A synergic effect of CNT/Al2O3 reinforcements on multiscale epoxy-based glass fiber composite: fabrication and molecular dynamics modeling

Investigating the flexural behavior of nanomodified multi-delaminated composites using acoustic emission technique

The formation of multiple delaminations is a frequently observed damage mechanism in composite materials, exerting a more pronounced influence on their strength properties compared to single delaminations. To tackle this issue, the incorporation of nanoparticles has been investigated as a means to enhance composite materials. This study aims to examine the effects of nano-additives, specifically carbon nanotubes and nanosilica, on the flexural behavior of glass/epoxy composites containing multiple embedded delaminations. The acoustic emission technique is employed to gain deeper insights into the damage mechanisms associated with flexural failure. Artificial delaminations of varying sizes, arranged in a triangular pattern, were introduced into four interlayers of a [(0/90)2]s oriented glass/epoxy composite. The findings reveal a notable reduction in flexural properties due to the presence of multiple delaminations. However, the addition of nanoparticles demonstrates a significant improvement in the flexural behavior of the multi-delaminated specimens. The most substantial enhancement is observed in the composite incorporating 0.3 wt% nanosilica + 0.5 wt% carbon nanotubes. Furthermore, genetic K-means and hierarchical clustering techniques are employed to classify different damage mechanisms based on the peak frequency and amplitude of the acoustic emission signals. The results indicate that the hierarchical clustering method outperforms the genetic K-means method in accurately clustering the acoustic emission signals. Moreover, the incorporation of nanoparticles' impact on the occurrence of distinct damage mechanisms is evaluated through the analysis of acoustic signals using Wavelet Packet Transform. By investigating the flexural behavior of nanomodified multi-delaminated composites and employing the acoustic emission technique, this study offers valuable insights into the role of nanoparticles in enhancing the mechanical properties and monitoring the damage mechanisms of composite materials.

The recent development of carbon-based nanoparticles as a novel approach to skin tissue care and management - A review

Since the skin is the first barrier of the body's defense against pathogens, delays in the healing process are affected by infections. Therefore, applying advanced substitute assistance improves the patient's quality of life. Carbon-based nanomaterials show better capabilities than conventional methods for managing skin wound infections. Due to their physicochemical properties such as small size, large surface area, great surface-to-volume ratio, and excellent ability to communicate with the cells and tissue, carbon-based nanoparticles have been considered in regenerative medicine. moreover, the carbon nano family offers attractive potential in wound healing via the improvement of angiogenesis and antibacterial compared to traditional approaches become one of the particular research interests in the field of skin tissue engineering. This review emphasizes the wound-healing process and the role of carbon-based nanoparticles in wound care management interaction with tissue engineering technology.

Mechanical optimization of an Al-Al2O3 composite nanowire via molecular dynamics simulation and metaheuristic optimization

In the present study, mechanical properties optimization is investigated for an Al-Al2O3 composite nanostructure. The Al-Al2O3 composite nanostructure is considered an Aluminum nanowire reinforced by spherical Al2O3 particles. The structure tensile test is simulated via molecular dynamics simulation using LAMMPS. The mechanical properties of the composite are extracted from the obtained stress-strain curve of the composite. The important mechanical properties include maximum stress and toughness. An optimization process is then applied to maximize the mechanical properties of the composite via metaheuristic optimization algorithms including Genetic Algorithm (GA), Ant Colony (ACO), and Grey Wolf Optimizer (GWO). Since the studied nanostructure is mono crystal, the reinforcing mechanism differs from that of a grained macro material. Therefore, the optimization variables are not confined to size and volume fraction but they also include the location of the particles. The optimization is performed for 0.05 and 0.10 volume fractions and different particle sizes with respect to the location of particles. Applying the optimization process, the mechanical properties of the studied composite nanowire are substantially improved for tensile loading. The results reveal that the placement of the particles has a considerable effect on the improvement of mechanical characteristics. At last, a pattern is presented for the placement of particles to achieve the highest tensile characteristics of Al-Al2O3 composite nanowires.