Free‐Standing,Multilayered Graphene/Polyaniline‐Glue/Graphene Nanostructures for Flexible,Solid‐State Electrochemical Capacitor Application

Graphene/polyaniline multilayered nanostructures (GPMNs) are prepared using a straightforward process through which graphite is physically exfoliated with quaternary polyaniline (PANI)‐glue. This is only accomplished by sonication of the graphite flakes in an organic solvent to form continuous films with PANI. During the sonication, the conductive PANI‐glue is spontaneously intercalated between the graphene sheet layers without deterioration of the sp² hybridized bonding structure. The resultant free‐standing, flexible films are composed of a network of overlapping graphene sheets and are shown to have a long‐range structure. The effects of different PANI content ratios and different interfacial energies (depending on the dispersion solvent) on the morphology and properties of the resulting GPMN are examined. It is found that GPMNs dispersed in water have a maximum specific capacitance of 390 F g⁻¹ in a three‐electrode configuration. Importantly, the unique structural design of GPMNs enables their use as electrode materials for the fabrication of flexible, solid‐state electrochemical capacitors, which show an enhanced performance compared to graphene‐only devices. They exhibit a high specific capacitance of 200 F g⁻¹, a cycling stability with capacitance retention of 82% after 5000 charge/discharge cycles, and, moreover, superior flexibility.     

Direct Applicability of La0.6Sr0.4CoO3 – δ Thin Film Cathode to Yttria Stabilised Zirconia Electrolytes at T ≤ 650 °C

For investigating the direct applicability of highly active cobalt containing cathodes on YSZ electrolytes at a lower processing and operating temperature range (T ≤ 650 °C), we fabricated a thin film lanthanum strontium cobalt oxide (LSC) cathode on an yttria stabilised zirconia (YSZ)‐based solid oxide fuel cell (SOFC) via pulsed laser deposition (PLD). Its electrochemical performance (5.9 mW cm^–2 at 0.7 V, 650 °C) was significantly inferior to that (595 mW cm^–2 at 0.7 V, 650 °C) of an SOFC with a thin (t ∼ 200 nm) gadolinium doped ceria (GDC) buffer layer in between the LSC thin film cathode and the YSZ electrolyte. It implies that even though the cathode processing and cell operating temperatures were strictly controlled not to exceed 650 °C, the direct application of LSC on YSZ should be avoided. The origin of the cell performance deterioration is thoroughly studied by glancing angle X‐ray diffraction (GAXRD) and transmission electron microscopy (TEM), and the decomposition of the cathode and diffusion of La and Sr into YSZ were observed when LSC directly contacted YSZ.     

Efficient flow‐control algorithm cooperating with energy allocation scheme for solar‐powered WSNs

Recently, solar energy emerged as a feasible supplement to battery power for wireless sensor networks (WSNs) which are expected to operate for long periods. Since solar energy can be harvested periodically and permanently, solar‐powered WSNs can use the energy more efficiently for various network‐wide performances than traditional battery‐based WSNs of which aim is mostly to minimize the energy consumption for extending the network lifetime. However, using solar power in WSNs requires a different energy management from battery‐based WSNs since solar power is a highly varying energy supply. Therefore, firstly we describe a time‐slot‐based energy allocation scheme to use the solar energy optimally, based on expectation model for harvested solar energy. Then, we propose a flow‐control algorithm to maximize the amount of data collected by the network, which cooperates with our energy allocation scheme. Our algorithms run on each node in a distributed manner using only local information of its neighbors, which is a suitable approach for scalable WSNs. We implement indoor and outdoor testbeds of solar‐powered WSN and demonstrate the efficiency of our approaches on them. Copyright © 2010 John Wiley & Sons, Ltd.     

Photocrosslinkable Zwitterionic Ligands for Perovskite Nanocrystals: Self-Assembly and High-Resolution Direct Patterning

Perovskite nanocrystals (PNCs) are attractive photoactive materials in various optoelectronic devices including light-emitting diodes, solar cells, and photodetectors. However, the weakly bound surface ligands on PNCs reduce colloidal stability and cause film formation and patterning difficulties, severely restricting their practical applications. Herein, a rationally designed photocrosslinkable zwitterionic (PZ) ligand is introduced to obtain directly patternable CsPbBr₃ PNCs with enhanced colloidal stability, optical properties, and self-assembly propensity. The PZ ligands strongly interact with the pre-synthesized PNCs in solution, substantially replacing the original capping ligands and effectively passivating surface defects. This surface engineering induces strong electrostatic interactions between the PNCs, enabling the fabrication of densely packed CsPbBr₃ PNC films. Furthermore, the methacrylate group of the PZ ligands serves as a bridge for active radical propagation in the ligand shells around the PNCs upon UV exposure. Accordingly, high-resolution direct photopatterning can be achieved through ligand crosslinking, and the resulting PNC patterns (minimum line spacing of 4 µm) maintain optical stability for over 2 weeks. Therefore, this study demonstrates that a tailored ligand design strategy enables the simultaneous achievement of high colloidal stability, optical properties, photopatternability, and self-assembly propensity and has considerable potential to be extended to other PNC materials.     

