Electrical, Thermal and Mechanical Properties of CNT Treated Prepreg CFRP Composites

Abstract

This study is part of Smart Intelligent Aircraft Structures (SARISTU) project, which aims considerable improvements in aircraft damage tolerance, electrical conductivity and weight reduction besides producibility in industrial scale. In this study, the effect of multiwalled carbon nanotube reinforcement on electrical, thermal and mechanical properties of T800/M21 carbon fibre reinforced plastic is studied experimentally. T800/M21 is a commercial prepreg carbon fibre/epoxy composite material considered for CNT treatment by means of CNT-doped thermoplastic-based dry powder. The CNTs are deposited on top of prepreg material uniformly using a controlled spraying machine selecting the best state-of-the art and innovative performing technology from the candidate technologies within the project. The electrical conductivity of the composite material with/without CNT is measured in longitudinal, transverse and thickness directions. The changes occurring in the electrical conductivity of the composite materials are investigated. In order to investigate thermal behaviour of the composite materials, differential scanning calorimetry and thermogravimetric analyses are performed. Detailed thermal analysis is conducted for with/without carbon nanotube reinforced material to obtain the thermal conductivity, specific heat and thermal expansion coefficient of the material. Finally, the effect of carbon nanotube reinforcement on mechanical behaviours is studied by tensile, bending and shear tests.

Recent advancements in interface engineering of carbon fiber reinforced polymer composites and their durability studies at different service temperatures

“…[38,93] However, the homogeneity in the dispersion of nanofillers decides the extent of improvement in mechanical properties. [5,94] There are various dispersion techniques, which include sonication assisted dispersion, [80] high frequency sonication assisted dispersion, [92] shear mixing, [81,95] magnetic stirring assisted dispersion, [96] calendaring, [83,97] thermal spraying of prepregs, [98] shear mixing with vacuum bagging, [99] and resin film infusion. [100] 2.1.1 | CNTs and functionalized CNTs as potential reinforcements…”

“…There are a variety of nanofillers available, which serve different functionalities in CFRP composites. [91,98,110] A fact to be noted is that not all nanofillers contribute towards enhancing mechanical performance. They could even lead to a decrement in the mechanical performance of CFRP composites.…”

FEA modelling and environmental assessment of a thin-walled composite drive shaft

“…This mirrors results observed by others who have studied using composite materials as a replacement for metals in automotive components. 40 Volume fraction was given the highest weighting as it contributes significantly to composites properties. Size was given a low weighting as the drive shaft is small in comparison to part typically manufactured from composites for the aerospace industry.…”

“…2-4 the most appropriate fibres would be carbon or basalt, while the most appropriate matrices are epoxy or bio-based epoxy resin. It has been reported that small amount of carbon nanotubes (CNT), i.e., 0.5-1wt%, can increase the strength of carbon/epoxy composites by 7-16% without changing the modulus [38][39][40]. Based on this DMM, three composites were chosen for study, including carbon/epoxy (C/E), basalt/bio-epoxy (B/BE) and carbon/CNT/epoxy (C/CNT/E).…”

Multi-fidelity probabilistic optimisation of composite structures under thermomechanical loading using Gaussian processes

“…Hence, RBDO focuses on the safety of structures when they are exposed to catastrophic and extreme circumstances. Many research works have considered the thermal buckling behaviours of composite and metallic structures caused by thermal expansions without considering mechanical loading [1][2][3][4][5]. Despite this, few research works have studied the thermomechanical buckling behaviours of composite structures, and they have applied deterministic optimisation methods that do not consider uncertainties [6,7].…”