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

Lotfi Hedjazi, Sofiane Belhabib, Sofiane Guessasma

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Lotfi Hedjazi, Sofiane Belhabib, Sofiane Guessasma. Exploring microstructural characteristics and tensile behaviour in 3D-Printed polyethylene terephthalate. Journal of Materials Research and Technology, 2025, 39, pp.1168 - 1184. 10.1016/j.jmrt.2025.09.136. hal-05494816

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

Lotfi Hedjazi<sup>a</sup>, Sofiane Belhabib<sup>b</sup>, Sofiane Guessasma<sup>c,*</sup>

## ARTICLE INFO

Handling Editor: SN Monteiro

**Keywords:**

- Additive manufacturing
- Polyethylene terephthalate
- Microstructure
- Tensile performance
- X-ray micro-tomography

## ABSTRACT

This study investigates the mechanical performance, microstructural characteristics, and optimisation 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.

## 1. Introduction

Polyethylene Terephthalate (PET) is a widely used thermoplastic polymer belonging to the polyester family, recognized for its durability, chemical resistance, and transparency [1]. PET was first synthesized in the mid-1940s by John Rex Whinfield and James Tennant Dickson of the Calico Printers' Association in the UK (patent). The structure of PET consists of a chain of monomers derived from terephthalic acid and ethylene glycol. Initially developed as a textile fibre and branded Terylene by Imperial Chemical Industries (ICI) in 1949, PET gained significant traction in the 1970s when it began to be used for plastic bottles. This revolutionized the beverage industry, thanks to its strength, lightweight nature, and recyclability [2]. Over time, PET has become one of the most widely used and recycled plastics globally, particularly in sectors like construction and packaging [2]. Its popularity stems from key properties such as mechanical strength, thermal stability, and chemical resistance [3]. PET also exhibits excellent wear resistance,

maintaining its strength and shape even at high temperatures.

Traditionally, PET is extensively used in the production of bottles, containers, packaging, membranes, films, and fibres [3,4], ranking among the top six most-used polymers [4], with global production reaching up to 20 million tons [5] and a market value of $44 billion [4]. The PET bottling and packaging industries account for a significant portion of this, with nearly one billion bottles produced daily [2]. However, the widespread use of PET also contributes to the 240 million tons of plastic waste generated annually, with up to 65 % of plastic waste being landfilled or incinerated [6]. Consequently, PET research is increasingly focused on recycling [7], degradation [8], carbon footprint evaluation, and the development of biosourced alternatives [1], especially given PET's non-biodegradable nature and the anticipated doubling of its market share by 2030 [4]. Several studies, such as one by Chan et al. [9], emphasize the development of functional materials from PET waste. These valorisation routes include applications in microelectronics, composite matrices, hydrogels, and chemical engineering

<footnote><sup>a</sup> ESTP Campus de Troyes, 1 Rue Fernand Sastre, Rosières-près-Troyes, 10430, France</footnote>

<footnote><sup>b</sup> Nantes Université, IUT, 2 Av. du Professeur Jean Rouzel, Carquefou, 44470, France</footnote>

<footnote><sup>c</sup> INRAE, Research Unit BIA UR1268, Rue Geraudiere, F-44316, Nantes, France</footnote>

<footnote>* Corresponding author.
E-mail address: sofiane.guessasma@inrae.fr (S. Guessasma).</footnote>
additives. For example, PET has been used in building materials, such as asphalt, where it replaces fine aggregates, improving pavement resilience to deformation and moisture [10]. Zou et al. [11] explored recycled PET as a foaming additive in paving applications. Vidakis et al. [26] demonstrated that PET-G retains acceptable mechanical properties after several recycling cycles, highlighting its potential for circular manufacturing. Similarly, Valvez et al. [27] reported that PET-G can act as an effective matrix for recycled glass-based reinforcements, achieving improved stiffness without significant compromise in processability. Moreover, the incorporation of biochar as a reinforcement agent [28] has shown promise in enhancing thermal stability and reducing the environmental footprint of PET-G composites.

The production of PET typically involves an ester-exchange reaction between dimethyl terephthalate and ethylene glycol or esterification of terephthalic acid with ethylene glycol to synthesize bis(hydroxy)ethyl terephthalate, followed by polycondensation [12]. This process is usually carried out through thermal treatment of terephthalic acid and ethylene glycol, with subsequent distillation of ethylene glycol after obtaining the monomer bis(2-hydroxyethyl)terephthalate. The molten PET is then extruded and cooled into an amorphous polymer [13]. The synthesis of certain PET nanomaterials, such as nanofibers, composites, or particles, may involve additional processes like milling or electro-spinning [4].

In recent years, PET has found applications in additive manufacturing (AM), thanks to its ability to create complex geometries, reduce material waste, and streamline production for both prototyping and end-use applications [12]. The growing interest in PET for AM is driven by its beneficial properties, including a high strength-to-weight ratio, durability, and recyclability [14]. These qualities make PET attractive to industries like automotive, aerospace, and consumer goods. Its compatibility with various 3D printing technologies, especially Fused Filament Fabrication (FFF) and Digital Light Processing (DLP), further enhances its adaptability.

In fused filament fabrication, PET is commonly used as a feedstock material, though its use as a recycled material presents challenges, such as variability and reduced mechanical performance [14]. As a feedstock for fused filament technology, PET has been explored as a bulk material or matrix in different blends. Pintos et al. [15] studied the feasibility of 3D printing with various grades of PET using material extrusion. Their research revealed that different grades affected dimensional accuracy and tensile behaviour, particularly in relation to thermal properties and crystallinity. Gebrehiwat et al. [16] examined the mechanical behaviour of carbon fibre-reinforced PET printed with different infill orientations, showing that part orientation significantly influenced creep behaviour and damage development. Vallejo et al. [17] investigated the machinability of 3D printed PET-Glycol (PET-G) composites, concluding that the machinability of carbon fibre-reinforced PET composites is good, even under varying printing parameters. Cano et al. [18] focused on the fracture behaviour of materials, including PET-G, and found it had high structural integrity, ranking second after PLA in fused filament printing. Vidakis et al. [19] investigated the tensile behaviour of various polymeric feedstock materials, including PET-G, under different strain rates. They reported that, within the strain-rate range of 10 mm/min to 100 mm/min, PET-G showed only a slight variation in tensile strength, maintaining an average value of about 42 MPa, while its Young's modulus remained stable at below 0.6 GPa. Landolfi et al. [20] explored material extrusion for recycling PET sourced from bottles, emphasizing the need to optimize processing conditions such as printing speed, bed, and extrusion temperatures. Al Rashid et al. [21] conducted a similar study on AM of PET and carbon fibre-reinforced PET from recycled plastic bottles, highlighting the potential for scaling up the printing process and the superior mechanical properties of PET-based composites. Zouine et al. [22] examined the antibacterial properties of 3D printed PET, demonstrating the effectiveness of surface treatments with tannic and gallic acids in reducing bacterial attachment.

Although the literature highlights successful efforts to optimize the

performance of 3D printed PET, there remains a notable gap in understanding the microstructural basis of the observed performance. For example, many studies rely on SEM micrographs, which provide only partial information, such as failure patterns. To gain a comprehensive understanding of how printing conditions affect the properties of PET, quantitative data on defect extent and the internal architecture of 3D printed PET is needed.

Within this framework, the study investigates fused filament 3D printing of PET, linking microstructural characteristics to mechanical performance. First, 3D printing of PET is carried out using the fused filament route under various printing conditions including printing angle and printing temperature. Synchrotron X-ray microtomography is used to provide a non-destructive means to examine internal structures under diverse printing conditions. Mechanical testing is carried out to study the effect of the printing conditions on tensile performance. The study demonstrates the potential for PET in consumer product design, showing how structural and mechanical criteria can be exploited to achieve controlled, application-specific material properties. This is illustrated in this study through the design and production of a technical part.

