Current trends in the description of lanthanum strontium manganite oxygen electrode reaction mechanism in a high-temperature solid oxide cell

This review summarizes recent progress in understanding the oxygen reduction and evolution reactions at the lanthanum strontium manganite electrode of a high-temperature solid oxide cell. Information provided here is put into the perspective of the defect chemistry of lanthanum strontium manganite and its impact on the electrode reaction mechanisms itself. After summarizing recent views on the oxygen reduction reaction mechanism, the focus turns to the oxygen evolution reaction, which is significantly less treated in the literature. A combination of the information in the literature on both reactions was the basis for modified reaction mechanism of the oxygen evolution reaction to be proposed under consideration of recent experimental observations and theoretical findings.     

Polymeric Carbon Nitride-based Single Atom Photocatalysts for CO2 Reduction to C1 Products

Photocatalytic CO₂ reduction to C₁ fuels is considered to be an important way for alleviating increasingly serious energy crisis and environmental pollution. Due to the environment-friendly, simple preparation, easy formation of highly-stable metal-nitrogen(M-N_x) coordination bonds, and suitable band structure, polymeric carbon nitride-based single-atom catalysts(C₃N₄-based SACs) are expected to become a potential for CO₂ reduction under visible-light irradiation. In this review, we summarize the recent advancement on C₃N₄-based SACs for photocatalytic CO₂ reduction to C₁ products, including the reaction mechanism for photocatalytic CO₂ reduction to C₁ products, the structure and synthesis methods of C₃N₄-based SACs and their applications toward photocatalytic CO₂ reduction reaction(CO₂RR) for C₁ production. The current challenges and future opportunities of C₃N₄-based SACs for photoreduction of CO₂ are also discussed.     

介观电路中量子纠缠的经典对应

从量子力学诞生日起,它的经典对应(或类比)一直是物理学家关心的话题.本文以介观电路量子化的框架中,带有互感的两个介观电容-电感(LC)电路为例,首次讨论了量子纠缠的经典类比(或对应)问题.先用有序算符内的积分理论证明其互感是产生量子纠缠的源头;再推导出求解特征频率的公式,就发现它与一个经典系统的小振动频率的表达式有相似之处,该经典系统组成如下:两个墙壁各连一个相同的弹簧,两个弹簧之间接着一个滑动小车可以在光滑的桌面上运动,小车挂有一根单摆.用分析力学求此系统的小振动频率,发现与上述介观电路的特征频率形式类似,单摆的摆动会造成小车来回振动,摆、小车和弹簧的互相牵制效应反映了小车和摆的"纠缠".     

Vacuum-gap-based lumped element Josephson parametric amplifier

We propose a lumped element Josephson parametric amplifier with vacuum-gap-based capacitor.The capacitor is made of quasi-floating aluminum pad and on-chip ground.We take a fabrication process compatible with air-bridge technology,which makes our design adaptable for future on-chip integrated quantum computing system.Further engineering the input impedance,we obtain a gain above 20 dB over 162-MHz bandwidth,along with a quasi quantum-limit noise performance.This work should facilitate the development of quantum information processing and integrated superconducting circuit design.     

Photocatalytic Cr(VI) sequestration and photo-Fenton bisphenol A decomposition over white light responsive PANI/MIL-88A(Fe)

Polyaniline (PANI)/MIL-88A(Fe) (Px@M88) composites were constructed through a simple one-pot hydrothermal method. The photocatalytic and photo-Fenton activities of Px@M88 composites toward reduction of Cr(VI) and degradation organic pollutants were explored by white light irradiation. PANI, as a conductive polymer, can improve MIL-88A(Fe)’s conductivity and the efficiency of photogenerated e⁻–h⁺ pair separation. In the presence of H₂O₂, a photo-Fenton reaction occured to boost the degradation efficiency of organic pollutants like bisphenol A. In addition, P9@M88 showed excellent recycling and stability in cycling experiments. Finally, a possible reaction mechanism for photocatalytic degradation was proposed and verified by X-ray photoelectron spectroscopy and electron spin resonance determination and electrochemical characterizations.     

