<figure><img src="image_1.png" /></figure>

# Dielectric and viscoelastic properties of 3D-printed biobased materials

Morgan Lecouplet<sup>a, b, *</sup>, Mohamed Ragoubi<sup>a, **</sup>, Nathalie Leblanc<sup>a</sup>, Ahmed Koubaa<sup>b</sup>

<figure><img src="image_2.png" /></figure>

## ARTICLE INFO

**Keywords:**

3D printing

Dielectric analysis

Dynamic mechanical analysis

Polylactic acid

Cellulose acetate

Polymer blends

## ABSTRACT

This study aimed to develop new biobased materials containing plasticized cellulose acetate (CA) by Fused Filament Fabrication (FFF). We investigated the influence of CA on the viscoelastic/dielectric properties and the influence of 3D printing on the dielectric properties of the polymer blends. A microstructural analysis showed that the blends had a strong heterogeneous morphology, as the two phases formed a fibrillar and lamellar structure. CA strongly increased the blend viscosity at 175 °C, multiplying by 100 times the complex viscosity between neat PLA and the blend containing 40% of CA by weight (CA-40). The addition of CA to the blends increased the dielectric constant (ε') and dielectric loss (ε''), as well as the alternative current electrical conductivity (σ<sub>AC</sub>). The dielectric constant of CA (ε'<sub>CA</sub>) was proportional to its percentage in the blend, showing a behavior analogous to a rule of mixture. Moreover, the activation energy of the electrical conductivity (σ<sub>DC</sub>) measured at T > 124 °C decreased with increasing CA content and was associated with the enhancement of the ionic conductivity provided by the CA and its plasticizer. A decrease in the α-relaxation temperature and the associated activation energy of the PLA was also linked to the presence of the CA plasticizer. Finally, 3D printing greatly decreased both ε', ε'' and σ<sub>AC</sub> due to the internal voids induced by the 3D printing process. The porosity was measured at 12% for neat PLA and between 20% and 25% for the blends. These results showed the advantage provided by FFF technology in the production of PLA:CA blends with controlled dielectric properties, thereby favoring the use of these new materials in key dielectric areas.

## 1. Introduction

The dielectric field is vital in our daily lives, usually occupied by glass, wood, ceramics, and synthetic polymer-based composites (Khouaja et al., 2021; Yuan et al., 2022). Polymer-based composites, such as PVC, PE, and PP, with their excellent dielectric and electrical properties and processability, are indispensable in today's world. However, due to their harmful ecological impacts and the increasing scarcity of fossil resources, it is necessary to find replacements to ensure sustainable development. Recent reports aim to promote new biobased polymers (Jin et al., 2022; Pei et al., 2020; Spinelli et al., 2020). One of the most promising biobased polymers is cellulose acetate (CA).

CA is a cellulose ester derived from cellulose (Deshmukh et al., 2017), the largest available polymer stock in the world, with an estimated annual production of 1.5*10<sup>12</sup> tons (Liu and Sun, 2010). This family is defined by the substitution degree (D.S.) of the hydroxyl groups of the D-glucose unit of cellulose by acetyl groups (Assis et al., 2020).

The D.S. ranges from 0 (cellulose) to 3 (cellulose triacetate) and can be tuned to adjust the multiphysical properties of CA (De Freitas et al., 2017; Rubio-Valle et al., 2022). Once associated with a plasticizer, its simplicity of processing makes it suitable for many applications such as medical products, packaging, membranes, and synthetic fibers (Assis et al., 2020; Deshmukh et al., 2017). Deshmukh et al. (2017) proposed using CA/Al<sub>2</sub>O<sub>3</sub>-based bionanocomposites for the manufacturing of electronic devices, such as embedded passives. They obtained a dielectric constant (ε') of 27.5 with a weight content of Al<sub>2</sub>O<sub>3</sub> (W<sub>f</sub> Al<sub>2</sub>O<sub>3</sub>) of 25% in CA film, measured at 30 °C and 50 Hz. In addition, this material had a low dielectric loss (ε''), which makes it perfectly suited for applications in passive embedded printed circuit boards (PCB) requiring such performance levels.

The necessity of replacing synthetic matrices is an invaluable vector of innovation for material processing. 3D printing processes would be perfectly suited in this case. Fused Filament Fabrication (FFF) is the most common 3D printing technology. It is a promising and perfectly adapted

<footnote><sup>a</sup> UniLaSalle, Unité de Recherche Transformations et Agro-Ressources (ULR 7519 UniLaSalle – Université d'Artois), Mont-Saint-Aignan, France</footnote>

<footnote><sup>b</sup> UQAT, Campus de Rouyn-Noranda, 445, boul. de l'Université, Rouyn-Noranda, QC J9X 5E4, Canada</footnote>

<footnote>* Corresponding author at: UniLaSalle, Unité de Recherche Transformations et Agro-Ressources (ULR 7519 UniLaSalle – Université d'Artois), Mont-Saint-Aignan, France.</footnote>