## 2. Experimental layout

### 2.1. Materials and processes

The experimental study is based on commercially available PET filament sourced from BASF SE, located in Heidelberg, Germany, under the brand name Ultrafuse® PET. This filament is made from food-safe granulate materials, making it suitable for food-contact applications in compliance with European Plastics Regulations. It has also been evaluated for food-safe 3D printing and meets the requirements of for example German Food, Commodities, and Feed (LFGB) and Regulation (EC) No. 1935/2004. The filament characteristics are summarized in Table 1. The density of PET reflects its relatively high molecular packing. The average ovality indicates good dimensional consistency of the filament. The Poisson's ratio of 0.42 is relatively high, suggesting the material exhibits noticeable lateral expansion under tensile loading, consistent with polymeric behaviour. Thermal properties show that the filament softens under moderate load at relatively low temperatures, relevant for the heat resistance during printing. The glass transition temperature is relatively high compared to PLA. The melt volume-flow rate (MVR) indicates a moderate flowability of the PET during extrusion, which balances good layer adhesion with minimal deformation, suitable for the present study.

The supplier-recommended printing parameters suggest a temperature range of 210 °C-230 °C for the extruder and a base temperature between 60 °C and 80 °C, with a printing speed between 40 and 80 mm/s. PET material is 3D printed using a Raise 3D Pro2 Plus printer. The printing conditions outlined in Table 2 are used to produce 3D printed dogbone-shaped specimens (Fig. 1a) from the PET filament.

For all processing conditions, the samples are oriented longitudinally, with the building direction aligned to the specimen's thickness. The printing parameters vary, with the printing temperature set between 210 °C and 230 °C and the printing angle ranging from 0° to 90° (Table 2, Fig. 1a). The control parameters, namely printing temperature

<caption>Table 1</caption>

Main characteristics of the PET filament in this study.

<table><thead><tr><td>Parameter</td><td>Value</td></tr></thead><tbody><tr><td>Density (g.cm<sup>-3</sup>)</td><td>1.329</td></tr><tr><td>Average ovality (mm)</td><td>&lt;0.050</td></tr><tr><td>Poisson's ratio (-)</td><td>0.42</td></tr><tr><td>Vicat softening at 10 N (°C)</td><td>67</td></tr><tr><td>Vicat softening at 50 N (°C)</td><td>64</td></tr><tr><td>Glass transition (°C)</td><td>74</td></tr><tr><td>Melt Volume-flow rate (cm<sup>3</sup>/10min) (220 °C, 2.16 kg)</td><td>16.3</td></tr></tbody></table>
<table><caption>**Table 2**
Printing conditions of PET considered in this study.</caption><thead><tr><th>Type</th><th>Parameter</th><th>Value</th></tr></thead><tbody><tr><td rowspan="8">Fixed</td><td>Infill (%)</td><td>100</td></tr><tr><td>Nozzle diameter (mm)</td><td>0.6</td></tr><tr><td>Layer height (mm)</td><td>0.3</td></tr><tr><td>Layer height, first layer (mm)</td><td>0.25</td></tr><tr><td>Bed temperature (°C)</td><td>60</td></tr><tr><td>Printing speed (mm/s)</td><td>50</td></tr><tr><td>Support density (%)</td><td>10</td></tr><tr><td>Frame width (mm)</td><td>1.2</td></tr><tr><td rowspan="3">Varied</td><td>Orientation (–)</td><td>Longitudinal (LO)</td></tr><tr><td>Printing angle, θ (°)</td><td>0, 15, 30, 45</td></tr><tr><td>Printing temperature, T<sub>p</sub> (°C)</td><td>200, 210, 220, 230</td></tr></tbody></table>

(200–230 °C) and printing angle (0°–45°), are selected because they are known to have a significant influence on the microstructure and mechanical performance of 3D-printed PET. The lower bound is 20 °C below the temperature recommended by supplier whereas the upper bound is 30 °C below the highest temperature recommended by the supplier. The printing angles were selected to cover the most common raster orientations used in fused filament fabrication, from fully aligned with the load direction to more oblique angles, which are known to influence the amount of filament that effectively participate in the load transfer [23].

## 2.2. Characterization techniques

Prior tensile loading, the microstructure of 3D PET reflecting contrasted printing conditions (θ = 0°, 15°, 30°, and 45°) are analysed. The X-ray micro-tomography technique is employed for three-dimensional imaging of PET samples at the ESRF (European Synchrotron Radiation Facility) beamline BM5 in Grenoble, France (Fig. 1b). The acquisition parameters encompass a 97 kV energy, a 360° scan range, a 1396 mm working distance, 5000 radiographic images, 101 reference images, 100 dark images, 2048 × 800 pixels detector resolution, 0.015s count time, 0.0015 s latency time, and a 3.04 µm voxel size. A back-projection reconstruction algorithm is utilized to generate the tomograms, with the incorporation of Paganin filtering for optimal phase retrieval of phase-contrast images.

To maintain ample resolution at the specified voxel size, two successive acquisitions along the height of the sample are conducted, effectively doubling the acquired volume. The typical tomogram resolution is thus 3856 × 3856 × 1600 voxels, covering an acquired volume of 11.72 × 11.72 × 4.86 mm³. Image analysis is carried out using ImageJ software from NIH (USA), involving tasks such as brightness calibration, conversion to 256 grey-level images, segmentation, 3D rotation, and filtering using opening and closing operators.

Furthermore, background elimination, determination of phase content, assessment of anisotropy, and calculations of size distribution are integral components of the image analysis process.

Tensile tests are performed with the objective of establishing a clear relationship between printing parameters, microstructure, and mechanical performance under uniaxial loading, which is a fundamental and widely used characterization for 3D-printed materials. Tensile tests provide direct measurements of stiffness, strength, and elongation at break, which are highly sensitive to filament orientation, porosity, and interlayer bonding.

All tensile specimens are tested according to ISO 527-1/-2 standard [24] using Zwick/Roell universal machine equipped with a 10 kN load cell (Fig. 1c). Tensile loading continues until material failure at a displacement rate of 5 mm/min. A total of 52 samples are subjected to testing, and for each condition (typically, 4 replicates per condition), the average engineering constants are determined. These include tensile strength, Young's modulus, yield stress, and elongation at break. Deformation sequences are captured using an optical high-speed camera

from Photonline (Phantom V7.3). The entire loading sequence is recorded in full frame (800 × 600 pixels) at a moderate speed of 50 fps (frames per second).

## 3. Finite element computation

To complement the experiments including mechanical testing and microstructure analysis, deeper analyses are carried out using Finite Element (FE) computation to evaluate stress distribution and deformation mechanisms. More specifically, FE analysis is employed to explore the correlation between the microstructure created by 3D printing of PET and its tensile performance.

This method applied to 3D-printed samples is inherently challenging due to the complex microstructure, anisotropy, and presence of porosity within printed parts. Accurately capturing filament orientation, interlayer bonding, and void distribution requires careful modelling. Indeed, as shown in a previous study by the authors [25], converting CAD (Computer-Aided Design) geometries into meshed models results in overestimation of the mechanical performance for fused filament technology as microstructural details and material discontinuities are not considered. These, however, influence the load transfer and stress concentration. To overcome this difficulty, structural meshes are generated from 3D X-ray micro-tomography images using a voxel-to-element conversion scheme. The reliability of the method relies primarily on the resolution of the 3D images. If the resolution is too low the conversion results in irregular or highly fluctuating stress patterns. Thus, there is a balance to find computational efficiency and the accurate representation of stress fields under varying printing conditions. The 3D images are downscaled by a factor of 0.1, yielding a final voxel size of 30.4 µm, which allows achieving the needed compromise. The element size remains well below the filament dimensions. The computational domain volumes are of the order of range from 148 mm³ to 195 mm³, resulting in model sizes spanning 62 million to 82 million degrees of freedom (DOFs), depending on the printing conditions.

