journal article·2025-11Open access

Exploring microstructural characteristics and tensile behaviour in 3D-Printed polyethylene terephthalate

Lotfi Hedjazi, Sofiane Belhabib, Sofiane Guessasma

Abstract

This study investigates the mechanical performance, microstructural characteristics, and optimization strategies for 3D-printed PET, focusing on the effects of printing temperature and angle. Tensile behaviour analysis reveals that while temperature variations (200–230°C) have a minor effect, the printing angle plays a pivotal role in determining mechanical properties. Lower angles (≤ 15°) enhance stiffness, tensile strength, and elongation at break by minimizing porosity and improving interfilament bonding. Conversely, higher angles (θ = 30°) result in increased porosity (up to 2.1%), leading to reduced mechanical performance. Microstructural analysis highlights the influence of filament arrangement and cohesive layering on stress distribution and mechanical integrity. Finite element simulations predict stress heterogeneity and align qualitatively with experimental results, demonstrating the significant impact of porosity and filament orientation on mechanical properties. To validate practical applicability, a bike bottle holder was successfully 3D-printed using PET. The design, occupying only 4.52% of the design domain volume, achieved a balance between material efficiency, mechanical performance, and energy consumption, with optimal settings of a 0° printing angle and an intermediate temperature of 210°C. These findings underscore the importance of optimizing printing parameters to enhance the structural performance and energy efficiency of 3D-printed PET components, providing valuable insights for future applications in additive manufacturing.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Additive Manufacturing and 3D Printing Technologies · Innovations in Concrete and Construction Materials · Manufacturing Process and Optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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