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Graphene and its related materials are increasingly applied in fiber‐reinforced polymers to tailor their material properties for high performance composites. Yet, the use of graphene derivatives that underwent a plasma functionalization process is not well understood. This study uses 1.50 wt.% of unfunctionalized (rGO) or plasma‐treated reduced graphene oxide with amine‐functionalities (frGO) in an epoxy matrix to prepare unidirectional pre‐impregnated carbon fibers. The material characteristics of the graphene‐modified carbon fiber‐reinforced polymers (g‐CFRP) are compared to the neat carbon fiber‐reinforced polymer (CFRP). Both g‐CFRP configurations exhibit a higher void content than the neat CFRP. No significant difference between the CFRP and the g‐CFRPs is observed with respect to the Young's modulus, glass transition temperature, storage modulus, specific heat capacity, thermal conductivity at room temperature, and in‐plane electrical conductivity. Yet, a reduction in ultimate tensile strength of up to −13% is noted. In addition, the apparent interlaminar shear strength and transverse electrical conductivity are increased by up to +12% for the rGO‐CFRP and +52% for the frGO‐CFRP. This knowledge will support the selection of additives for fiber‐reinforced polymers for, for example, lightning strike protection in aircrafts, sensory materials, electromagnetic interference shielding or heat transfer elements.

Estimating the load-carrying capacity of concrete structures is a major challenge as the infrastructure industry thrives to reduce the consumption of concrete for environmental concerns as well as improving the cost and time efficiency of infrastructural projects. Quantifying such load-carrying capacity needs a detailed study of the micro-structures of the concrete mixture composed of stones, reinforcement, and cement matrix. Computed Tomography (CT) provides a reliable nondestructive technique to analyze and segment the different materials within the concrete structures. However, CT is normally accompanied by different kinds of artifacts that highly degrades the quality of the reconstructed image. Among these artifacts, scatter imposes severe degradation of the quality of the image including reduced contrast between different materials, cupping and streaks artifacts. Several methods were used to remove the scatter effect. The most effective way to correct for the scatter effect is by the use of the Monte Carlo (MC) method due to the accurate modeling of the physics accompanying the photon matter interaction. In this work, a fast MC photon transport model accelerated over the use of the GPU(s) platforms is developed. It is extensively verified against several well-known simulators and experimentally has been used to correct the scatter effect and to improve the contrast between the concrete component.