The solid phase is uniformly meshed using structural cubic elements, each defined by eight nodes with three displacement components (UX, UY, UZ) per node. An isotropic elastic material model, incorporating the Young's modulus and Poisson's ratio (0.381) for amorphous PET. These data are gathered from tensile experiments performed on as-received materials and complemented by the CES EduPack database (Granta Design, Cambridge, UK) to simulate the tensile behaviour of the 3D-printed PET.

The analysis employs a quasi-static linear model to predict the stiffness of the 3D-printed PET as a function of varying printing angles. Tensile loading is applied along the specimen's length (Z-direction), with boundary conditions restricting lateral displacements (UX = 0 and UY = 0) at both ends (z = 0, z = L, where L is the sample length). A positive displacement (UZ > 0) is applied to nodes at z = L, while nodes at z = 0 are fixed (UZ = 0).

The elasticity problem is solved using a preconditioned Conjugate Gradient (PCG) solver. The overall Young's modulus is determined from the reaction forces at the loaded end (z = L), and von Mises stress fields are derived to examine the influence of the porous structure on stress distribution.

High-performance computing resources, featuring CPUs running at 5.2 GHz and 128 GB of RAM, are employed to handle the large-scale models, with computation times reaching up to 15 min per load increment. All simulations are conducted using ANSYS Multi-Physics software.

## 4. Results and discussion

### 4.1. Mechanical properties of 3D printed PET

Fig. 2 highlights the influence of printing parameters on the tensile behaviour of 3D-printed PET. Fig. 2a shows the deformation sequence of
<figure><img src="image_4.png" /><figcaption>(a)</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>(b)</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>(c)</figcaption></figure>

**Fig. 1.** The dogbone geometry employed in this investigation, along with the tensile testing protocol: (a) a sliced view of the PET specimen with two printing angles, (b) X-ray microtomography configuration at the BM05 beamline (Synchrotron Radiation Facility, ESRF) for 3D microstructural investigation, and (c) the setup for tensile testing captured through optical recording.
<figure><img src="image_7.png" /><figcaption>Fig. 2. Optical recording of deformation sequences for 3D printed PET as a function of (a) printing temperature (Tp) - θ = 0°, and (b) printing angle (θ) - Tp = 200 °C.</figcaption></figure>
PET samples printed at temperatures ranging from 200 °C to 230 °C, specifically focusing on the moments of rupture and maximum extension before rupture. All specimens were printed with a 0° printing angle, meaning the building direction was parallel to the sample thickness (horizontal orientation). The images show only slight elongation before rupture, suggesting a predominantly quasi-brittle behaviour. Cracking occurs rapidly, with little visible damage accumulation prior to failure.

The effect of printing temperature is not distinctly evident from the deformation sequences, as all samples exhibit similar extensions before rupture. The rupture patterns, however, appear consistent across samples. Within the construction plane defined by the sample's width and length, the filament layup significantly affects the behaviour. In all cases (Fig. 2a), cracks deviate toward -45° under local shear, but the material's brittleness limits further deflection, highlighting the predominance of opening mode fracture. Additionally, crack branching is observed, resulting from competing transverse cracks, which eventually cause parts of the sample to be ejected at the rupture point.

Fig. 2b qualitatively demonstrates the effect of the printing angle (θ) on the deformation sequences of 3D-printed PET. For θ = 0°, the same failure characteristics observed in Fig. 2a are evident in another replicate shown in Fig. 2b. When the printing angle is adjusted to 15°, the cracking behaviour remains comparable, but the crack deviation shifts to angles closer to -30° or 60°, aligning with the initial filament orientation in the layup. This adjustment results in less stretching compared to the 0° printing angle.

At a 30° printing angle, the layup aligns more closely with the transverse direction (Fig. 2b), increasing the likelihood of transverse crack propagation through the external frame. This orientation introduces a mixed-mode fracture with two primary crack angles, -15° and 75°.

For a 45° printing angle (Fig. 2b), there is a high likelihood of complete unstable transverse cracking due to discontinuities perpendicular to the loading direction. In this case, the cracking predominantly follows a full opening mode. Crack branching is less probable because the main transverse instability governs the rupture process.

The tensile behaviour under various conditions is further examined in Fig. 3 using engineering stress-strain curves. Fig. 3a illustrates the typical response of three different replicates of the as-received PET filament. Although slight variations are observed among the replicates, the overall tensile trend remains consistent. An elastic-plastic behaviour is evident, characterized by limited stretchability. Further analysis of the tensile response is conducted to determine key engineering constants, key engineering parameters—including Young's modulus (E<sub>Y</sub>), yield stress (σ<sub>Y</sub>), tensile strength (σ<sub>T</sub>), rupture stress (σ<sub>R</sub>), and elongation at break (ε<sub>R</sub>)—derived from the tensile responses of four replicates.

These values are summarized in Table 3, with the variability of the results staying within 8%. The difference between the rupture stress and tensile strength is less than 10%, suggesting a minimal necking effect.

For 3D printed materials, all tested samples exhibit elastic characteristics with a minimal plastic phase. The predominantly elastic-like behaviour is attributed to the filament arrangement and the discontinuities within the samples. This restricted plasticity of 3D-printed PET is consistent with the findings of Toth et al. [26] for samples with 0% elastomer content. It also agrees with Nguyen et al. [27] across various printing conditions including layer thickness and contour count.

Fig. 3a examines the effect of printing temperature, ranging from 200 °C to 230 °C, for a fixed printing angle of 0°. There are no significant differences observed among these conditions. The plasticity stage is limited to approximately 1%, while the linear elasticity shows consistent stiffness across all samples. Only slight variations in ultimate properties and tensile strength are observed.

The influence of the printing angle on mechanical performance is presented in Fig. 3b for a fixed printing temperature of 200 °C. Distinct differences are noted among the conditions. For example, the weakest performance is observed at a 30° printing angle, whereas the 0° and 15° cases exhibit nearly identical trends, improving strength, stiffness, and

<figure><img src="image_8.png" /><figcaption>Fig. 3. Tensile performance of (a) as-received and 3D printed PET as a function of (b) printing temperature (Tp) - θ = 0°, and (c) printing angle (θ) - Tp = 200 °C.</figcaption></figure>

elongation capacity. A printing angle of 45° ranks second overall in terms of performance compared to the top-performing conditions.

A quantitative assessment of the impact of printing conditions is summarized in Table 3, which details the same key engineering parameters measured for the as-received material and for four replicates per condition.

Further analysis of the overall effect of printing temperature reveals a slight improvement in stiffness (about 3%) as the temperature increases, with values rising from 900 MPa to 925 MPa. This improvement is offset by a proportional reduction in elongation at break, also by around 3%. The largest observed increase is in tensile strength, which
<caption>**Table 3**</caption>

Mechanical properties of 3D-printed PET as a function of printing temperature and printing angle. E<sub>Y</sub>: Young's modulus, σ<sub>Y</sub>: Yiled stress, σ<sub>T</sub>: tensile strength, σ<sub>R</sub>: rupture stress, ε<sub>R</sub>: elongation at break.