<footnote>** Corresponding author.</footnote>

<footnote>E-mail addresses: morgan.lecoulet@unilasalle.fr (M. Lecoulet), mohamed.ragoubi@unilasalle.fr (M. Ragoubi).</footnote>
technology for the fast development of customizable, cheap, and thermoplastic structures for numerous applications (Bajwa et al., 2021; Zhou et al., 2022). During the FFF processing, the material filaments are fused in a heated nozzle, extruded, and deposited layer-by-layer to build physical models previously designed in CAD software (Bajwa et al., 2021; Bi et al., 2018). Spinelli et al. (2020) produced PLA nanocomposites filled with carbon nanotubes (CNT) and graphene nanoplatelets (GNP) using FFF technology to increase both electrical and thermal conductivity properties. At 100 Hz and a $W_f = 6\%$, the electrical conductivity of PLA was around 3 decades higher for CNT-based nanocomposites than for GNP-based ones, which was made possible by the CNT form factor, favoring the percolation point of CNT-based nanocomposites. Kuzmanić et al. (2023) evaluated the dielectric properties of 3D-printed PLA parts and the processing parameters influencing the dielectric properties. They showed that the infill ratio plays a key role in the dielectric constant, going from 1.78 to 2.81 for an infill ratio of 33% and 100%, respectively. This result shows the possibility of controlling the dielectric constant using keen material design. Concerning the use of cellulose acetate through the 3D printing process, the majority of literature relies on inkjet technology. By using the FFF technology, plasticized cellulose acetate propionate (CAP) samples, a cellulose ester, have been successfully produced (Immonen et al., 2021). The research team noted the potential of cellulose esters for 3D processing, while also pointing out the problems of layer adhesion in the case of an excessive plasticizer content. For applications in electronics, cellulose acetate has been used in conjunction with acrylonitrile butadiene styrene (ABS) and graphite for electrode design using FFF technology (Amorim et al., 2022). The authors reported that the addition of CA enhanced the electroactive surface area and heterogeneous electron transfer rate constant of the electrodes, demonstrating the potential of combining cellulose acetate and 3D printing for electronic devices.

Even if CA is a promising biobased polymer for electronic applications, its application by FFF technology is still largely undeveloped. To further investigate such materials, this study proposes the dielectric and viscoelastic investigation of CA-based materials produced by FFF technology. To facilitate the processing, PLA was chosen as a co-matrix for 3D printing because of its wide availability and good 3D printing capacity. The originality of this work is multiple, as it proposes to study the influence of CA content and the 3D printing process on the dielectric, dynamic mechanical and rheological properties of CA-based polymer blends, which has not yet been performed as far as we know. This combined properties study will help to investigate the potential of such 3D-printed materials to promote the integration of biobased materials in the dielectric field.

## 2. Materials and methods

### 2.1. Raw materials

Natureplast (Caen, FRA) and EURL BBFil (Heiligenberg, FRA) supplied the ACI 002 plasticized cellulose acetate (CA) and the Ingeo 2003D polylactic acid (PLA), respectively. The PLA presented a D-lactic acid content of 4.5%. All biobased polymers were 4 mm diameter in 25 kg bags. According to the suppliers, the CA had a plasticizer content of 29% and the PLA had a Melt Flow Index of $7 g·10 min^{-1}$ at 190 °C and 2.16 kg.

### 2.2. Sample preparation

A total of 4 different blends were produced with different CA content by mass ($W_{CA}$). The 4 blends were named CA-10, CA-20, CA-30, and CA-40 and possessed a $W_{CA}$ of respectively 10, 20, 30 and 40%. Neat PLA was also added and used as a reference. The first processing step was the blending via extrusion. Pellets were dried in an oven at 60 °C overnight to ensure a perfectly dry state to avoid the effect of high moisture on CA processing. A SCAMEX 25-20D (SCAMEX, Isques, FRA) single screw

extruder was used, with a temperature profile of 160-170-180 °C and a screw speed of 30 rounds per minute (RPM), as determined by preliminary tests. The filament-making step was carried out with a 3DEVO filament maker (3DEVO, Utrecht, NLD) with a temperature profile of 170-180-180-170 °C and a screw speed of 5 RPM. The resulting filaments had a $2.85 \pm 0.1$ mm diameter. This diameter was a compromise between size stability and filament quality. Filaments were stored at 60 °C in an oven before being processed by a SIGMAX R19 3D printer (BCN3D, Gavà, ESP). The UltiMaker Cura slicer was used, and the printing parameters are shown in Table 1. All produced conditions used the same printing parameters with the exception of the infill pattern. The Fig. 1 presents the produced samples for BDS and DMA samples. Overall, all samples achieved good quality, with no warping or cracking effects. Only CA-30 and CA-40 required the use of glue stick on the glass bed to increase adhesion.

Reference specimens were produced by hot-pressing with a Scamex 20 T 300×300 press (SCAMEX, Isques, FRA) at 180 °C, with a processing time of 2 minutes, and a mold pressure of 2.5 bars. The hot-pressed samples were cut with an ML-W1290 150 W laser cutter (MLlaser, Pont-à-Mousson, FRA). A laser power of 30% and a speed of $30 mm·s^{-1}$ was sufficient to cut the samples without degradation nor distortion. Moreover, for the dielectric analysis, a neat CA, named CA-100, was also prepared by hot-press. All samples were stored in a desiccator during 3 h before being characterized.

### 2.3. Blend characterization

#### 2.3.1. Scanning electronic microscopy (SEM) analysis

SEM analysis was performed with a Jeol JSM IT200 (Jeol, Akishima, JAP) to characterize the microstructure of the blends. Tests were carried out on specimens obtained by hot-press. A cryofracture with liquid nitrogen was carried out to obtain a clean cross-section, and the selected specimens were all carbon-coated. Tests were made at 15 kV with a magnification of x200.

#### 2.3.2. Rheological analysis

The dynamic rheological tests were conducted on an MCR 102 plane rheometer (Anton Paar, Graz, AUT) to characterize the viscoelastic behavior of the hot-pressed samples in the melt state. Disc samples with a diameter of 25 mm and a thickness of 1.5 mm were first stored in an oven at 60 °C to ensure a perfectly humidity-free state. During the test, they were subjected to a temperature of 175 °C under nitrogen. All tests were performed in the Linear Viscoelastic Range (LVE) and with a shear rate range between $0.1 \text{ and } 628 \text{ rad·s}^{-1}$.