Fe3O4 – Glutathione stabilized Ag nanoparticles: A new magnetically separable robust and facile catalyst for aqueous phase reduction of nitroarenes

The heterostructured Ag nanoparticles decorated Fe₃O₄ Glutathione (Fe₃O₄‐Glu‐Ag) nanoparticles (NPs) were synthesized by sonicating glutathione (Glu) with magnetite and further surface immobilization of silver NPs on it. The ensuing magnetic nano catalyst is well characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), powder X‐ray diffraction (PXRD), thermogravimetric analysis (TGA). The prepared Fe₃O₄‐Glu‐Ag nanoparticles have proved to be an efficient and recyclable nanocatalyst with low catalyst loading for the reduction of nitroarenes and heteronitroarenes to respective amines in the presence of NaBH₄ using water as a green solvent which could be easily separated at the end of a reaction using an external magnet and can be recycled up to 5 runs without any significant loss in catalytic activity. Gram scale study for the reduction of 4‐NP has also being carried out successfully and it has been observed that this method can serve as an efficient protocol for reduction of nitroarenes on industrial level.     

Nonintrusive data-based learning of a switched control heating system using POD,DMD and ANN

The aim of this work is to derive an accurate model of two-dimensional switched control heating system from data generated by a Finite Element solver. The nonintrusive approach should be able to capture both temperature fields, dynamics and the underlying switching control rule. To achieve this goal, the algorithm proposed in this paper will make use of three main ingredients: proper orthogonal decomposition (POD), dynamic mode decomposition (DMD) and artificial neural networks (ANN). Some numerical results will be presented and compared to the high-fidelity numerical solutions to demonstrate the capability of the method to reproduce the dynamics.     

Assessment of Noise Exposure of Sawmill Workers in Southwest,Nigeria

Economic wood processing employs the use of industrial machines for cutting, shaping, milling, and sawing timber, thereby leading to the generation of high levels of noise. Published data from empirical studies have categorized noise as an environmental hazard of global significance. Furthermore, noise exposure limits for different industries and all the industrial machines available has not been formally established as it presently exists in developed nations around the world. Therefore, this study assessed the daily exposure of sawmills workers to noise in Southwestern Nigeria. Reconnaissance surveys were first carried out in Osun, Oyo, Ondo, Ekiti, Lagos, and Ogun States to select sawmills that were fully operational and fit for the study. Two fully functional sawmills in two cities of each State were eventually selected for data collection, making a total of 24 sawmills, while the Circular Machines (CM), Planer Machines (PM), and Band-saw Machines (BM) were the machines in each sawmill considered. Two machines each of CM, PM, and BM were considered in each sawmill, making a total of forty-eight (48) machines each of CM, PM, and BM. Sound data were collected between 7 am and 7 pm each day for six days (between Monday and Saturday) using Extech 407732 sound level meter and all stabilized measurements were taken three times at different intervals. The data collected were in three different periods: Machine No-work Period (NP_m), Machine Idle Period (IP_m), and Machine Working Period (WP_m). A two–way Analysis of Variance (ANOVA) was carried out at P < 0.05 to determine whether there is a significant difference in the sound level average before and after the break, for both the idle and working periods of the three machines considered. This was also done to determine whether there is a significant difference between the sound level average of the results collected during idle and working periods of the three machines. Noise Pollution Levels (L_np) ranged from 83.20 dB (PM) to 107.65 (BM) and 93.42 (CM and PM) – 116.00 (BM) respectively, while IP_m also gave the least noise pollution level of 95.79 dB and WP_m gave the highest level of 102.88 dB. The results revealed that all the machines’ L_np values in the working period are more than the 90 dB acceptable limit the recommendation value of 90 dB while 89.6% of CMs, 75% of PMs, and 89.6% of BM had their L_np above 90 dB in the idle period respectively. The minimum and the maximum noise dose levels for IP_m, WP_m and overall are 0.09 (BM) and 2.37 (CM), 0.50 (CM), and 4.77 (PM) and 0.69 (BM) and 6.64 (PM) respectively. The study found out that the fundamental contributing factors to the high noise levels in sawmills are poor machine maintenance, use of old and obsolete machines, poor housekeeping strategy, limited space, workers’ negligence, lack of PPE, and lack of occupational safety training. The study recommends that proper workplace practices such as use of personal protective equipment, new and modern machines, training, and occupational safety programmes be implemented in the considered sawmills.     

Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.