<table><thead><tr><th>Material</th><th>T<sub>P</sub> (°C)</th><th>θ (°)</th><th>E<sub>Y</sub> (MPa)</th><th>σ<sub>Y</sub> (MPa)</th><th>σ<sub>T</sub> (MPa)</th><th>σ<sub>R</sub> (MPa)</th><th>ε<sub>R</sub> (%)</th></tr></thead><tbody><tr><td>filament</td><td>-</td><td>-</td><td>1175 ± 75</td><td>54.35 ± 4.25</td><td>65.91 ± 0.67</td><td>59.40 ± 8.53</td><td>8.53 ± 0.65</td></tr><tr><td rowspan="15">3D printed</td><td>200</td><td>0</td><td>926 ± 13</td><td>59.87 ± 0.76</td><td>61.14 ± 0.85</td><td>56.76 ± 3.42</td><td>7.51 ± 0.28</td></tr><tr><td>200</td><td>15</td><td>932 ± 11</td><td>60.74 ± 0.62</td><td>61.69 ± 0.29</td><td>58.76 ± 1.46</td><td>7.17 ± 0.15</td></tr><tr><td>200</td><td>30</td><td>841 ± 13</td><td>52.08 ± 0.28</td><td>52.17 ± 0.28</td><td>51.13 ± 1.56</td><td>6.31 ± 0.08</td></tr><tr><td>200</td><td>45</td><td>903 ± 8</td><td>53.65 ± 0.88</td><td>53.68 ± 0.83</td><td>52.95 ± 0.59</td><td>6.02 ± 0.04</td></tr><tr><td>210</td><td>0</td><td>943 ± 8</td><td>61.26 ± 0.28</td><td>62.60 ± 0.25</td><td>59.15 ± 2.86</td><td>7.39 ± 0.37</td></tr><tr><td>210</td><td>15</td><td>944 ± 12</td><td>61.36 ± 0.43</td><td>62.40 ± 0.45</td><td>60.06 ± 0.69</td><td>7.10 ± 0.03</td></tr><tr><td>210</td><td>30</td><td>838 ± 7</td><td>51.76 ± 1.38</td><td>51.77 ± 1.40</td><td>51.19 ± 1.55</td><td>6.27 ± 0.23</td></tr><tr><td>210</td><td>45</td><td>911 ± 24</td><td>57.19 ± 0.54</td><td>57.24 ± 0.61</td><td>57.09 ± 0.57</td><td>6.37 ± 0.09</td></tr><tr><td>220</td><td>0</td><td>956 ± 9</td><td>61.92 ± 0.45</td><td>63.11 ± 0.22</td><td>61.88 ± 1.08</td><td>7.07 ± 0.36</td></tr><tr><td>220</td><td>15</td><td>952 ± 5</td><td>61.49 ± 0.38</td><td>63.08 ± 0.32</td><td>61.37 ± 1.99</td><td>7.13 ± 0.20</td></tr><tr><td>220</td><td>30</td><td>863 ± 14</td><td>54.76 ± 0.88</td><td>54.76 ± 0.88</td><td>54.70 ± 0.95</td><td>6.36 ± 0.04</td></tr><tr><td>220</td><td>45</td><td>937 ± 20</td><td>59.10 ± 2.41</td><td>59.89 ± 2.79</td><td>59.23 ± 2.68</td><td>6.58 ± 0.32</td></tr><tr><td>230</td><td>0</td><td>962 ± 4</td><td>61.84 ± 0.92</td><td>62.82 ± 0.99</td><td>61.67 ± 1.58</td><td>6.76 ± 0.21</td></tr><tr><td>230</td><td>15</td><td>923 ± 45</td><td>56.97 ± 4.72</td><td>57.78 ± 5.58</td><td>56.56 ± 5.03</td><td>6.46 ± 0.73</td></tr><tr><td>230</td><td>30</td><td>864 ± 23</td><td>53.14 ± 5.75</td><td>54.97 ± 2.82</td><td>54.34 ± 2.59</td><td>6.35 ± 0.30</td></tr><tr><td>230</td><td>45</td><td>950 ± 8</td><td>60.26 ± 0.59</td><td>60.57 ± 0.67</td><td>58.77 ± 1.53</td><td>6.58 ± 0.06</td></tr></tbody></table>

rises by 5 %, with higher temperatures achieving 58 MPa compared to 55 MPa at lower temperatures. As reported by Toth et al. [26] for recycled PET, there is significant variation between the tensile strength of the filament (50 MPa) and the 3D printed parts (close to 30 MPa), which is not the case in this study. For all printing temperatures, the variation is as minor as 5 %.

Regardless of printing temperature, the printing angle has a more pronounced effect, with changes in engineering constants ranging between -2 % and -11 %. For instance, higher printing angles result in reduced stiffness (by 2 %), yield stress (by 6 %), tensile strength (by 7 %), rupture stress (by 5 %), and elongation at break (by 11 %). Compared to the relatively linear effect of printing temperature, the influence of the printing angle is nonlinear, with the best-performing conditions corresponding to angles below 30°. Compared to recycled PET, the tensile strength is significantly higher than the values reported in the literature, which range from 10 to 35 MPa [26,27]. The most comparable results to the present study were reported by Idrees et al. [28] for PET modified with biochar, where the tensile strength of neat PET is close to 40 MPa and reached a maximum of 52 MPa at a biochar content of 0.5 %. In terms of stiffness a wide variability is observed in the literature depending on the testing conditions [29] and PET grades, where Toth et al. [26] report a modulus of 2 GPa, whereas Idrees et al. [28] slightly above 0.5 GPa.

An automatic fitting routine, based on over 200 functions, was employed to establish correlations between the printing conditions and mechanical properties using a minimal set of fitting parameters.

$$ 
\begin{aligned}
E_Y(\text{MPa}) &= 752 + 0.91 \times T_P(\text{°C}) + 7.25 \times \theta(\text{°}) - 0.70 \times \theta(\text{°})^2 + 0.01 \times \theta(\text{°})^3 R^2 \\
&= 0.94
\end{aligned} 
\qquad (1) $$

$$ 
\begin{aligned}
\sigma_Y(\text{MPa}) &= 49 + 0.06 \times T_P(\text{°C}) + 0.53 \times \theta(\text{°}) - 0.05 \times \theta(\text{°})^2 + 0.001 \times \theta(\text{°})^3 R^2 \\
&= 0.81
\end{aligned} 
\qquad (2) $$

$$ 
\begin{aligned}
\sigma_T(\text{MPa}) &= 47 + 0.07 \times T_P(\text{°C}) + 0.56 \times \theta(\text{°}) - 0.06 \times \theta(\text{°})^2 + 0.01 \times \theta(\text{°})^3 R^2 \\
&= 0.82
\end{aligned} 
\qquad (3) $$

$$ 
\begin{aligned}
\sigma_R(\text{MPa}) &= 36 + 0.11 \times T_P(\text{°C}) + 0.50 \times \theta(\text{°}) - 0.05 \times \theta(\text{°})^2 + 0.01 \times \theta(\text{°})^3 R^2 \\
&= 0.78
\end{aligned} 
\qquad (4) $$

$$ 
\begin{aligned}
\varepsilon_R(\%) &= 8.56 - 0.01 \times T_P(\text{°C}) + 0.03 \times \theta(\text{°}) - 0.003 \times \theta(\text{°})^2 + 6 \times 10^{-5} \times \theta(\text{°})^3 R^2 \\
&= 0.74
\end{aligned} 
\qquad (5) $$

Where R² represents the correlation factor, which measures the strength and direction of the relationship between the mechanical properties and the printing angle. All correlation coefficients exceed 0.5, indicating a strong statistical relationship between the mechanical parameters and the printing angle. A detailed statistical analysis of these correlations is provided in the supplementary material (Table S1).

