Ultrathin MoSSe alloy nanosheets anchored on carbon nanotubes as advanced catalysts for hydrogen evolution

The activity of transition metal dichalcogenides (TMD) toward hydrogen evolution reaction (HER) derives from the active sites at the edges, but the basal surface still remain catalytic insert. Herein, ultrathin MoSSe alloy nanosheets array on multiwalled carbon nanotubes (MWCNTs) to form a core shell structure via a simple solvothermal process. These three-dimensional (3D) MoSSe hybrids show a high activity in hydrogen evolution reaction (HER) with a small Tafel slope of 38 mV dec⁻¹ and a low overpotential of 102 mV at 10 mA cm⁻². In addition, their HER activity remains remarkably stable without significant decay after 100 h polarization. Such superior catalytic HER activity springs from the 3D hierarchical heterostructure, which is abundant of catalytic edge sites, and the alloy effect between S and Se, which will create huge defects and strain to form vacancy sites on the basal plane. This strategy may open a new avenue toward the development of nonprecious high-performance HER catalysts.     

PtIr alloy nanowire assembly on carbon cloth as advanced anode catalysts for methanol oxidation

The interconnecred PtIr alloy nanowires were uniformly deposited on carbon cloth via One-step wet chemistry method, which diameter is averaged to be 5 nm with a length of 50–200 nm. The carbon cloth supported PtIr nanowire assembly (PtIr NA/CC) shows a larger electrochemical active surface area (ECSA) due to its 3D nanostructure and a high CO-resistance as a result from the synergistic effect of PtIr alloy. The PtIr NA/CC exhibits an extremely high mass activity and a reliable long-term stability toward methanol oxidation reaction (MOR). The superior catalytic performance on MOR can match and even surpass those best Pt-based nanowires reported recently in the literature.     

Heat Transfer and Deformation Behavior of Shell Solidification in Wide and Thick Slab Continuous Casting Mold

With the considerations of the behaviors of shell deformation, mold flux film and air gap dynamic distribution in shell/mold gap, a two dimensional slice-travel transient thermo-mechanical coupled model of simulation shell solidification in wide and thick slab continuous casting mold was developed by using the commercial program ANSYS. The evolutions of strand-mold system thermal behaviors, including the air gap formation and the mold flux film dynamical distribution in shell/mold gap and shell temperature field, and the evolutions of shell deformation and stress distribution of peritectic steel solidified in a 2120 mm wide and 266 mm thick slab continuous casting mold were analyzed. The results show that the air gap formation and the thick mold flux film distribution mainly concentrate in the regions 0–21 mm and 0–7 mm, 0–120 mm and 0–100 mm off the shell wide and narrow faces corners, and thus the hot spots are given rise to form in the regions 15–55 mm and 15–50 mm off the shell wide and narrow face corners. The shell server deformation occurs in the off-corners in the middle and lower parts of the mold. The stress evolution in shell surface is tensile stress, while that in shell solidification front is compressive stress.     

Light-modulated ferromagnetism of strained NiFe2O4 nanocrystals

Light provides a potential approach to modulate magnetism due to the low energy consumption, which could be used for the development of optical-magnetic coupling devices, data storage technology and quantum computation technology. In this work, NiFe₂O₄ nanocrystals with inverse spinel structure confined in non-magnetic Al₂O₃ film are synthesized. Based on theoretical calculation and experimental validation, it is revealed that the NiFe₂O₄ nanocrystals experience compressive strain from Al₂O₃ film. The compressive strain can be partially relaxed, leading to the formation of disorder layers at the surfaces of strained NiFe₂O₄ nanocrystals, which provide an ideal platform to modulate magnetism optically. A remarkable light-modulated ferromagnetism in the strained NiFe₂O₄ nanocrystals is observed. This work demonstrates a novel approach to optically engineer the ferromagnetic properties for applications in next generation of magnetic nano-devices.     

Characterization of polyaniline doped with diphenyl phosphate

UV–Vis spectroscopy and conductivity of the polyaniline (PANI) doped with diphenyl phosphate (DPHP), in comparison with that of HCl-doped polyaniline, show that the decrease in polaron delocalization and structural order results from the steric hindrance imparted by the longer chain counter ion. PANI protonated with DPHP is soluble in common organic solvents such as toluene, chloroform, dimethyl sulfoxide, etc. The conductivity of PANI/DPHP pressed pellet (at 25°C, 1.66 S cm⁻¹) increases with temperature from −40°C (1.18 S cm⁻¹) to +140°C (3.07 S cm⁻¹) due to thermal activation, and decreases with temperature from 140 to 180°C (0.25 S cm⁻¹) due to thermal undoping accompanied by the loss of some polarons. The temperature dependence of spin density is consistent with those of conductivity. After the heating scan, the conductivity (0.52 S cm⁻¹) at room temperature reduces to nearly one-third of the original value.     

