Effect of Co addition on microstructural and mechanical properties of WC–B4C–SiC composites

In this study, the effect of Co addition on microstructural and mechanical properties of WC-B₄C–SiC composites sintered by spark plasma sintering (SPS) method was investigated. For this purpose, three batches of WC-B₄C–SiC with different contents of Co (10 vol%, 15 vol%, and 20 Vol %) were sintered at 1400 °C. The results of X-ray diffraction (XRD) analysis of the samples indicated the formation of W₂B₅, W₃CoB₃ as well as the remained C phases and unreacted SiC phase. It was observed that by increasing the Co content, the amount of W₂B₅ phase reduces and W₃CoB₃ and C contents increase. Therefore, W₂B₅ peaks were not detected in the sample containing 20vol% Co. Relative density values above 97% were obtained for all the composites. However, a decrease was observed in relative density by increasing the Co content in the composites. The highest flexural strength (510 ± 42 MPa), fracture toughness (10.34 ± 0.82 MPa m^1/2), and hardness (20.63 ± 0.75 GPa) were also obtained for the sample containing 10vol% Co compared to the other samples. In addition, Transgranular fracture of SiC as well as pulling out of W₃CoB₃ and W₂B₅ particles were observed in the fracture surface micrographs of the samples. The presence of micro-cracks in the SiC grains, fracture of W₃CoB₃ grains, and crack deflection was reported as dominant toughening mechanisms.     

Barium cobaltite nanoparticles: Sol-gel synthesis and characterization and their electrochemical hydrogen storage properties

The study of the effect of different chelating agents in the Pechini method on the morphology has been a promising strategy that can be used for practical tuning of the nanoparticle's morphology and hence the electrochemical hydrogen storage capacity. In the current study, the conventional Pechini sol-gel approach was used to prepare the Ba₂Co₉O₁₄ nanoparticles as a novel hydrogen storage material. The X-ray diffraction investigation approved the formation of Ba₂Co₉O₁₄ with a Hexagonal crystal structure for all of the synthesized samples. The scanning electron microscopy (SEM) revealed when citric acid was used as a chelating agent, nanoparticles with finer and more uniform morphology were obtained rather than other chelating sources. The transmission electron microscopy (TEM) showed in the presence of citric acid; the size of the synthesized nanoparticles was between 14 and 24 nm. According to the Diffuse Reflectance Spectroscopy (DRS) analysis, the calculated bandgap of synthesized nanoparticles was approximately 3.2 eV, which indicates that synthesized nanoparticles were semiconductors in essence. The electrochemical hydrogen adsorption/desorption results showed that the sample synthesized by the citric acid has an enhancement in electrochemical hydrogen storage of approximately 800 mAh/g after 15 cycles.     

Integrated energy in Germany–A critical look at the development and state of integrated energies in Germany

In the face of global warming and a scarcity of resources, future energy systems are urged to undergo a major and radical transformation. The recognition of the need to embrace renewable energy technologies and to move toward decarbonization has led to significant changes in the German energy generation, consumption and infrastructure. Ambitious German national plans to decrease carbon dioxide emissions on one side, and the unpredictable and volatile nature of renewable energy sources on the other side have elevated the importance of integrated energies in recent years. The deployment of integrated technologies as a solution to interlink various infrastructures creates opportunities for increasing the reliability of energy systems, minimizing environmental impacts and maximizing the share of renewable resources. This paper discusses the role of integrated energy systems in supporting of sustainable solutions for future energy transitions. Moreover, the reinforcement of this movement with the help of different technologies will be discussed and the development of integrated energy systems in Germany will be reviewed.     

Investigation on Microstructure,Wear Behavior and Microhardness of Al−Si/SiC Nanocomposite

Aluminum matrix nano-composites have been widely used in various fields such as aerospace, automobile, and packing industries. In this study, the effect of nano-SiC content on the microst-ructure, wear resistance and micro-hardness of Al–Si/SiC nano-composite was investigated. In this regard, Al–Si matrix was reinforced by different amounts of nano-SiC: 0, 0.5, 1, 1.5, 3, 5, 10 wt %. The results showed that with increasing the nano-SiC weight ratio, nano-particles are agglomerated and unsuitable sintering increases the porosity, as pores and cavities. For more than 1.5% weight ratio of nano-SiC in the matrix, the wear resistance and the micro-hardness decreased. The results of the wear test, scanning electron microscopy, energy dispersive X-ray spectroscopy and worn surfaces showed that the dominant wear mechanism is controlled by nano-SiC contents. This study indicated that with adding nano-SiC particles more than the optimal content, wear resistance and micro-hardness of Al–Si/SiC nano-composite increased more than twice.     

Cr2O3 nanoparticles: A promising candidate to improve the mechanical properties and corrosion resistance of Ni-Co alloy coatings

This study was aimed to assess the effects of reinforcement nanoparticles content, on the microstructural features, mechanical properties, and corrosion-related properties of Ni-Co-Cr₂O₃ nanocomposite coatings. Scanning electron microscope (SEM), energy dispersive X-ray spectrometer (EDS), and X-ray diffraction (XRD) analysis were employed in order to evaluate the microstructural features and chemical composition of the nanocomposites. Moreover, the microhardness tester and electrochemical impedance spectra (EIS) tests coupled with potentiodynamic polarization measurements were used to investigate the mechanical and corrosion-related properties, respectively. Results demonstrate that albeit the volume fraction of cobalt in coating, average particle size, Cr₂O₃ nanoparticle content in coating, and microstructural features are of prime significance in determining the mentioned properties of the nanocomposite coatings, Co content is more important. Actually, Cr₂O₃ nanoparticles serve as suitable nucleation sites for Co particles deposition throughout the microstructure. Thus, combined actions of Cr₂O₃ nanoparticles incorporation and their optimal content ensures the nucleation of high population of Co particles, which significantly contributes to the improvement in the properties. The Ni-Co-8.9 wt%Cr₂O₃ nanocomposite coating exhibits the superior mechanical and corrosion-related properties.     

Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning

The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by using a Model consisting of various Neural Networks trained on a custom dataset. It can be automated into assisting designers, allowing them to focus on the other more complicated parts of the system they are designing by quickly generating what would rather be straightforward busywork. Over the past 20 years, the boom in how much the internet is used and the sheer volume of pages on it demands a high level of work and time to create them. For the efficiency of the process, we proposed a multi-model-based architecture on image captioning, consisting of Convolutional neural network (CNN) and Long short-term memory (LSTM) models. Our proposed approach trained on our custom-made database can be automated into assisting designers, allowing them to focus on the other more complicated part of the system. We trained our model in several batches over a custom-made dataset consisting of over 6300 files and were finally able to achieve a Bilingual Evaluation Understudy (BLEU) score for a batch of 50 hand-drawn images at 87.86%