The analysis of the correlations between printing parameters and mechanical properties reveals that the observed nonlinearity is primarily influenced by the printing angle, which is the dominant factor. In comparison, the printing temperature plays a secondary role, with its associated positive coefficient indicating a linear positive effect on all mechanical properties, except for elongation at break.

Regarding the loss of mechanical properties caused by the printing process, a comparison between the as-received material and the most optimal printing condition reveals a modest 4 % reduction in tensile strength, alongside more significant losses of 18 % in stiffness and 17 % in elongation at break. However, the printing process has a beneficial impact on yield stress and ultimate properties, with improvements of 14 % and 4 %, respectively.

## 4.2. 3D microstructure of 3D printed PET composites

To gain deeper insights into the mechanical performance ranking of 3D-printed PETs, an analysis of the induced microstructure is conducted. Given the limited influence of printing temperature on the mechanical results, the focus is shifted to the impact of the printing angle.

Fig. 4 illustrates a comparison between orthogonal planes of 3D printed PET, employing printing angles of 0° and 90°. These perspectives are generated by combining consecutive tomograms along the specimen's height, with a typical Region of Interest measuring 4.0 × 10 × 4.7 mm. In Fig. 4a, the microstructure unveils significant characteristics related to process-induced porosity, a common occurrence in Fused Filament Fabrication (FFF). The segmentation successfully differentiates the PET phase and porosity, yielding two distinct Gaussian
<figure><img src="image_9.png" /><figcaption>Fig. 4. Comparison between the microstructure of 3D printed PET samples for two printing angles – orthogonal views: (a) θ = 0°, (a) θ = 45°.</figcaption></figure>

distributions in the grey-level histogram. A threshold of 143 is identified as the optimal compromise for both printing angles. Based on the segmented images, the porosity content is measured as a voxel count [30] according to the formula

$$f_{P}(\%) = \sum_{i,j,k=1}^{N_{X} \times N_{Y} \times N_{Z}} \left(1 - \left(\frac{g_{ijk}}{255}\right)\right) / (N_{X} \times N_{Y} \times N_{Z}) \quad (6)$$

Where $f_P$ is the porosity level, $N_X$, $N_Y$, $N_Z$ is the total number of voxels in X-, Y- and Z-directions. $g_{ijk}$ is the grey level associated to the voxel at the coordinates i,j,k. For each voxel, the grey level is either 255 corresponding to the solid phase or 0 for porosity.

The XY plane view accentuates key features of FFF, showcasing in-plane discontinuities associated with filament layup. However, these discontinuities are limited in extent, rendering the printing conditions outlined in Table 2 optimal for this material. The triangular pore morphology is consistent with the observations of Loskot et al. [31], who used a similar X-ray microtomography technique to investigate the porous structure of 3D-printed PETG. However, in their study, the porosity level was strongly influenced by the print speed, which varied between 20 and 100 mm/s.

For samples printed at a 0° angle (θ = 0°), two primary filament orientations, +45° and -45° relative to the sample's primary dimension

(length), emerge. The spatial distribution of process-induced porosity displays regular patterns with discernible preferred orientations corresponding to the chosen layups. Observations in the XY and YZ planes reveal two dominant porosity types: core porosity within the raster and porosity at the raster-frame interface. In addition to providing perspective views of the porous structure across the entire Region of Interest (ROI), surface porosity aligned with the building direction contributes to the sample's rough finishing surface, serving as an indicator of the construction direction. In the XY plane, this direction aligns with the Y-direction.

Fig. 4b displays analogous orthogonal perspectives of the 3D printed PET, this time utilizing a printing angle of 45°. The figure highlights a distinctive filament arrangement where half of the filaments within the core are fully aligned with the loading direction. Similar mesoscopic porosity is observed, and discerning its magnitude in comparison to the 0° printing angle is not immediately apparent. Similar to the previous case, process-induced porosity does not compromise the cohesion of the core structure. Porosity within the frame, formed by two filaments aligned with the specimen's primary direction, is barely detectable. Although necking would typically generate longitudinally oriented porosity, this effect is not clearly observed here. Additionally, a change in the tool trajectory near the specimen's edge introduces a deceleration that alters the lateral dimensions of the filaments. This alteration is
observable in the YZ views in both Fig. 4a and b.

Significant distinctions are noticeable in the morphology of porosities within the frame and the core of the specimen, as seen in the XY- and XZ-views. The former is a result of changes in filament orientation relative to the raster, while the latter is associated with filament crossings following the sequence imposed by the printing angle.

In order to achieve a quantification of the amount and distribution of process-induced porosity, the following image analysis processes are considered (Fig. 5a). Rotation and cropping at the main processes followed by the external flooding that allows separating the background from the process-induced porosity. For PET samples, this process proves effective due to the dense matrix and the limited connectivity of porosity, particularly between surface and core regions. The resulting segmented phases are further exploited in Fig. 5b. This figure shows perspective views of the porous structure for both printing angles (θ = 0°, θ = 45°). The porous structure follows the filament arrangement

according to the prescribed printing angle. Both printing angles induce a peripherical porosity at the frame, whose orientation is perpendicular with respect to the building direction. These porosities merge with the core porosities allowing a significant connectivity to take place. Within the core of the sample, the porous network is an alternation of -45°/+45°, 0°/+90° along the building direction for θ = 0°, θ = 45°, respectively. For a printing angle of 0°, the overall porosity level is 1.2 ± 0.02 %. For a printing angle of 45°, the overall porosity level is 1.6 ± 0.19 %. The standard deviation here reflects the jaggier trend of the 45° sample. These results contrast with the porosity content measured for 3D printed recycled PET [26], where typical level of 17 % are observed. In terms of porous structure, previous studies reported relatively high connectivity despite low porosity, a trend observed across several material types [32–34].

Fig. 6 shows orthogonal views of 3D printed PET according to intermediate printing angles of 15° and 30°. These angles correspond to

<figure><img src="image_10.png" /><figcaption>Fig. 5. (a) Main image analysis processes for identification of main microstructural features of 3D printed PET, (b) result of the process illustrated using perspective views for two extreme printing angles.</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>Fig. 6. Comparison between the microstructure of 3D printed PET samples for two intermediate printing angles – orthogonal views: (a) θ = 15°, (b) θ = 30°.</figcaption></figure>

layups of -30/+60° and -15°/+75°, respectively. Both angles exhibit the same qualitative features, including raster defects as well as characteristic aspects of the external frame and layering structure. However, a close examination of the porous structure reveals that a higher porosity content is observed especially for the printing angle 30°. The same segmentation processed on both samples shows that the overall porosity content is 1.4 ± 0.16 % and 2.1 ± 0.36 % for θ = 15°, and θ = 30°, respectively (Fig. 7a). This result suggests that θ = 30° is the worst printing condition as it promotes the highest amount of porosities. This outcome is linked to the in-plane layup mapping of -15°/+75°, which does not ensure sufficient space filling of the regular geometry, particularly in the gauge area. It qualitatively agrees with the mechanical results, which indicate low performance for this configuration. The optimal condition is θ = 0°, which allows the lowest amount of porosity. The correlation between the porosity content fP and the printing angle θ can be approached using a nonlinear function

$$f_P(\%) = 1.19 + 0.001 \times \theta(^{\circ})2 - 4.67 \times 10^{-20} \times \exp(\theta(^{\circ})) R^2 = 0.99 \quad (7)$$

The printing angle clearly exhibits a similar nonlinear effect on porosity content as it does on the mechanical properties. This indicates that the porous network formed during the printing process directly influences tensile performance. From a stiffness perspective, the amount of porosity has a direct impact on the overall Young’s modulus. For other mechanical parameters, such as elongation at break and tensile strength, further investigation into the characteristics of the porous network is necessary, including complementary microstructural attributes. For example, cracking behaviour may be associated with the connectivity of the pores.