#### 2.3.3. Broadband dielectric spectroscopy (BDS) analysis

Two BDS tests were conducted with an E4980A Precision LCR Meter (Keysight, Santa Rosa, USA) on the hot-pressed samples and 3D-printed samples. An isothermal test at 20 °C with a frequency ranging from $1 \cdot 10^2$ and $2 \cdot 10^6$ Hz with 20 measurements per decade was used to get the dielectric properties at room temperature. A test from 0 °C to 160 °C with 4 °C steps and a frequency ranging of $1 \cdot 10^2$ to $1 \cdot 10^6$ Hz with 10

<table><caption>**Table 1**
3D printing parameters.</caption><thead><tr><td>Parameters</td><td>Values</td></tr></thead><tbody><tr><td>Nozzle temperature</td><td>215 °C</td></tr><tr><td>Nozzle diameter</td><td>0.6 mm</td></tr><tr><td>Printing speed</td><td>30 mm·s<sup>-1</sup></td></tr><tr><td>Bed temperature</td><td>60 °C</td></tr><tr><td>Sample thickness</td><td>~ 2 mm</td></tr><tr><td>Layers</td><td>14</td></tr><tr><td>Layer thickness</td><td>0.15 mm</td></tr><tr><td>Infill density</td><td>100%</td></tr><tr><td>Infill pattern (BDS)</td><td>Concentric</td></tr><tr><td>Infill pattern (DMA)</td><td>± 45</td></tr></tbody></table>
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** 3D-printed PLA and CA-40 samples. Disk-shaped specimens are used for BDS analysis and rectangular shaped specimens are used for DMA analysis.</figcaption></figure>

measurements per decade were conducted to get the dielectric behavior vs temperature of the samples. All samples, 3D-printed or hot-pressed, were disk-shaped with a 25 mm diameter and 2 mm thickness. The dielectric constant (ε'), dielectric loss (ε''), A.C. conductivity (σAC) and D.C. conductivity (σDC) were determined according to Benabed and Seghier (2015). The activation energy E_a of the conductivity was calculated by applying an Arrhenius model proposed by Ziemath et al. (2017). The T_g determined by BDS was based on the research of Dichtl et al. (2017), with an application of the Havrilak-Negami (HN) model, followed by a Vogel-Fulcher-Tamman (VFT) fit to obtain the final relaxation temperature associated with the α-relaxation of PLA.

### 2.3.4. Dynamic mechanical analysis (DMA)

Hot-pressed samples and 3D-printed samples of 60×10×2mm were tested on a DMA 242 E Artemis (Netschz, Selb, DEU) in double cantilever mode to obtain the viscoelastic behavior of the blends in the solid state. The dual cantilever mode was chosen instead of the 3-point bending mode because of the very low stiffness of PLA once its glass transition temperature is reached (T > 60 °C). The tests were conducted in ramp mode between 30 and 140 °C with a heating rate of 5 °C·min⁻¹, a monitored force of 1 N and a frequency of 1 Hz.

### 2.3.5. Determination of the porosity content of the samples

To determine the porosity in the samples, a method derived from the measured permittivity was used:

$$ Porosity_{(ε)}(\%) = 100 - \left( \frac{ε_{xp} - ε_{air}}{ε_{th} - ε_{air}} \right) * 100 \quad (1) $$

Where εxp corresponds to the measured dielectric constant of the sample; εth corresponds to the theoretical dielectric constant; εair corresponds to the permittivity of the air filling the voids. In this case, εair was assumed to be equal to 1. Moreover, since a first-order model between dielectric constant and CA content has been demonstrated, εth can be derived from a rule of mixture:

$$ ε_{th} = ε_{PLA} * \frac{(100 - w_{CA})}{100} + ε_{CA} * \frac{w_{CA}}{100} \quad (2) $$

Where WCA corresponds to the weight content of CA; εPLA corresponds to the dielectric constant of hot-pressed PLA (found at 2.92); εCA corresponds to the dielectric constant of hot-pressed CA (found at 4.20). This method of determining the porosity will be compared to the method derived from the density and given by:

$$ Porosity_{(d)}(\%) = 100 - \frac{w}{d_{th}} * 100 \quad (3) $$

Where w is the mass of the sample in grams, V is the volume of the sample in cm³, and dth is the theoretical density. The specimens being discs of 25 mm in diameter, the porosity can be simplified as:

$$ Porosity_{(d)}(\%) = 100 - \frac{w}{d_{pyc}} * 100 \quad (4) $$

Where l is the thickness of the sample in cm, dpyc is the density of the blends and was calculated by a pycnometer analysis of the 3D-printing filaments. Densities were found between 1.2605 and 1.2877 (Table 2).

## 3. Results and discussions

### 3.1. Microstructural analysis

Fig. 2 shows the SEM images of all tested samples. As expected, PLA had a smooth surface. However, the incorporation of CA into PLA dramatically increased the system's heterogeneity. The roughness of the cryo-fractured cross-sections also increased with the addition of CA. The two phases are visible, as the blends were incompatible. Moreover, the system presents a lamellar and fibrillar-like morphology.

Fig. 3a) presents the variation in complex viscosity of hot-pressed PLA and PLA:CA blends as a function of frequency. Neat PLA and all the blends tested had a shear-thinning behavior. When the complex viscosity decreased, the shear rate increased. Neat PLA presented a Newtonian plateau at f < 1 rad·s⁻¹, where the viscosity is independent of shear rate and named zero-shear viscosity (η₀). By applying a Cross model (Volpe et al., 2018), the shear-independent viscosity η₀ was determined for PLA at 3060 Pa·s. Increasing the CA content from 0% to 40% at a 1 rad·s⁻¹ shear rate increased the complex viscosity by 248 times. CA-10 and CA-20, as for PLA, had a flattening shoulder in their curves around 100 rad·s⁻¹, tending towards a Newtonian plateau. Another shoulder was observed around 5 rad·s⁻¹ and the viscosity increased exponentially towards low frequencies. The complex viscosity of CA-30 and CA-40 blends were very frequency dependent as they did not exhibit inflections in the tested frequency range. A simple power law curve was perfectly fitted for CA-30 and CA-40, y=2.514*10⁵ X⁻⁰.⁶⁵⁶ and y=7312*10⁵ X⁻⁰.⁷⁰⁶, respectively, with X being the shear rate in s⁻¹. Their respective coefficients of determination (r²) were 0.997 and 0.999. Fig. 3b) shows a close-up at high frequency of the previously mentioned curves and their associated power law. This zoom was performed at frequencies f > 100 s⁻¹, a shear rate range similar to the 3D processing. It is important to know the material behavior under a high shear rate to predict its printability (Ding et al., 2023; Gunduz et al., 2018). The five blends clearly showed a perfect power law fit with a good coefficient of determination (r² > 0.995). Both models' exponents and coefficients increased as expected with the addition of CA. Moreover, at 628 rad·s⁻¹, the addition of CA increased under a first-order fit to the complex viscosity of the blends (Fig. 3c). This behavior permitted the reliable prediction of the viscosity of all blends at 175 °C. Fig. 3d) shows the complex modulus G* as a function of the complex viscosity η*. According to Wang et al. (2017), this curve provides information about the flow behavior of fluids. The PLA showed a well-defined Newtonian plateau and present at low G*. The addition of CA, however, made the Newtonian plateau disappear, and the ensuing curve became steeper, a complex viscosity trend also observed by Coltelli et al. (2021). This increase in viscosity may be due to the rigidity of the cellulosic unit of the CA (Zhang et al., 2023), thereby restricting the mobility of PLA and, therefore, of the associated blends. Moreover, in a previously published work, we demonstrated that the PLA and CA blends showed interactions

