scholarly journals Fabrication and Electrical Conductivity of Vapor Grown Carbon Fiber Reinforced Aluminum Composites

2009 ◽  
Vol 50 (9) ◽  
pp. 2160-2164 ◽  
Author(s):  
Zhe-Feng Xu ◽  
Yong-Bum Choi ◽  
Kazuhiro Matsugi ◽  
Dong-Chun Li ◽  
Gen Sasaki
2017 ◽  
Vol 52 (11) ◽  
pp. 1495-1503 ◽  
Author(s):  
K Hamdi ◽  
Z Aboura ◽  
W Harizi ◽  
K Khellil

This work tends to characterize the effect of carbon black nanofillers on the properties of the woven carbon fiber reinforced thermoplastic polymers. First of all, composites from nanofilled Polyamide 6 resin reinforced by carbon fibers were fabricated. Scanning electron microscopy observations were performed to localize the nanoparticles and showed that particles penetrated the fiber zone. In fact, by reaching this zone, the carbon black nanofillers create a connectivity's network between fibers, which produces an easy pathway for the electrical current. It explains the noticed improvement of the electrical conductivity of the carbon black nanofilled composites. Electrical conductivity of neat matrix composite passed from 20 to 80 S/cm by adding 8 wt% of carbon black and to 140 S/cm by adding 16 wt% of the same nanofiller. The addition of nanofillers modifies the heating and cooling laws of carbon fiber reinforced polymer: the nanofilled carbon fiber reinforced polymer with 16 wt% is the most conductive so it heats less. Based on these results, the use of the composite itself as an indicator of this mechanical state might be possible. In fact, the study of the influence of a mechanical loading on the electrical properties of the composite by recording the variance of an electrical set is possible.


Polymers ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1865 ◽  
Author(s):  
Liberata Guadagno ◽  
Luigi Vertuccio ◽  
Carlo Naddeo ◽  
Marialuigia Raimondo ◽  
Giuseppina Barra ◽  
...  

A suitably modified resin film infusion (RFI) process was used for manufacturing carbon fiber-reinforced composites (CFRCs) impregnated with a resin containing nanocages of glycidyl polyhedral oligomeric silsesquioxane (GPOSS) for enhancing flame resistance and multi-wall carbon nanotubes (MWCNTs) to contrast the electrical insulating properties of the epoxy resin. The effects of the different numbers (7, 14 and 24) of the plies on the equivalent direct current (DC) and alternating current (AC) electrical conductivity were evaluated. All the manufactured panels manifest very high values in electrical conductivity. Besides, for the first time, CFRC strings were analyzed by tunneling atomic force microscopy (TUNA) technique. The electrical current maps highlight electrically conductive three-dimensional networks incorporated in the resin through the plies of the panels. The highest equivalent bulk conductivity is shown by the seven-ply panel characterized by the parallel (σ//0°) in-plane conductivity of 16.19 kS/m. Electrical tests also evidence that the presence of GPOSS preserves the AC electrical stability of the panels.


2018 ◽  
Vol 18 (5-6) ◽  
pp. 1698-1710 ◽  
Author(s):  
Jan Cagáň ◽  
Jaroslav Pelant ◽  
Martin Kyncl ◽  
Martin Kadlec ◽  
Lenka Michalcová

Electrical resistance tomography is a method for sensing the spatial distribution of electrical conductivity. Therefore, this type of tomography is suitable for sensing damages, which affect electrical conductivity. The utilization of resistance tomography for the structural health monitoring of carbon fiber–reinforced polymer composites is questionable owing to its low spatial resolution and the strong anisotropy of carbon fiber–reinforced polymer composites. This article deals with the employment of resistance tomography with regularization based on a Gaussian anisotropic smoothing filter for the detection of cuts. The advantages of the filter are shown through the image reconstruction of rectangular composite specimens with three different laminate stacking sequences. The cuts are implemented by a milled groove. Visual comparison of the images shows a substantial improvement in the shape reconstruction ability. In addition to visual comparison, the image reconstructions are assessed in terms of the reconstruction error and cross-correlation.


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