3D labelling of all porosities (Fig. 7b) allows the quantification of the

connectivity according to the equation

$$\tau = 100 \times \text{MAX}(O_i) / \sum_{i=1}^{N_p} O_i \quad (8)$$

Where i is the label index of a porous cluster containing Oi voxels, Np is the number of independent porosities, i.e., porosities that do not share any voxel.

Pore connectivity is defined based on a 6-face connectivity model. Using this definition, 3D labelling of the entire 3D-printed PET samples reveals a connectivity of 3.0 % for θ = 0° and 9.8 % for θ = 45°. The higher connectivity observed at θ = 45° is attributed to larger filament segments aligned parallel and perpendicular to the longitudinal direction. Interestingly, the worst-performing printing configuration (θ = 30°) does not exhibit the highest pore connectivity, with a value of 4.7 ± 0.29 %, and the same applies to θ = 15° (pore connectivity of 1.4 ± 0.51 %). This discrepancy is related to differences in pore size distribution across printing conditions. results reported in this study can be considered in the low range compared to other materials. Indeed, pore connectivity is both material and printing condition dependent. For example, composite filaments such as PLA with iron oxide exhibit nearly full connectivity (~95 %) due to multi-scale porosity, including pores within the filaments themselves [33]. Filament such as polyamide which does not contain porosity within the filament can reach connectivity as large as 99 % [35], whereas for ABS it is close to 85 % [36].

Using 3D granulometry processing, the cumulative pore size distribution is plotted in Fig. 8. The results show a monomodal distribution trend, with an average pore size increasing from 34.6 ± 15.69 µm to 38.1 ± 15.22 µm. The entire distribution range remains below 200 µm.
<figure><img src="image_12.png" /><figcaption>Fig. 7. X-ray micro-tomography results for intermediate printing angles 15° and 30°: (a) Perspective views showing the surface texture and the porous network, (b) A close view on the morphology of porosity.</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>Fig. 8. Pore size distribution for 3D printed PET under various printing angles.</figcaption></figure>

Notably, $\theta = 30°$ exhibits the widest pore size distribution among all conditions, corroborating the observation that this configuration generates larger pores with lower connectivity compared to the other conditions.

Further analysis is conducted to evaluate the anisotropic spatial

distribution of process-induced porosity. Axial porosity profiles are examined for two extreme printing angles ($\theta = 0°$ and $\theta = 45°$). These profiles entail quantifying the black voxels related to the porosity phase in a specific direction, normalized with respect to the length, depth, or width, depending on the orientation of the sample. For instance, the porosity profile along the depth direction is determined as follows:

$$f_j(\%) = \frac{\sum_{i,k=1}^{D_x \times D_z} \delta(\gamma_{ijk})}{\mu(\gamma_{ijk})} \qquad (9)$$

Where $f_j$ represents the porosity level in the Y-direction at the jth position, specifically along the depth or construction direction ($D_x, D_z$ being the total number of voxels in the X- and Z-directions, corresponding to the height of the specimen). $\gamma_{ijk}$ denotes the grey level associated with the voxel at coordinates i, j, k. For each voxel, the grey level is either 255, corresponding to the PET phase, 128 for the background, or 0 for the porosity, $\delta$ and $\mu$ are functions of the form

$$\delta(\gamma_{ijk}) = \begin{cases} 1 & |\gamma_{ijk}| = 0 \\ 0 & |\gamma_{ijk}| > 0 \end{cases} \qquad (10)$$

and

$$\mu(\gamma_{ijk}) = \begin{cases} 1 & |\gamma_{ijk}| = \{0; 255\} \\ 0 & |\gamma_{ijk}| = 128 \end{cases} \qquad (11)$$

Fig. 9 offers more detailed quantitative information regarding porosity distribution through axial porosity profiles for contrasted
<figure><img src="image_14.png" /><figcaption>**Fig. 9.** Profiles illustrating axial porosity levels in 3D printed PET for two extreme printing angles 0° and 45° along (a) the length, (b) construction (depth) direction, and (c) width direction.</figcaption></figure>

printing angles 0° and 45°. In Fig. 9a, the outcomes of porosity profiles along the length direction are depicted. The overall porosity content remains minimal, with the highest peaks registering below 5 %, irrespective of the printing angle. The PET sample printed at a 45° angle displays elevated peaks, albeit with consistent variation. The peak-to-peak distance is approximately 600 µm, which can be directly linked

to the largest dimension of the elliptical cross-section of the filament.

Across the depth, notable peaks are apparent for both printing angles, even when the average porosity levels are comparable (Fig. 9b). The most prominent peaks are below 6 % (5.53 ± 0.19 %) for θ = 0°, while even higher porosity level peaks close to 6.09 ± 0.07 % are observed for θ = 45. All samples exhibit a consistent variation in porosity levels with a similar repeating trend. However, the periodicity of this trend is distinct, measuring 300 µm instead of 600 µm, corresponding to the layer height.

Porosity profiles across the specimen's width (Fig. 9c) highlight the presence of interfilament porosity within the external frame, as depicted in Fig. 4. The porosity reaches a maximum of approximately 7 %. Near the specimen's edges, low porosity levels suggest connectivity between the raster and the external frame. In the specimen's core, the sequencing produces a periodic filament arrangement, with gaps between adjacent filaments contributing to porosity levels as low as 0.5 %. Notably, the porous structure appears significantly jagged at a printing angle of 45°, whereas at 0°, the porosity trend is more consistent. Similar axial profiles are reported for other materials such as PLA composites [32,33,35].

Fig. 10 presents axial porosity profiles for intermediate printing angles of 15° and 30°. Along the specimen's length (Fig. 10a), the profiles exhibit more consistent and periodic patterns, with the 30° printing angle producing the highest peaks. While the peaks for the 30° angle are lower compared to those at 45°, the overall porosity level is significantly higher for the 30° printing angle as well as the ground levels which are above 1 %.

Across the depth (Fig. 10b), notable peaks are apparent for the printing angle 30°, which are the highest compared to all printing conditions. The porosity peak levels are significantly larger reaching almost 10 % (9.97 ± 0.18 %) for θ = 30°, while limited porosity peaks are obtained for θ = 15° (2.52 ± 0.00 %). These profiles show that high stress concentrations are expected to occur for 30° as a result of the alternation between high and low porosity levels across the depth of the specimen.

Porosity profiles across the specimen's width (Fig. 10c) highlight the same features such as interfilament porosity within the external frame. High peaks are attributed to the printing angle 30°, which is likely to promote the separation of the external frame due to the stress concentration that occurs within the junction between the core of the specimen and the frame. The porosity reaches maximums of 16 %, and evolves between 2 % and 5 % within the core of the specimen printed at 30°.

### 4.3. Finite element predictions

To further investigate the influence of the porous network in relation to printing angles, finite element computation results are analysed. These results involve the application of 3D microstructure models under elastic conditions to evaluate stress heterogeneity for each printing configuration.

Fig. 11 illustrates the displacement fields along the loading direction and the von Mises stress contour plots for all analysed printing angles. The displacement fields highlight key microstructural features, including filament orientation within the raster, the external frame, and the porosity network. These features are effectively captured with the selected voxel size of 30 µm. On a microstructural scale, stress heterogeneity highlights the influence of filament arrangement, particularly the variation in layering effects along the building direction, confirming cohesive layering.

