Effect of Porosity on Mechanical Properties of 3D Printed Polymers: Experiments and Micromechanical Modeling Based on X-ray Computed Tomography Analysis

Polymers (Basel). 2019 Jul 5;11(7):1154. doi: 10.3390/polym11071154.

Abstract

Additive manufacturing (commonly known as 3D printing) is defined as a family of technologies that deposit and consolidate materials to create a 3D object as opposed to subtractive manufacturing methodologies. Fused deposition modeling (FDM), one of the most popular additive manufacturing techniques, has demonstrated extensive applications in various industries such as medical prosthetics, automotive, and aeronautics. As a thermal process, FDM may introduce internal voids and pores into the fabricated thermoplastics, giving rise to potential reduction on the mechanical properties. This paper aims to investigate the effects of the microscopic pores on the mechanical properties of material fabricated by the FDM process via experiments and micromechanical modeling. More specifically, the three-dimensional microscopic details of the internal pores, such as size, shape, density, and spatial location were quantitatively characterized by X-ray computed tomography (XCT) and, subsequently, experiments were conducted to characterize the mechanical properties of the material. Based on the microscopic details of the pores characterized by XCT, a micromechanical model was proposed to predict the mechanical properties of the material as a function of the porosity (ratio of total volume of the pores over total volume of the material). The prediction results of the mechanical properties were found to be in agreement with the experimental data as well as the existing works. The proposed micromechanical model allows the future designers to predict the elastic properties of the 3D printed material based on the porosity from XCT results. This provides a possibility of saving the experimental cost on destructive testing.

Keywords: 3D printing; X-ray computed tomography; mechanical properties; micromechanical modeling.