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**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Padhan, Paul and Bijwe. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
<figure><img src="image_299.png" /></figure>

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# Hollow Section Fibers Characterization for Seats Covers Fabric Application

Valentina Brunella¹*, Giulia Albini¹,², Vito Guido Lambertini² and Bartolomeo Placenza²

¹ Dipartimento di Chimica e NIS Research Centre, University of Turin, Turin, Italy, ² Group Materials Labs, Polymers Group, Centro Ricerche Fiat, Turin, Italy

This research is focused on hollow polyethylene terephthalate (PET) fibers and fabrics. The aim of hollow section fibers application is a textile contribution to weight reduction of the whole vehicle. CO₂ emissions consequences and awareness of companies to environmental issues are driving studies on the direction of vehicle weight reduction, according to recent European regulations. For this purpose, fabrics composed of hollow fibers have been produced and characterized. In order to be applied as seats covers for the automotive sector, they have been compared to current production woven fabrics. Tensile, tear strength tests and aesthetic and structural abrasion have been carried out. The performance of hollow fibers PET fabrics is slightly lower than full section fabrics, but completely acceptable according to automotive requirements. Its specific application can be evaluated.

**Keywords:** hollow fibers, PET fibers, automotive fabric, technical textile, weight reduction, emission reduction

## OPEN ACCESS

**Edited by:**
Emilia Morallon,
University of Alicante, Spain

**Reviewed by:**
Antonio Greco,
University of Salento, Italy
Philippe Boisse,
Institut National des Sciences
Appliquées de Lyon (INSA Lyon),
France
Kadir Bilisik,
Erciyes University, Turkey

*Correspondence:
Valentina Brunella
valentina.brunella@unito.it

**Specialty section:**
This article was submitted to
Polymeric and Composite Materials,
a section of the journal
Frontiers in Materials

**Received:** 18 February 2020

**Accepted:** 03 July 2020

**Published:** 04 August 2020

**Citation:**
Brunella V, Albini G, Lambertini VG and Placenza B (2020) Hollow Section Fibers Characterization for Seats Covers Fabric Application. *Front. Mater.* 7:243. doi: 10.3389/fmats.2020.00243

## INTRODUCTION

Due to recent European regulations and Companies' awareness to environmental issues, CO₂ emissions need to decrease and more recycled materials need to be used. Recycling involves reducing waste and production of new materials, recovering and transforming of refuse. PET and other plastics affect the amount of waste for disposal, but they can be recycled, as an economical way to reduce plastic waste for automotive application (Cole and Sherman, 1995; Jambor and Beyer, 1997; Koch, 2005). Apart from Companies' responsibility, Customers' awareness in reducing fuel consumption and using fuels from renewable resources are important (Official Journal of the European Union, 2009). In fact, CO₂ production is directly related to type and fuel consumption quantity. European legislation has set 95 g/km maximum limit of CO₂ emission within 2020 (Official Journal of the European Union, 2009; Poyant, 2013).

Carmakers have been looking for new ways for reducing CO₂ emissions, focusing on increasing the use of recycled materials and vehicle total weight reduction. The technology of new engines is related to innovation with an increased efficiency, trying to reduce fuel consumption in conventional engines or using renewable resources origin fuels together with new kinds of engines. Emissions reducing is related to whole vehicle weight reduction, and similarly, vehicle weight reduction affects fuel consumption for 75% (Fredriksson and Veitl, 2011; Poyant, 2013).
In the recent years, the average weight of vehicles has been increasing from 800 kg of 1970s to its climax, 1300 kg of 2012. The increase is approximately 32% (Koch, 2005). 100 kg vehicle weight reduction can cause fuel consumption decreasing of 0.3–0.8 L per 100 km (Fredriksson and Veitl, 2011).

In the textile field for automotive application, awareness of environmental issues is related both to the use of green materials from recycled sources and to weight reduction. To continue in the eco-friendly direction for the automotive area, in this work our attention will be driven to the last objective.

A study (Albini et al., 2019), about recycled PET fabrics for automotive application has already proved that post-consumer PET fibers can be used to make yarns and fabrics, which withstand all high technical requirements. Instead, in order to reduce the weight of the whole vehicle, a collaboration among automotive sectors is essential and a contribution of all areas can be decisive. These areas are car body development, engine manufacturing departments and design. The goal of reducing total weight of vehicle can be achieved using lightweight materials (Cole and Sherman, 1995; Jambor and Beyer, 1997). Among these, plastics, composites and light alloys (Lyu and Choi, 2015). Reducing weight in every kind of component affects vehicle final weight (Cole and Sherman, 1995; Jambor and Beyer, 1997). Textile covering also conditions the whole weight of about 20 kg and this could be a significant part if related with all other improvements in weight (Fredriksson and Veitl, 2011). Textile materials cover seats, floor, door panels, ceiling and they are used in functional roles, as for seat belts, pipes, airbags, and tires.

Textile weight reduction is demanding. First, fabrics have to meet automotive requirements to satisfy applications with high technical-mechanical performances. High wear resistance, fastness to light, comfort and safety features are fundamental characteristics to ensure durability of the vehicle (Fung and Hardcastle, 2001; Hearle and Morton, 2008). Different papers tell about possible applications of hollow fibers in the automotive sector. For example, hollow fibers fabrics for interiors insulation applications or composing technical non-woven (Mahmoud et al., 2011; Ki-Young et al., 2013).

The objective of this research is to examine hollow section PET fibers and hollow PET fibers fabric. These fabric properties need to be equivalent to current production fabrics for seats covers application. Hollow fibers are polymeric fibers with a continuous hole running down the middle (Eichhorn et al., 2009). This particular section affects fabric mechanical, structural and after wearing aesthetical final properties (Matsudaira et al., 1993; Khoddami et al., 2009). Hollow fibers fabrics have been compared to current production fabrics in order to evaluate their possible application. Fabrics characteristics and hollow section fibers fabrics final weight reduction will be evaluated. Assessing different mechanical properties, this research can contribute increasing knowledge about hollow fibers production and fabrics characteristics and, above all, their possible applications.