High-performance liquid chromatography using diode array detector and fluorescence detector for hydrogen peroxide analysis in processed fishery foods

Food Science and Biotechnology - Hydrogen peroxide (H2O2) is a food additive for bleaching and sterilization, owing to its strong oxidizing effect. The current study aimed to develop analytical...     

Artificial intelligence enabled smart machining and machine tools

Journal of Mechanical Science and Technology - Artificial intelligence (AI) in machine tools offers diverse advantages, including learning and optimizing machining processes, compensating errors,...     

Measurement of re-suspended road dust emission factor using mobile laboratory and flux tower

Re-suspended road dust is one of the main urban atmospheric pollutants. Thus, systematic management of polluted roads is essential, which requires precise measurement of re-suspended road dust emission factors. A mobile laboratory (ML) and a flux tower (FT) were used to measure re-suspended road dust. Re-suspended road dust concentration was measured while driving the ML at speeds of 40, 50, and 60 km/h along straight sections of five different roads in Incheon City, Korea. The correlation between measurements using the ML and the FT was anlyzed according to the ML speed. The results revealed a linear relationship between the mass concentration measured by the ML and the emission factor obtained from the FT. At faster ML speeds, the same emission factor was associated with higher concentrations measured by the ML. Thus, if the ML measurements are adjusted for the ML speed by employing the methods of this study, re-suspended road dust emission factors can be measured more accurately. Based on these findings, it is expected that the use of the MLs will contribute to reducing re-suspended road dust by enabling more effective management of road pollution levels.

     

Generating Texture for 3D Human Avatar from a Single Image using Sampling and Refinement Networks

There has been significant progress in generating an animatable 3D human avatar from a single image. However, recovering texture for the 3D human avatar from a single image has been relatively less addressed. Because the generated 3D human avatar reveals the occluded texture of the given image as it moves, it is critical to synthesize the occluded texture pattern that is unseen from the source image. To generate a plausible texture map for 3D human avatars, the occluded texture pattern needs to be synthesized with respect to the visible texture from the given image. Moreover, the generated texture should align with the surface of the target 3D mesh. In this paper, we propose a texture synthesis method for a 3D human avatar that incorporates geometry information. The proposed method consists of two convolutional networks for the sampling and refining process. The sampler network fills in the occluded regions of the source image and aligns the texture with the surface of the target 3D mesh using the geometry information. The sampled texture is further refined and adjusted by the refiner network. To maintain the clear details in the given image, both sampled and refined texture is blended to produce the final texture map. To effectively guide the sampler network to achieve its goal, we designed a curriculum learning scheme that starts from a simple sampling task and gradually progresses to the task where the alignment needs to be considered. We conducted experiments to show that our method outperforms previous methods qualitatively and quantitatively.     

Effect of Texture and Temperature on Strain-Induced Martensitic Transformation in 304 Austenitic Stainless Steel

The austenitic stainless steel's remarkable mechanical properties are caused by twinning-induced plasticity and transformation-induced plasticity mechanisms. Numerous studies focus on stacking fault energy's effect, which is affected by various factors, to interpret and control these mechanisms. However, crystallographic orientation is also an important parameter for mechanical properties in metals. This study compares the mechanical properties and microstructural features of 304 austenitic stainless steel, focusing on the effect of initial texture and deformation temperature. Microstructural characterization is identified by an interrupted tensile test based on strain, tensile direction, and temperature conditions, and X-ray diffraction and electron back-scattered diffraction analysis are performed. The results show that the mechanical features and strain-induced martensitic transformation rate depend on the tensile directions. In addition, this trend is maintained irrespective of the temperature conditions. The attribute reason is that the difference in the Taylor factor and the formation rate of the deformed band structure is induced by the initial crystallographic orientations. Moreover, a decrease in temperature significantly increases the dislocation densities and abundant twins and transformed martensites formation. Furthermore, the yield and tensile strengths are enhanced while the elongation decreased with the tensile strains.