<table><caption>**Table 2**

Densities measured by pycnometer analysis for the hot-pressed samples.</caption><thead><tr><th></th><th>PLA</th><th>CA-10</th><th>CA-20</th><th>CA-30</th><th>CA-40</th></tr></thead><tbody><tr><th>Density</th><td>1.2605</td><td>1.2689</td><td>1.2742</td><td>1.2848</td><td>1.2877</td></tr></tbody></table>
<figure><img src="image_4.png" /><figcaption>Fig. 2. SEM analysis of a) PLA, b) CA-10, c) CA-20, d) CA-30, e) CA-40 at x200.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>Fig. 3. a) Complex viscosity versus frequency of hot-pressed samples of PLA and CA:PLA blends, b) Zoom on high shear rate and their associated power law fit, c) log(complex viscosity η*) versus CA content measured at 631 rad·s⁻¹ and the associated first-order fit, d) Complex viscosity η* versus complex modulus G*.</figcaption></figure>
between the hydroxyl functions of CA and the carbonyl functions of PLA (Lecoubllet et al., 2023). These interactions also hindered and increased the viscosity of the associated blends. These types of interactions between PLA and CA were also reported by El Assimi et al. (2021). This higher viscosity could explain the need to use adhesives to improve adhesion, since a viscous material, combined with a lower PLA content in the blends, does not adhere properly on the glass bed. Another hypothesis suggested by Immonen et al. (2021), suggested an excessive plasticizer content in the blend. However, despite a complex viscosity between 20 and 1000 times higher than neat PLA, CA-40 was successfully produced by 3D printing. This may be due to the combined effect of the shear-thinning properties of the blends and the high shear rate process induced by the 3D printing process, which mitigates the high viscosity of PLA:CA blends.

## 3.2. Dielectric analysis

Fig. 4 presents the dielectric constant $ε'$ of hot-pressed and 3D-printed blends at 20 °C. All the specimens had $ε'$ between 2.5 and 3.5, which corresponds to the expected behavior of a low-permittive polymer. The highest $ε'$ was observed for the hot-pressed CA-40 and the lowest for the 3D-printed CA-10. However, all the curves had the same decreasing trend in their dielectric constant with increasing frequency. For example, at 100 Hz, $ε'$ of the hot-pressed PLA was 3.32 and decreased to 3.16 at a frequency of 2 MHz, representing a 5% decrease in the material response to the applied electrical field. Wang and Yang (2023) argued that dipolar polarization cannot follow the AC voltage shift, which leads to a continuous decrease in the dielectric constant. All the tested samples showed a larger decrease at $f > 10^6$ Hz, which could be due to the upper measuring limit of the equipment used. A linear-like increase in the dielectric constant with the addition of CA was observed for the hot-pressed specimens due to the higher polar aspect of CA. However, for the 3D-printed specimens, CA-10 had a lower $ε'$ than PLA and CA-40 had higher values than CA-10, showing that an interference phenomenon hindered the linear increase in the dielectric constant with the addition of CA in hot-pressed samples. Moreover, a 20% decrease in the dielectric constant was observed for the 3D-printed blends compared to the hot-pressed blends.

Fig. 5 presents the dielectric loss ($ε''$) of hot-pressed and 3D-printed blends at 20 °C. The dielectric loss represents the part of the electromagnetic energy absorbed by the material and converted into heat. It is a physical quantity that must be kept low to improve the durability of thermally sensitive biobased materials for use in the field of dielectrics. For the tested samples, the lowest dielectric losses were obtained for the hot-pressed PLA and the 3D-printed CA-10, and the highest dielectric loss was observed for the hot-pressed CA-40. At 1 kHz, the 3D-printed

PLA presented an $ε''$ of $1.06*10^{-2}$ and the 3D-printed CA-40 presented an $ε''$ of $1.83*10^{-2}$. The dielectric loss increased with increasing frequency for all blends, which can be associated with the presence of the β-relaxation of PLA (Badia et al., 2014). The 3D-printed specimens showed a significant increase in $ε''$ toward frequencies $> 10^6$ Hz, with a more pronounced behavior for the PLA-rich specimens. Here again, 3D printing decreased the dielectric loss and the addition of CA increased this dielectric loss for all blends.

