Predicting the strength of 3D-printed conductive composite under tensile load: A probabilistic modeling and experimental study
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https://orcid.org/0009-0003-3493-2519
Fatima Majid
Laboratory of Nuclear, Atomic, Molecular, Mechanical and Energetic Physics, Chouaib Doukkali University, El jadida, Morocco
https://orcid.org/0000-0001-8909-8232
Taoufik Hachimi
Laboratory of Nuclear, Atomic, Molecular, Mechanical and Energetic Physics, Chouaib Doukkali University, El jadida, Morocco
Najoua Barhoumi
Laboratory of mechanics materials and processes, National high school of engineering of Tunis (ENSIT), 5 rue Taha HussienMonfleury, 1089 Tunis Bab Alleoua, Tunis
https://orcid.org/0000-0002-7005-9601
Kaouthar Khlifi
Laboratory of mechanics materials and processes, National high school of engineering of Tunis (ENSIT), 5 rue Taha HussienMonfleury, 1089 Tunis Bab Alleoua, Tunis
Soufyan Dadoun
Laboratory of Nuclear, Atomic, Molecular, Mechanical and Energetic Physics, Chouaib Doukkali University, El jadida, Morocco
https://orcid.org/0009-0004-1853-3910
Abstract
Conductive PLA is an innovative composite material that combines the ecological benefits of polylactic acid, a biodegradable thermoplastic, with electrical conductivity properties. Usually used in additive manufacturing for its ease of printing and low environmental impact, PLA remains an insulator, which limits its applications in the electrical field. To overcome this limitation, conductive fillers such as carbon nanotubes or carbon black are being added, opening the way to new functional uses. This study focuses on a specific composite: carbon black-filled PLA (PLA-CB). This material combines the qualities of traditional PLA with enhanced conductivity thanks to the carbon black particles. To assess its performance, a number of mechanical tests were carried out, including tensile tests on samples manufactured by 3D printing using the FFF process. The study focused in particular on the influence of crosshead speed and the impact of different notch shapes on the material's properties. To analyze the durability of PLA-CB, a probabilistic model based on the two-parameter Weibull distribution was used to assess the risk of failure under different conditions. Reliability curves were also established to better understand the tensile stress and strain at break of the material. This approach could also be applied to other 3D-printed polymers to refine their analytical and numerical modeling.
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