Mechanical and thermal performance of 3D-printed polycarbonate composites reinforced with aerosil nanoparticles under extreme conditions

Abstract In the quest for high-performance materials capable of withstanding extreme environments, Additive Manufacturing (AM) has emerged as a powerful tool for designing customized polymer composites. By integrating functional nanofillers into thermoplastic matrices, it becomes possible to enhance mechanical, thermal, and structural properties while exploiting the freedom of AM. This study introduces a novel class of additively manufactured composite materials that combine ceramic nanofillers (Aerosil 300) with a polycarbonate (PC) matrix. Aerosil was incorporated at weight fractions of 1%, 2%, and 4% to improve the mechanical performance of the polymer. The main objective is to investigate the mechanical behavior of these composites under extreme thermal conditions, through static compression tests performed at temperatures ranging from − 90 °C to 80 °C. The influence of Aerosil content on void formation and interlayer quality is further examined through SEM analysis, with the aim of minimizing process-induced defects. Two loading configurations were tested: out-of-plane (compression parallel to the printing direction) and in-plane (compression perpendicular to the printing direction), to assess the influence of printing orientation on the mechanical response. In addition to the experimental approach, a comprehensive numerical analysis was carried out using Digimat and Abaqus to simulate both the mechanical behavior and the additive manufacturing process. A 3D thermomechanical model was developed to evaluate the impact of printing parameters on residual stresses, temperature gradients, deflections, and warpage in Aerosil/PC printed parts. The results demonstrate that the addition of Aerosil 300 significantly enhances the mechanical and thermal performance of the composites under harsh conditions. Furthermore, the combined numerical-experimental approach proves effective in predicting process-induced defects and provides valuable insights for optimizing additive manufacturing processes.