Carbon nanotubes (CNTs) have been grown by decomposition of propane over a nanocamposite catalyst by chemical vapour deposition (CVD). The catalyst was prepared from an aluminum/iron oxide/graphite mixture milled in a high-energy ball-milling equipment. Scanning and transmission electron microscopies, Raman spectroscopy and X-ray diffraction measurements have been carried out in order to investigate the catalyst and synthesized CNTs. The results show that iron nanoparticles are produced in an alumina and ball-milled graphite matrix. This produced nanocomposite is used as a catalyst to synthesize CNTs via CVD successfully. The yield of CNTs formation was greatly influenced by the milling time and deposition temperature.
This study concentrated on the role of particle size of silicon carbide (SiC) on dimensional stability of aluminum. Three kinds of Al/SiC composite reinforced with different SiC particle sizes (25 μm, 5 μm, and 70 nm) were produced using a high-energy ball mill. The standard samples were fabricated using powder metallurgy method. The samples were heated from room temperature up to 500• C in a dilatometer at different heating rates, that is, 10, 30, 40, and 60• C/min. The results showed that for all materials, there was an increase in length change as temperature increased and the temperature sensitivity of aluminum decreased in the presence of both micro-and nanosized silicon carbide. At the same condition, dimensional stability of Al/SiC nanocomposite was better than conventional Al/SiC composites.
Microstructural damage can occur during metal forming, but how and where this happens vary with the local microstructure and strain path. Large-scale analysis of such damage mechanisms is particularly important in advanced steels with a heterogeneous phase distribution.
In our previous work, we demonstrated that deep learning enables a mechanism-based, statistical analysis by classifying many individual damage sites. The aim of this work is to generalize this approach to different stress states, e.g., biaxial instead of uniaxial tension, without manually labeling a large new ground-truth dataset of further micrographs and to thereby assess the changes in damage behavior with respect to stress state. Data augmentation and regularization allow us to directly apply our approach to the new, biaxial loading case. Overall, the network performance could be greatly improved and an analysis of changes in damage behavior, here the martensite crack angle distribution, with stress state can now be performed.
Yucca fiber is a natural cellulose fiber that can be extracted from the Yucca plant leaves by retting. The physical properties of the Yucca fiber are extremely sensitive to the retting conditions. This research was designed to study the effects of chemical retting on the structural and properties of this fiber. Chemical retting was done by soaking the Yucca leaf in 10 to 150 g/l sodium hydroxide concentration at 80 to 100 °C for 60 to 240 min. Fiber characteristics such as fineness, tenacity, functional groups, crystallinity, thermal degradation, and surface morphology were then investigated. The Yucca fibers exhibited high crystallinity (56–66%), high tenacity (36–46 cN/tex), and low linear density (3–5 tex). It was also found that the elementary fiber had a mean diameter of about 1.2 [Formula: see text] and a helical structure of square-shaped spires. The thermogravimetric analysis also indicated that the Yucca fiber had the thermal stability of up to 250 °C. Based on the findings, the Yucca fiber may be suitable for various applications such as a reinforcement material in the composites applications and can be turned to yarn for textile applications.
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