Isolation and identification of procyanidins in apple pomace

The chemical nature of the procyanidin components in apple pomace was investigated as part of a programme seeking alternative uses of the large quantity of pomace that is being generated from the apple juice industry. The homogeneous nature of the procyanidin fractions was demonstrated by the isolation and identification of a range of epicatechin oligomers, namely epicatechin-(4β-6) epicatechin, epicatechin (4β-8) epicatechin, epicatechin (4β-8) epicatechin (4β-8) epicatechin and epicatechin (4β-8) epicatechin (4β-8) epicatechin (4β-8)-epicatechin. The procyanidin polymers were also isolated and purified by a Sephadex LH20 column and shown to consist exclusively of epicatechin units. The chemical structures of these procyanidins were established by ¹³C-NMR spectroscopy, by acid-catalysed degradation reaction with phloroglucinol and by electrospray mass spectrometry.     

Research on programmable controller of construction machinery based on embedded system and cloud computing

In recent years, significant advances in sensor innovation have achieved considerable advances in the proficiency of development and the level of computerization of development hardware. The application of sensor technology to monitor such conditions, self-governing development, and the Internet of Things (IOT) has been generally concentrated in development apparatus. Above all else, this work primarily screens the innovation of oil contamination and holes, vibration and fumes gas checking, and describes construction machinery conditions, including monitoring. Second, this article examines and talks about movement, rotational movement, route/situating frameworks, and vision framework straight for independent development innovation. Third, the Internet of Things Technology will be explained, especially regarding research on general construction machinery, maintenance in the life cycle, construction management, and safety management. Proposed Divergence Data Control Technology (DDCT) is a work under IOT with FPGA tools. Finally, with the advancement of unwavering high quality, sensitive sensors, and huge information, the board of sensor data is portrayed as solving potential problems for future construction machinery.     

Prediction simulation of sports injury based on embedded system and neural network

Sports injury prediction is one of the most important parts of the challenge of prevention and harm challenging in motion. Sports injury contemplated wherein a simplified view of the phenomenon to study the reduction unit's cause. A linear analysis is viewed as the unidirectional manner a substantial portion of, and causality. This reduction method depends on the correlation and regression analysis. Despite the extensive efforts to predict sports injuries, the existing method is the inability to identify the predictors that were and have been limited. The risk of the very important element for sports players' injury when developing prevention and risk mitigation strategies for work-related accidents. Some signs can be used in many ways to identify risk factors for injury. However, it can be made from the data and lead to incorrect inferences and difficulty understanding the nuances of different statistical methods. The proposed Neural Network (NN) and the embedded system classify the sports player's injury prediction to solve the problem. The proposed Neural Network (NN) and the embedded system have attracted a simple calculation and interpretation of the reliable results for sports injury prediction. The simulation results show the high performance compared to other existing methods.     

Campus football application based on FPGA system and GPS wearable electronic equipment

Campus football application is a Wearable innovation in sports area disassembling wearable innovation functionality for different clients and why there is such a need for these gadgets in everyday existence. It shows how persuasive the various sensors are in conveying an assortment of readings, which can help from many angles, in the existing method, deep learning and machine learning-based campus football application monitoring system. In this current system, data monitoring, data sharing are significantly less accurate in the football application monitoring system. So in the proposed system Global Positioning System (GPS) and FPGA (Field Programmable Gate Array) for Campus Football Application. Wearable sensors are expanding at work, and by coordinating innovations, clients are gathering more information about themselves. The scale of the wearable design is vast, each with its function to perform in different organizations. Sports wearable include an inertia rating unit and a Global Positioning System (GPS) sensor, which can be modified for various purposes. In this audit, differences show which sensors are feasible and lead to sensor innovation for sport applications. The sport requires constant emotional assessment. This is because the details observed by the sensors are physical. The Colony Optimization Algorithm presentation classifies a portion of the assessment capabilities. Separation can give clients a picture of their performance. The sensors measure the execution details and are done by data preparation, where the channels may vary on the actual information in terms of execution. Other reliability concerns are whether the continuous data input is as accurate as the post-game information.