Table 3 presents the calculated conductivity $σ_{AC}$ of hot-pressed and 3D-printed blends at 20 °C. The highest $σ_{AC}$ was measured for hot-pressed CA-40 at $1.38*10^{-12} \text{ S·cm}^{-1}$ and the lowest for 3D-printed PLA at $4.37*10^{-13} \text{ S·cm}^{-1}$, both measured at 100 Hz. At 20 °C, the $σ_{AC}$ conductivity values of PLA were consistent with those reported by Fal et al. (2021). We found that, overall, conductivity increased with increasing frequency. This increase was steady for all the tested blends and processes. For example, the 3D-printed PLA's conductivity increased by 25600 between 100 Hz and 1 MHz. The frequency increase favors the hopping carrier phenomenon, conveying the electrical current in the insulating materials. This purely frequency-dependent behavior has been associated with an insulating material's behavior (Wu et al., 2019). An improvement in the electrical insulation behavior of 3D-printed samples has been observed. This phenomenon may be associated with the presence of interfaces between layers, which can generate boundary zones for electron flow and, consequently, limit electrical conductivity (Yang et al., 2019). An increase in the electrical sensitivity of the blends with the addition of CA were also observed. Blends with CA showed a slightly more conductive character than neat PLA. This behavior could be associated with the more polar nature of CA and the plasticizer improving the mobility of the carrier charges (Badara et al., 2011). Moreover, Table 3 shows that no electrical percolation point was present, even at $W_{CA} = 40\%$, attesting to the electrical insulating nature of these materials. The conductivity values were in the electrically insulating range noted by Solazzo et al. (2019), which also suggests that the proposed materials are suitable for the electrical insulation field.

To better understand the effect of CA on the dielectric constants of blends, Fig. 6a) shows the dielectric constant of the hot-pressed samples at 20 °C and 100 Hz vs CA content. The dielectric constant of CA-100 was added to the graph to improve the fitting of the associated model. At 100 Hz and 20 °C, CA-100 had a dielectric constant of 4.21, a similar value to those observed by Saad et al. (1992). Furthermore, under these measurement conditions, the PLA possessed a dielectric constant of 2.91, a value also reported in the literature (Badia et al., 2017; Cao et al., 2014). The variation of $ε'$ when CA was incorporated perfectly matched a first-order fit with an associated equation of $0.01296 X + 2.8994$, with X being the percent $W_{CA}$. With the $r^2$ being higher than 0.995, we can

<figure><img src="image_6.png" /><figcaption>Fig. 4. Dielectric constant $ε'$ versus frequency of a) hot-pressed samples, b) 3D-printed samples. 3D-printed PLA and CA-20 curves are overlapping.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Fig. 5. Dielectric loss ε'' versus frequency of a) hot-pressed samples, b) 3D-printed samples.</figcaption></figure>

<table><caption>**Table 3**

Electrical conductivity of hot-pressed and 3D-printed samples @ 20 °C.</caption><thead><tr><th>Frequency (Hz)</th><th></th><th>100</th><th>1 k</th><th>10 k</th><th>100 k</th><th>1 M</th></tr></thead><tbody><tr><td rowspan="5">Conductivity (S·cm<sup>-1</sup>)</td><td rowspan="5">Hot-pressed samples</td><td>PLA</td><td>7.59*10<sup>-13</sup></td><td>6.17*10<sup>-12</sup></td><td>8.71*10<sup>-11</sup></td><td>1.02*10<sup>-9</sup></td><td>1.07*10<sup>-8</sup></td></tr><tr><td>CA-10</td><td>9.55*10<sup>-13</sup></td><td>8.51*10<sup>-12</sup></td><td>1.17*10<sup>-10</sup></td><td>1.38*10<sup>-9</sup></td><td>1.51*10<sup>-8</sup></td></tr><tr><td>CA-20</td><td>9.12*10<sup>-13</sup></td><td>1.00*10<sup>-11</sup></td><td>1.35*10<sup>-10</sup></td><td>1.55*10<sup>-9</sup></td><td>1.62*10<sup>-8</sup></td></tr><tr><td>CA-30</td><td>7.24*10<sup>-13</sup></td><td>1.07*10<sup>-11</sup></td><td>1.51*10<sup>-10</sup></td><td>1.78*10<sup>-9</sup></td><td>2.24*10<sup>-8</sup></td></tr><tr><td>CA-40</td><td>1.38*10<sup>-12</sup></td><td>1.70*10<sup>-11</sup></td><td>2.24*10<sup>-10</sup></td><td>2.75*10<sup>-9</sup></td><td>4.37*10<sup>-8</sup></td></tr><tr><td rowspan="5">Conductivity (S·cm<sup>-1</sup>)</td><td rowspan="5">3D-printed samples</td><td>PLA</td><td>4.37*10<sup>-13</sup></td><td>5.62*10<sup>-12</sup></td><td>7.59*10<sup>-11</sup></td><td>8.91*10<sup>-10</sup></td><td>1.12*10<sup>-8</sup></td></tr><tr><td>CA-10</td><td>5.25*10<sup>-13</sup></td><td>5.13*10<sup>-12</sup></td><td>6.92*10<sup>-11</sup></td><td>7.94*10<sup>-10</sup></td><td>1.00*10<sup>-8</sup></td></tr><tr><td>CA-20</td><td>6.03*10<sup>-13</sup></td><td>6.46*10<sup>-12</sup></td><td>8.71*10<sup>-11</sup></td><td>9.77*10<sup>-10</sup></td><td>1.17*10<sup>-8</sup></td></tr><tr><td>CA-30</td><td>5.75*10<sup>-13</sup></td><td>7.76*10<sup>-12</sup></td><td>1.00*10<sup>-10</sup></td><td>1.12*10<sup>-9</sup></td><td>1.35*10<sup>-8</sup></td></tr><tr><td>CA-40</td><td>7.41*10<sup>-13</sup></td><td>1.15*10<sup>-11</sup></td><td>1.48*10<sup>-10</sup></td><td>1.70*10<sup>-9</sup></td><td>2.00*10<sup>-8</sup></td></tr></tbody></table>

