Dual-energy X-ray computed tomography for void detection in fiber-reinforced composites

Void detection in fiber-reinforced composites traditionally relies on precise density measurements before and after the physical removal of the polymer matrix; consequently, this method only provides data on the total volume of voids within the material without information about void sizes, shapes, and distributions. Despite advances in X-ray computed tomography, it is still challenging to quantitatively and convincingly characterize void content due to the complex X-ray physics of divergent, broad-spectrum laboratory X-ray sources. Here, we demonstrate that by using aligned high-energy and low-energy X-rays, dual-energy X-ray computed tomography provides high-quality images and phase-based segmentation that allows for clear distinction between air, polymer matrix, and reinforcing fibers. We verify the method on several fiber-reinforced composite samples: epoxy-glass fiber composites fabricated by vacuum-assisted resin transfer molding and by light resin transfer molding (light resin transfer molding), and a carbon fiber composite fabricated via vacuum-assisted resin transfer molding.