edges of the aromatic lamellae inside the pores. In particular, when the non-washed Na-AC electrode was in water or 0.1M KOH electrolyte, the Na-AC trapped hydrated Na ions well in the pores, and the exchange rate between in-pore water and ex-pore water was slower than Non-AC. Understanding surface-activity relationships of materials is a promising topic for revealing their working mechanisms in different applications as well as for optimization with improved properties. DNP-enhanced solid-state NMR was performed to probe the surface of N-HTC selectively at atomic resolution. In a typical magic-angle spinning (MAS) DNP experiment, several mechanisms are simultaneously involved when transferring much larger polarization of electron spins to NMR active nuclei of interest. Recently, spontaneous 1H-13C cross-relaxation induced enhancement (CRE) effect under DNP by active motions that was not frozen out at even 100 K was reported as one of the mechanisms. Based on this, the spontaneous 1H-15N CRE effect under DNP was first demonstrated using both primary ammonium and amine structures in model compounds during 15N DPMAS DNP. The influence on CRE efficiency caused by variation of the radical solution composition and by temperature was also investigated. Notably, the structural depth-profiling with the CRE effect under DNP has been demonstrated using 13C/15N fully labeled N-HTC having effective reorientation dynamics of methyl and amine groups on the particle surface. CRE contributions on the signal can be determined as a function of polarization time, which is then associated with the spin diffusion length inside the particle. This selectivity showed differences in structural distributions between surface and bulk, with carbonyl and amide groups having a higher concentration near the surface of N-HTC. This new approach could be beneficial for low surface area materials that have been challenging for DNP applications, like N-HTC (0.7 m2/g). Furthermore, this approach may also be extended to systems where the reorientation dynamics of protons on the surface are not available. By the intentional introduction of isotope-labeled probe molecules with rotatable protons on the surface of a material, surface polarization could be enabled

Selection of<i>Lecanicillium</i>Strain with High Virulence against Developmental Stages of<i>Bemisia tabaci</i>

Selection of fungal strains with high virulence against the developmental stages of Bemisia tabaci was performed using internal transcribed spacer regions. The growth rate of hyphae was measured and bioassay of each developmental stage of B. tabaci was conducted for seven days. All of the fungal strains tested were identified as Lecanicillium spp., with strain 4078 showing the fastest mycelium growth rate (colony diameter, 16.3 ± 0.9 mm) among the strains. Compared to strain 4075, which showed the slowest growth rate, the growth rate of strain 4078 was increased almost 2-fold after seven days. Strains 4078 and Btab01 were most virulent against the egg and larva stages, respectively. The virulence of fungal strains against the adult stage was high, except for strains 41185 and 3387. Based on the growth rate of mycelium and level of virulence, strains 4078 and Btab01 were selected as the best fungal strains for application to B. tabaci, regardless of developmental stage

Creep Deformation of Type 2205 Duplex Stainless Steel and its Constituent Phases

The creep deformation of type 2205 duplex stainless steel in industrial continuous annealing conditions was analyzed and compared with the creep behavior of its constituent phases, ferrite and austenite. The bulk ferrite phase deformed by viscous glide. The deformation of the bulk austenite phase was by lattice diffusional creep at low applied stress and by dislocation climb at higher applied stress. Grain boundary sliding was the rate controlling mechanism of creep deformation of duplex stainless steel. The value of the stress exponent and the grain size exponent of the creep rate equation both strongly support the possibility that cold rolled type 2205 duplex stainless steel deforms superplastically during recrystallization annealing in industrial continuous annealing furnaces.X1122Ysciescopu

Generation of AI-based proxy radar data from GK2A/AMI data in East Asia

&amp;lt;p&amp;gt;Remote sensing data such as weather satellites and radars with the high spatio-temporal resolution are importantly used for severe weather monitoring. Geostationary meteorological satellites can observe clouds in a wide area, and the weather radar can obtain rainfall intensity information close to the ground truth through raindrop particle observation. These remote sensing data are collected as real-time images, which are suitable for application to image convolution-based artificial intelligence (AI) models. In this study, we developed an AI-based model for the generation of proxy radar data from the Geo-Kompsat-2A (GK2A) satellite data. As an AI model structure, an image-to-image translation technique called Pix2PixCC which is based on a conditional Generative Adversarial Network (cGAN) was used. For the training model, GK2A satellite data and composite data of radar reflectivity with Korea, Japan, and China were used. In order to solve the memory issue of AI model learning using high-performance GPU, the model was trained by dividing the image into 256x256 patch sizes. This AI model made it possible to produce real-time proxy radar data without gaps in the East Asian region, and this proxy data showed a similar shape to the real radar data compared to precipitation information from geostationary meteorological satellites in traditional methods. In future studies, we plan to improve the accuracy by applying a custom loss function that applies a high weight to the high reflectivity of radar.&amp;lt;/p&amp;gt;</jats:p

Mechanical Behavior of the Constituting Phases in Duplex Stainless Steel during Creep Deformation

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