<figure><img src="image_8.png" /><figcaption>Fig. 6. a) Dielectric constant VS CA content at 100 Hz. Error bars represent the standard deviation. b) log (D.C. conductivity) versus temperature and c) activation energy of electrical conductivity VS CA content. First-order fits are shown in all figures.</figcaption></figure>

assume that the PLA:CA blends followed the rule of mixtures. The isothermal-step BDS analysis also provided the direct current (D.C.) conductivity $\sigma_{DC}$ of the blends between 124 and 160 °C. Fig. 6b) shows the $\sigma_{DC}$ of PLA and CA-40 as a function of temperature. As expected, $\sigma_{DC}$ PLA and $\sigma_{DC}$ CA-40 increased with temperature. This increase in temperature was directly linked to the free volume of the polymers caused by an increase in the segmental chain motion and to the thermal expansion of polymers, which facilitates ionic mobility and the mobility of the polymeric segments (AlFannakh and Ibrahim, 2022). At 124°C, the $\sigma_{DC}$

PLA and $\sigma_{DC}$ CA-40 was 7.95*10⁻¹³ and 1.02*10⁻¹¹ S·cm⁻¹, respectively. The $\sigma_{DC}$ of CA-40 was 13 times higher than for neat PLA, which is consistent with the observed behavior of $\sigma_{AC}$ at 20 °C. However, at 160 °C, the behavior changed, and the $\sigma_{DC}$ PLA was 85% higher than $\sigma_{DC}$ CA-40. The $\sigma_{DC}$ was less temperature dependent for CA-40 than for PLA. This observation could be related to the rheological observations; the addition of CA greatly restricted PLA mobility and thus limited the creation of free volumes. Fig. 6c) shows the activation energy (Eₐ) of conductivity as a function of the blends. Activation energy decreased
linearly from 2.32 to 0.87 eV with increasing amounts of CA. This activation energy decrease could also be linked to the more polar nature of CA and with the plasticizer improving the mobility of the carrier charges.

### 3.3. Relationship between porosity and permittivity

To quantify the dielectric properties variation observed, Table 4 presents the dielectric constants (ε'), dielectric losses (ε''), and A.C. conductivity (σAC) measured at 20 °C and 1 kHz for hot-pressed and 3D-printed specimens, as well as the observed decrease between the two. The dielectric constants of 3D-printed PLA were similar to that observed in the literature (Dichtl et al., 2017; Kuzmanić et al., 2023). The smallest decrease was observed for the PLA ε'' at -1.2%, and the largest was observed for the CA-40 ε'' at -41.7%. The ε'' and σAC quantities were very sensitive to the printing process compared to the ε'. PLA showed only small variations in its values, under 10%, while all blends showed much higher property decreases. Finally, no clear relationship between CA content and observed decreases was noted.

A key notion to consider in 3D printing is the creation of internal defects in the printed specimens, called voids. These defects occur as a result of an inability of the filament to fill its given space which causes a triangle-shaped void between two deposited filaments (Fig. 7a)). A direct link has already been established between the porosity and permittivity (Goulas et al., 2019; Kuzmanić et al., 2023). The calculated porosities of the 3D-printed samples are presented in Fig. 7b). All measured porosities of the samples were globally between 12% and 23%. The lowest porosity observed, 12.5%, was for PLA, which is logical for a neat material and agreed with the results obtained by (Liao et al., 2019) for 3D-printed PLA. CA-20 had the highest porosities at approximately 23%. Adding CA up to a WCA = 20% greatly increased the porosity, with a P-Value for the density-derived porosity and the permittivity-derived porosity of respectively 1.12*10⁻⁹ and 4.13*10⁻⁶. The increase in porosity observed with CA content up to 20% can be linked to the complex viscosity results presented. A less viscous material can better fit and fill the free space than a more viscous material. After peaking for CA-20 blends, the porosity of 3D-printed samples decreased slightly for higher CA contents, with P-values of 5.82*10⁻⁴ and 1.17*10⁻² for the derived density measurement and derived permittivity measurement, respectively. Note, also, that the two methods gave comparable porosity measurements, with P-Values above 0.4. This observation validated the use of BDS analysis to determine the porosity of 3D printed samples. It also showed that it is possible to control the permittivity of the 3D-printed system by controlling the internal porosity. This parameter can easily be tuned by varying the infill ratio. The much higher porosity of CA-10 compared to PLA seemed to be the reason for the lower dielectric properties shown in Figs. 4 and 5.

### 3.4. DMA analysis

Figs. 8 and 9 present, respectively, the storage modulus (E') and the loss modulus (E') of hot-pressed and 3D-printed blends. At 30 °C, the highest moduli were reported for neat PLA and the lowest for CA-40. At

30 °C, the 3D-printed PLA presented a storage modulus of 1.81 GPa. All blends showed the same general behavior as a function of temperature. At low temperatures (< 40 °C), all the samples showed a storage modulus > 1 GPa and a relatively low loss modulus. This behavior is typical of the glassy state, where the mobility-limited macromolecules produced good stiffness properties and low-temperature dependencies. A sharp drop of E' and E'' peak were observed for all blends, between 40 and 70 °C, depending on the blend. This behavior is typical of the α-relaxation of PLA, shifting from a glassy state to a rubbery state (Ding et al., 2023). The incorporation of CA tended to decrease the modulus drop and the E'' peak, as well as widening the peak. A collective drop of storage and loss moduli was observed between 60 and 90 °C, depending on the blend. This can be attributed to the rubbery state of PLA. It is also worth noting that the E' and E'' drop was lower for the high CA content specimens. An increase in both storage and loss moduli was visible between 80 and 100 °C, depending on the blend. This behavior is well reported in the literature and is associated with the cold crystallization relaxation of PLA. The thermal energy was high enough for PLA to rearrange into a crystalline network. This decreases the entropy by forming a crystalline network, logically increasing the material stiffness. Between 100 and 130 °C, depending on the blend, a second rubbery state was observed, characterized, however, by a more rigid state than the first rubbery state due to the newly formed crystalline network. Finally, towards temperatures > 130 °C, a last inflection of E' and E'' was observed, which was associated with the beginning of fusion of the previously formed crystal lattice of PLA. This drop was more pronounced for high-CA content blends. The effect of 3D printing on mechanical properties was less clear than for the dielectric properties. However, the 3D-printed specimens showed higher storage moduli in the first rubbery state than the hot-pressed specimens. This observation was even more pronounced for low CA-content blends. This could be due to the 3D-printing process, which induced a greater macromolecular orientation on the deposition axis (Park et al., 2022) and could decrease the stiffness drop in the rubbery state (Young, 1989). The addition of CA to PLA decreased the energy required for the relaxations (Tg, Tcc, and Tm) and decreased their respective temperature. This probably comes from the presence of the plasticizer in CA, which also impacts PLA. Also, once the Tg is reached, the CA acts as a stiffener for the PLA in the rubbery state. For the 3D-printed specimens in the first rubbery state (60 < T < 90 °C), the minimum E' PLA was 4.04 MPa, and the E' CA-40 was 68.33 MPa, i.e., 12 times higher.