The figure also demonstrates the impact of printing angle on the predicted von Mises stress (σ<sub>c</sub>) distribution. Computations were performed on as-acquired volumes with a displacement increment corresponding to a unit voxel size of 30 µm. Aside from stress concentrations at specimen edges, stress heterogeneity is primarily governed by the filament arrangement. The greatest stress variations occur at a printing angle of θ = 30°, which corresponds to the highest porosity levels. Conversely, the smallest stress variations are observed at θ = 45°, as seen
<figure><img src="image_15.png" /><figcaption>**Fig. 10.** Profiles illustrating axial porosity levels in 3D printed PET for two intermediate printing angles 15° and 30° along (a) the length, (b) construction (depth) direction, and (c) width direction.</figcaption></figure>

in the surface views provided in Fig. 11. The results are qualitatively consistent with several studies that employed direct conversion of X-ray microtomography data into finite element models [25,32,37]. For instance, Yang et al. [37] compared simulations based on CAD models and 3D images for lattice structures, concluding that stress concentrations strongly depend on defect morphology, an effect that cannot be captured using CAD models alone.

In terms of mechanical performance, the relative change in Young's modulus compared to the intrinsic value is predicted to be 8%, 19%, 25%,

and 5% for printing angles of 0°, 15°, 30°, and 45°, respectively. These predictions align qualitatively with experimental data, accurately ranking the printing conditions, with the lowest modulus corresponding to θ = 30°. However, the predictions do not account for localized stiffness variations due to incomplete filament adhesion or changes in crystallinity.

For example, experimental evidence shows the relative changes in Young's modulus compared to the reference condition (θ = 0°, regardless of printing temperature) are approximately 0%, -1%, -10%, and -2% for printing angles of 0°, 15°, 30°, and 45°, respectively. In contrast, the computational predictions yield values of 0%, -12%, -18%, and +3% for the same angles. While there is general qualitative agreement, discrepancies are notable for θ = 45°.

### 4.4. Demonstrator made of 3D printed PET

Fig. 12 presents a demonstrator of a bike bottle holder, 3D-printed using PET. This mount is specifically designed to securely hold water bottles equipped with a bite valve. The design occupies a cylindrical space measuring approximately 146 mm in height and 87 mm in diameter. The CAD model has been optimized to minimize material usage while maintaining sufficient mechanical performance and ensuring quick bottle access. The design's relative volume represents only 4.52% of the total design domain, with a total weight of 77 g and a wall thickness ranging from 4 to 7 mm.

The slicing process was carried out using IdeaMaker software, with the part oriented upright to ensure filament continuity along the circumference. This orientation is essential to withstand outward pressure but requires 31% additional support material. The printing parameters follow the conditions outlined in Table 2, with a modification to the external frame thickness, which was reduced to 0.6 mm. A printing angle of 0° was selected, and the volumetric speed was adjusted between 0.09 mm³/s and 10.8 mm³/s.

To balance energy efficiency and print quality, the printing temperature was set to an intermediate value of 210 °C. According to Table 3, increasing the temperature to 230 °C would only result in a 2% stiffness improvement while consuming an additional 35 Wh of energy, representing a 1.56% increase. This energy consumption was measured for a total printing time of 5 h and 49 min. Under these conditions, the 3D print was produced with a columnar support structure featuring a relative density of 0.3, as shown in Fig. 12. The figure also displays the final part after the removal of the support material, highlighting the clean and functional rendering of the bike bottle holder.

### 4.5. Discussion of main findings

Studies on the 3D printing of PET—particularly recycled PET [26,38] —have mainly focused on identifying the optimal printing temperature [38] as this parameter strongly influences the material's melt flow behaviour. For instance, Nikam et al. [38] considered a processing temperature between 220 °C and 240 °C, which overlaps with the temperature range considered in this study. This sensitivity to thermal conditions is even more pronounced in recycled PET due to its altered molecular structure and changed crystallinity behaviour [26]. Some researchers have expanded the search for optimal processing conditions to consider the combined effects of multiple parameters, such as printing temperature, layer height, infill density, and print speed [39]. Nevertheless, limited attention has been given to the filament orientation within the construction plane and its potential interdependence with other printing parameters. O'Driscoll et al. [39] reported tensile strengths ranging from 32 MPa to 37 MPa across a wide range of printing conditions, whereas in the present study, tensile strength reaches values as high as 62 MPa. More generally, and not exclusively in the PET literature, most prior studies have examined part orientation relative to the build direction [40], where for instance Nizam et al. [40] reported a 60% increase in the tensile strength of PLA when samples were printed
<figure><img src="image_16.png" /><figcaption>**Fig. 11.** Finite element results showing displacement component UZ field as well as von Mises stress counterplots for all printing angles. Loading is performed along the length of the specimens (Z-direction).</figcaption></figure>

in the lateral direction (16 MPa) compared to the vertical direction (10 MPa). Only a limited number of studies have explicitly considered filament orientation within the construction plane as a variable and quantified its influence on mechanical properties and porosity. Previous work by the present authors has demonstrated the critical importance of evaluating the proportion of filaments aligned with the loading direction—an aspect influenced both by part orientation and by how the filaments are arranged within the construction plane [41]. For a printing angle of 45°, corresponding to half of the filaments aligned with the loading direction, PLA reinforced with ceramics exhibits a maximum tensile strength of 39 MPa. In contrast, under the same printing angle, the present study reports a tensile strength of 61 MPa, which is not even the highest value observed across the range of printing conditions tested. The present work indicates that the filament orientation can result in variations in mechanical strength of up to 21 %. This marked influence of the filament orientation within the plane of construction with respect to the printing temperature further demonstrate the criticality of considering a multi-parameter optimisation approach as also considered by Kafshgar et al. [42] to optimize the mechanical performance of 3D printed polymers.

Although the printing temperature plays a crucial role in the polymer printability, there is a temperature range where the impact of the printing temperature on the mechanical performance is limited (Fig. 3). Additional criteria such as energy consumption should be considered to select the most suitable printing conditions. However, this criterion is not yet present in most control software. Energy consumption in additive manufacturing (AM) can be evaluated using several complementary approaches, each offering different levels of resolution and accuracy. A direct method involves real-time electrical measurements of the machine’s power draw using power meters or data acquisition systems, which can capture instantaneous consumption and identify process-specific peaks (e.g., during heating, laser operation, or motor action). This method is selected for this study using an AC 85–290V 3-phase 4 wire power energy meter with 0–23 kW range and RS485 communication (model KWS-306L from Yuyao Lianke Electronics company, China). Another approach is component-level monitoring, where individual subsystems such as heaters, motion control units, and cooling systems are instrumented separately to determine their specific contributions to total energy usage. This approach is for instance considered by S. Zakaria et al. [43] through a measurement box
<figure><img src="image_17.png" /><figcaption>Fig. 12. Design and fabrication of bike bottle holder using PET.</figcaption></figure>

consisting of eight current sensors.

The authors showed that heated bed operation accounts for 60–70 % of total energy use, making low bed temperature a key factor, along with high layer thickness and high printing speed, to minimize both printing time and energy demand. Indirect methods estimate energy consumption from process parameters [44] such as build time, layer thickness, scanning speed, or extrusion rate, combined with machine specifications, allowing for comparative studies without extensive instrumentation. More advanced strategies employ process modelling and life-cycle assessment (LCA) [45], integrating simulation data, machine efficiency factors, and material properties to predict energy demands across the entire production chain, from preheating to post-processing.