CA influenced blend structure and modified their viscoelastic properties. Fig. 10 shows the Cole-Cole plot of the moduli determined by DMA. Cole-Cole plots are useful for determining the homogeneity of the blend by interpreting the shape of the given curve. The more homogeneous the material, the more its curve is shaped like a half-sphere (Sahu and Gupta, 2021). PLA had a quasi-circular curve, which was expected for a homogeneous material. The observed viscoelastic behavior is coherent with the values observed by Bajwa et al., (2021) and Eichers et al., (2022). As the CA content of the blend increases, the curve steepens and deflects, demonstrating that heterogeneity increases with the addition of CA. The SEM analysis supports these results, as the roughness increased with the incorporation of CA. A previous study also

<table><caption>**Table 4**
Dielectric and electrical variation between hot-pressing and 3D-printing processing @ 100 Hz.</caption><thead><tr><th rowspan="2"></th><th colspan="3">ε'</th><th colspan="3">ε''</th><th colspan="3">σ<sub>AC</sub></th></tr><tr><th>Hot-pressed</th><th>3D-printed</th><th>Δε' (%)</th><th>Hot-pressed</th><th>3D-printed</th><th>Δε'' (%)</th><th>Hot-pressed</th><th>3D-printed</th><th>Δσ<sub>AC</sub> (%)</th></tr></thead><tbody><tr><td>PLA</td><td>2.92</td><td>2.68</td><td>-8.0</td><td>1.07*10<sup>-2</sup></td><td>1.06*10<sup>-2</sup></td><td>-1.2</td><td>6.19*10<sup>-12</sup></td><td>5.64*10<sup>-12</sup></td><td>-8.7</td></tr><tr><td>CA-10</td><td>3.04</td><td>2.63</td><td>-13.4</td><td>1.47*10<sup>-2</sup></td><td>1.03*10<sup>-2</sup></td><td>-30.1</td><td>8.54*10<sup>-12</sup></td><td>5.11*10<sup>-12</sup></td><td>-40.1</td></tr><tr><td>CA-20</td><td>3.18</td><td>2.69</td><td>-15.4</td><td>1.82*10<sup>-2</sup></td><td>1.25*10<sup>-2</sup></td><td>-31.3</td><td>1.06*10<sup>-11</sup></td><td>6.41*10<sup>-12</sup></td><td>-39.6</td></tr><tr><td>CA-30</td><td>3.27</td><td>2.80</td><td>-14.3</td><td>2.26*10<sup>-2</sup></td><td>1.50*10<sup>-2</sup></td><td>-33.8</td><td>1.27*10<sup>-11</sup></td><td>7.82*10<sup>-12</sup></td><td>-38.4</td></tr><tr><td>CA-40</td><td>3.42</td><td>2.91</td><td>-14.7</td><td>3.25*10<sup>-2</sup></td><td>1.89*10<sup>-2</sup></td><td>-41.7</td><td>1.94*10<sup>-11</sup></td><td>1.15*10<sup>-11</sup></td><td>-40.7</td></tr></tbody></table>
<figure><img src="image_9.png" /><figcaption>Fig. 7. a) SEM analysis of a cross-section of 3D-printed PLA, b) Comparison of porosities of 3D-printed specimens with a 100% infill density, determined by density and permittivity derived methods. Error bars represent the standard deviation.</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>Fig. 8. Storage modulus E' versus temperature of a) hot-pressed samples, b) 3D-printed samples.</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>Fig. 9. Loss modulus E'' versus temperature of a) hot-pressed samples, b) 3D-printed samples.</figcaption></figure>

reported this roughness increase for PLA-starch blends (Yang et al., 2023). The special fibrillar and lamellar morphology was also observed for PLA:CA blends (Coltelli et al., 2021). The Cole-Cole curve also highlighted the cold crystallization phenomenon at high temperatures.

3.5. Glass transition determination by BDS and DMA analysis

BDS and DMA measurements both showed that the addition of CA impacted the α-relaxation of PLA. To better understand this
<figure><img src="image_12.png" /><figcaption>Fig. 10. a) Cole-Cole plot E'' VS E'.</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>Fig. 11. Glass transition temperature of PLA measured by DMA and BDS and their associate first-order fits.</figcaption></figure>

phenomenon, Fig. 11 presents the T<sub>g</sub> PLA for the hot-pressed and 3D-printed blends obtained by DMA and BDS measurements. The determination of T<sub>g</sub> by DMA was based on calculating the E'' peak (Yang et al., 2009) to better correlate with the T<sub>g</sub> values determined by BDS. BDS measurements gave glass transition temperatures of 52.3 and 53.5 °C for hot-pressed and 3D-printed PLA, respectively. These values were coherent with those observed by Dichtl et al. (2017) using the same method. On the other hand, DMA measurements gave glass transition temperatures of 59.9 and 59.6 °C for hot-pressed and 3D-printed PLA, respectively, which is also in agreement with previous findings (Pluta and Galeski, 2007; Yang et al., 2009). The T<sub>g</sub> determined by DMA had higher values than those observed for BDS. This result can be explained by the nature of the measurement, but these results are also consistent with the preliminary results from the DSC analysis. Regardless of the blends and T<sub>g</sub> determination methods, an overall decreasing T<sub>g</sub> trend with increasing CA content was observed. This decrease followed a first-order fit (Fig. 11). The T<sub>g</sub> determined by BDS seemed more sensitive to adding CA, with a slope of approximately -0.54 compared to the -0.39 for DMA. These results allowed accurate prediction of blend glass transition temperatures. Finally, the processing method does not have a clear influence on the response of the CA to the α-relaxation.