In terms of correlation between the printing parameters, namely the printing angle and the printing temperature, this study (equations (1)–(5)) shows that there statistically a strong correlation between the mechanical properties and the printing parameters. The literature review indicates that most prior studies have focused on part orientation, rather than on the filament orientation within the construction plane. This observation holds true across several additive manufacturing technologies, including UV light-based methods [46] and fused filament fabrication [40]. The optimisation of the printing parameters with respect to technical performance of 3D-printed parts is typically assessed through design of experiments, where ANOVA (Analysis of Variance) analysis is used to quantify the influence of process parameters on mechanical properties such as ultimate tensile strength, yield strength, modulus of elasticity, toughness, and elongation at break [42]. For example, Valvez et al. [25] applied ANOVA to optimize the printing parameters of PET-G-based feedstock materials. Their results indicated that the best

bending performance was achieved at a high printing temperature of 265 °C combined with a low printing speed of 20 mm/s. These analyses generally yield regression models fitted separately for each mechanical property [47]. In the present work, we extend this approach: instead of relying solely on linear correlations, we apply a fitting procedure across a broad range of candidate equations to better capture complex relationships. The selection of polynomial order and variables is guided primarily by an empirical fitting approach rather than a purely theoretical model, due to the complex and multi-factorial nature of the measured properties, for which no simple closed-form physical relationships are available. The polynomial orders are chosen after testing lower-order fits and evaluating statistical performance (R², residual analysis, etc, Table S1). Higher-order terms are retained only when they provided a statistically significant improvement in fit quality without introducing signs of overfitting.

Similarly, the same approach is applied, in this study, to quantify the relationship between porosity level and printing parameters (equation (6)). In fact, porosity is generally derived from apparent density measurement which only provide an overall estimation of the porosity content [26]. Using this method, Toth et al. [26] demonstrated that porosity in 3D-printed recycled PET can vary widely, ranging from 17 % to 27 %. In contrast, the present study reports a lower overall porosity (Equation (6)). Notably, the variation observed along the principal directions is substantial (Figs. 7–10). Previous studies have highlighted the complexity of process-induced defects in 3D printed polymers, which can be more accurately characterized using 3D imaging techniques such as X-ray microtomography [48,49]. The integration of porosity modeling using synchrotron X-ray micro-tomography is one of the current
tendencies to gain further insight on the influence of the printing pa-
rameters on the microstructural arrangement including for instance
density measurement, roughness evaluation, defect quantification, and
dimensional deviation as pointed out by Khosravani et al. [49].

The intricate arrangement of the porous structure calls for a more advanced porosity model. In the present work, the exponential term exp (θ) in Eq. (6) is introduced because exploratory data analysis revealed a strongly non-linear and asymmetric dependence on θ —behaviour that cannot be adequately captured by a polynomial alone. While the exact physical mechanism may not be straightforward to derive, the exponential form is consistent with phenomena where changes in angular orientation produce multiplicative effects on effective pore space. Therefore, the model form reflects a semi-empirical choice, informed by both observed data trends and plausibility in light of the underlying geometry of the filament arrangement within the construction plane.

Although microstructural characterization provides a detailed assessment of porosity and structural features, the influence of the induced microstructure on deformation mechanisms is highly relevant when integrating microstructural data into finite element simulations, as highlighted by several studies [50]. Our finite element results show that stress heterogeneity develops as a result of spatial arrangement of filaments. However, local stiffness variations due to incomplete interlayer bonding and crystallinity gradients in 3D-printed PET are not considered. Indeed, these are important factors that can influence both the effective modulus and the predicted stress fields in finite element models. The current FE model assumes uniform, isotropic elastic properties at the filament scale, without spatial variation in stiffness. However, studies on PET and other semicrystalline thermoplastics show that crystallinity is highly sensitive to thermal history, with pronounced effects on mechanical performance. [51,52]. Indeed, Mokhtari et al., [51] compared the crystallinity of injection-moulded PET at different processing stages, including as-received cylinders, tensile specimens, and annealed bars. They reported that crystallinity variations of up to 45 % can substantially influence the Young's modulus, with stiffness changes of up to 32 %. Aliberti et al. [52] showed that, in PET/PBT blends, increasing the PET content reduces the degree of crystallinity, which in turn impacts the elongation at break. Prediction of mechanical properties based on crystalline structure of PET has been the subject of several studies. For instance, Zarbali et al. [53] achieved a nonlinear relationship between crystallinity and young's modulus for PET, combining both experimental measurements and simulated values. Their results show that Young's modulus remains nearly constant (~2.5 GPa) at low crystallinity (below ~0.3) but increases sharply for crystallinities above 0.4, reaching ~12 GPa at full crystallinity. This non-linear increase indicates that the material's stiffness is highly sensitive to the development of crystalline order, particularly in the high-crystallinity range, where small increases in order result in substantial gains in modulus. When incorporating such crystallinity into a finite element (FE) model, two main approaches can be considered: (i) applying a correction to the material stiffness, or (ii) modelling at the relevant scale for polymer chain dynamics [54], as outlined by Zekriardehani et al. [55]. The first approach effectively introduces a global shift in the stress level but does not allow for a detailed representation of local stress heterogeneity. The second approach can more accurately capture this heterogeneity by explicitly accounting for chain mobility in both amorphous and crystalline phases. However, it requires a multi-physics model that includes the thermal effects associated with PET chemistry [56]. Such a model can also simulate the crystallization process, enabling quantification of the crystallization rate, particularly under rapid thermal cycling, as occurs in fused filament fabrication [57].

5. Conclusions

Based on the combination of experimental and numerical results, this
study provides microstructural interpretation about the mechanical
behaviour for 3D-printed PET under varying printing conditions. The

following key conclusions can be drawn:

* Printing angle significantly affect the tensile behaviour of 3D-printed PET. While temperature variations (200–230 °C) have a minor impact, improving stiffness (~3 %) and tensile strength (~5 %) but reducing elongation at break (~3 %), the printing angle exerts a more pronounced influence.

* Lower printing angles (θ ≤ 15°) enhance mechanical properties by reducing porosity and improving interfilament bonding. In contrast, higher angles (θ = 30°) promote higher porosity and stress heterogeneity, leading to the poorest mechanical performance.

* Process-induced porosity, influenced by printing angle and filament arrangement, is a key determinant of mechanical performance. The lowest porosity (1.2 % at θ = 0°) corresponds to optimal mechanical properties, while higher porosity levels (θ = 30° with 2.1 %) lead to reduced stiffness and tensile strength. For optimal results, printing angles below 30° should be prioritized, and intermediate temperatures should be used to balance energy consumption and mechanical properties.

* The computational model based on imbedding 3D microstructure in a quasi-elastic simulation accurately predict stress distribution and mechanical performance trends, aligning with experimental data. The poorest performance at θ = 30° is attributed to high porosity and stress concentration. Localized effects such as incomplete filament adhesion and changes in crystallinity require further investigation to refine predictive models.

* A bike bottle holder was successfully 3D-printed using PET, demonstrating the material's potential for structural applications. The optimized design used only 4.52 % of the design domain volume while maintaining functional integrity. The printing settings, including a 0° angle, intermediate temperature (210 °C), and upright orientation, achieved a balance between mechanical performance and energy efficiency, with support structures effectively removed in post-processing.

* In conclusion, this work emphasizes the critical role of microstructure, particularly porosity and filament arrangement, in determining the mechanical performance of 3D-printed PET. The findings provide a foundation for optimizing printing strategies to enhance the functionality and efficiency of PET components for practical applications.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This Research was funded by the French National Research Agency (ANR) through the project MAGNELIN4D ANR-22-CE10-0010. We acknowledge the European Synchrotron Radiation Facility ESRF for provision of beam time on BM05 beamline.

**Appendix A. Supplementary data**

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jmrt.2025.09.136.

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