All VFT parameters from the BDS fittings are given in Table 5. The data showed that 3D-printed and hot-pressed PLA had an activation energy of α-relaxation of about 960 kJ·mol<sup>-1</sup>. A decrease in E<sub>a</sub> was observed with the addition of CA. According to Delpouve et al., 2018, this decrease could be due to the rupture of the macromolecular interaction caused by the intercalation of the CA and plasticizer molecules.

<caption>Table 5</caption>

Calculated parameters for the VFT model. The Fragility Index m and activation energy of the α-relaxation were added.

<table><thead><tr><th></th><th></th><th>log<br>(f0)<br>(log<br>(Hz))</th><th>B<br>(K)</th><th>T<sub>0</sub><br>(K)</th><th>T<sub>g</sub><br>(K)</th><th>m<br>(S.<br>U.)</th><th>Ea<br>(kJ·mol<sup>-1</sup>)</th></tr></thead><tbody><tr><td rowspan="5">3D-printed<br>samples</td><td>PLA</td><td>12.12</td><td>1093</td><td>294.8</td><td>326.7</td><td>153.1</td><td>957.5</td></tr><tr><td>CA-<br>10</td><td>13.11</td><td>1382</td><td>282.6</td><td>320.4</td><td>135.0</td><td>828.2</td></tr><tr><td>CA-<br>20</td><td>12.63</td><td>1258</td><td>279.9</td><td>315.3</td><td>137.5</td><td>829.7</td></tr><tr><td>CA-<br>30</td><td>13.67</td><td>1514</td><td>270.6</td><td>310.5</td><td>128.1</td><td>761.3</td></tr><tr><td>CA-<br>40</td><td>15.42</td><td>2015</td><td>257.8</td><td>304.8</td><td>116.0</td><td>703.8</td></tr><tr><td rowspan="5">Hot-pressed<br>samples</td><td>PLA</td><td>12.14</td><td>1073</td><td>294.3</td><td>325.5</td><td>155.7</td><td>970.3</td></tr><tr><td>CA-<br>10</td><td>13.41</td><td>1413</td><td>281.7</td><td>319.6</td><td>136.8</td><td>836.9</td></tr><tr><td>CA-<br>20</td><td>14.43</td><td>1729</td><td>270.5</td><td>314.1</td><td>124.1</td><td>746.1</td></tr><tr><td>CA-<br>30</td><td>14.90</td><td>1867</td><td>262.8</td><td>308.6</td><td>119.2</td><td>704.3</td></tr><tr><td>CA-<br>40</td><td>14.87</td><td>1804</td><td>258.7</td><td>303.0</td><td>120.7</td><td>700.5</td></tr></tbody></table>

The parameter m is the Fragility Index, useful for quantifying the deviation of the temperature-dependence of relaxation times from an Arrhenius behavior (Delpouve et al., 2018). A high m reflects a high deviation, indicating a "fragile" polymer behavior. A low m, on the other hand, reflects a good correlation with an Arrhenius behavior, giving the polymer a "strong" behavior. The hot-pressed PLA presented a m index of 154, which is in good agreement with previous reports (Delpouve et al., 2018, 2014; Pascual-Jose et al., 2021). Moreover, the decrease in the Fragility Index of the blends could indicate that the CA and the plasticizer produced a "stronger" PLA behavior, the temperature dependence deviating from a VFT-like behavior and moving closer to an Arrhenius-like behavior (Delpouve et al., 2018).

## 4. Conclusion

In this study, biobased polymer blends made from PLA and CA were successfully prepared using a 3D-printing process. Samples with a CA weight content (W<sub>CA</sub>) of up to 40% were produced and tested with Broadband Dielectric Spectroscopy (BDS), Dynamic Mechanical Analysis (DMA), and dynamic rheology. BDS and DMA measurements showed that the plasticizer in CA decreased the α-relaxation temperature and behavior of PLA. The complex viscosity increased with the addition of CA, following a power law, associated with an increasingly constrained system limiting the fluidity of PLA. The dielectric properties were also influenced by the addition of CA. CA increased the dielectric constant and the dielectric loss, as well as the A.C. conductivity at 20 °C. Moreover, the activation energy of the D.C. conductivity decreased with the addition of CA. The dielectric constant of the PLA:CA blends followed a rule of mixture. 3D-printed biobased blends had lower permittivities and conductivities than the hot-pressed ones. These lower values have been associated with the addition of voids during the 3D-printing process. It would, therefore, be possible to control the dielectric performance of PLA:CA blends by controlling the porosity. Furthermore, this study showed that 3D-printing is a viable method for the use of CA in innovative electronic fields requiring low permittivity and conductivity, such as electrical insulation.

## CRediT authorship contribution statement

Morgan Lecoubllet: Writing – original draft, Software, Methodology, Investigation, Data curation. Mohamed Ragoubi: Writing – review & editing, Writing – original draft, Supervision. Nathalie Leblanc:
Writing – review & editing, Supervision, Conceptualization. **Ahmed Koubaa:** Writing – review & editing, Supervision, Conceptualization.

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.

Data availability

Data will be made available on request.

Acknowledgment

This work was supported by the Région Normandie (Fr), the Canada Research Chair Program; the NSERC Discovery Grant; MITACS Globalink Program; and TABES Create Program (Grant Number CREATE 554777-2021). We would like to thank the ITHEMM laboratory (Charleville-Mézières, France) for letting us use their 3DEVO filament maker.

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