For *Original Research Articles*, *Clinical Trial Articles*, and *Technology Reports* the introduction should be succinct, with no subheadings. For *Case Reports* the Introduction should include symptoms at presentation, physical exams, and lab results.

# MATERIALS AND METHODS

An Italian manufacturer supplied fibers. PET hollow section fibers and full section fibers were produced. The production of the two different fibers is substantially equivalent in order to obtain two final products comparable. Fibers production starts from PET chips, which are crystallized at 100–170°C before the spinning process, in order to decrease the humidity content. After that, PET chips are melted, extruded and sent to the dosing pumps. They were mass dyed in black. The parameters of the first step of fibers production are:

* Entry air temperature (drying) 170°C; exit air temperature (drying) 100°C;

* Enter temperature (extrusion) 270°C; exit temperature (extrusion) 280°C;

* Rotating pumps speed is 21,6 rpm for hollow ones and 25,7 rpm for full ones;

* Spinneret pack holes number is 56 for hollow ones and 48 for full ones;

* Cooling temperature is 30°C;

* Yarn collecting speed is 3000 m/min for hollow ones and 3050 m/min for full ones;

* Yarn count (for each yarn end) is 235 dtex for hollow ones and 257 dtex for full ones;

* Finish is texturing for both fibers type.

Main differences between hollow and full section fibers production are rotating speed and number of holes of the spinneret pack (Figure 1). Melted material is sent to the spinneret pack, composed of 48 and 56 holes for full and hollow section fibers production, respectively.

<figure><img src="image_300.png" /><figcaption>**FIGURE 1** | Part of the spinneret pack (Lukay Nonwoven Solutions, 2019) and hollow (left) and full (right) section of spinneret pack holes.</figcaption></figure>
Because of lower covering capability of hollow section fibers yarns compared to full section fibers, the holes number of the spinneret pack has been increased to give them better covering capability and volume and make them comparable to full section fibers.

As regards hollow fibers production, the hole is usually shaped with the introduction of air or other gas (nitrogen) in the polymeric solution (wet spinning process) or melt spinning through specially designed spinnerets. For this research, the method is the last. Hollow fibers provide greater bulk with less weight. Exiting the spinneret pack, yarns are POY (partially oriented yarn) and they progressively are cooled, stretched and textured with “Taslan” process. The last process allows the yarn to be structurally modified with a air flow bending some areas of the yarn and creating curled fibers on the yarn itself, giving the yarn specific characteristics (Andreoli and Freti, 2004).

The two kinds of fiber sections have been structurally analyzed by a metallographic microscope Reichert MeF3A, to understand their section. The preparation of the samples for microscope analysis includes yarns insertion into a thermosetting resin. These samples are 40 mm wide. The upper side of the sample is polished with abradents and diamond paste to better evaluate its surface.

Yarns and fabrics properties are summarized in **Table 1**. Yarns are composed of 6 yarn ends for warp yarns direction and 4 yarn ends for weft yarns direction. The final yarn count is reported in the table below, with a reduction of 19.6% for hollow fibers warp yarns and 19% for hollow fibers weft yarns. The setting parameters for fibers production have conducted to an acceptable reduction in weight of the yarns (equal length). A major Italian company produced flat woven fabrics with a Jacquard loom, using hollow and full section fibers yarns. Woven fabric is the most used for seat cover application (Pamuk, 2008) and consists of two sets of yarns interlaced at right angles to each other. Its strength and durability can be varied and depend on the yarn type and the thread spacing (Horrocks and Arnand, 2016). For this research, woven fabric structure type is twill weave. Three samples with different number of weft yarns/cm have been considered to notice the influence of yarns density on the results and to better evaluate global fabrics characteristics.

Fabrics were subjected to further processes: dry cleaning with $C_2Cl_4$, thermo-fix process at 140°C and calender process to

optimize dimensional stability. As some authors tell (Becerir et al., 2007), hollow fibers can compromise wear resistance of the final product. For this reason, double washing during the production process was done, to better eliminate impurities and weaving oils. The last production step is a lamination process. It is applied to almost every kind of fabric in the automotive sector and it impart a soft touch to the fabric and ease the sewing process of cover manufacturing. During this step, a flame lamination step, the polyurethane is the adhesive, melted with a gas flame. The fabric manufacturer laminated fabrics to one side of a polyurethane foam layer and a scrim fabric to the other side of the polyurethane layer (Fung and Hardcastle, 2001). In **Table 1**, values of fabrics total thickness and fabrics total weight are referred to laminated fabrics with polyurethane layer foam and the scrim fabric, instead fabric weight and thickness refers to the fabric itself, without lamination.

As visible in **Table 1**, hollow and full fibers fabrics weight is different and we can evaluate a 20% average reduction in weight for the fabric without lamination. This reduction reflects reduction of the yarn weight with the yarn count, as mentioned above with data reported in **Table 1**. Each hollow section fibers sample has been compared to its respective full section fiber sample. The evaluation has been done on five samples for each kind of fabric. In particular, the reduction in weight is 20.1% for 13 weft yarns/cm sample, 20.7 and 20.9% for 14 and 15 weft yarns/cm samples, respectively. Instead, total laminated weight can change depending on the variability of polyurethane and scrim fabric weight and thickness and on the variability of the sampling.

Tensile and tear resistance tests were performed to evaluate fabrics mechanical characteristics. Fabrics need to bear seat cover manufacturing processes and to perform highly when exposed to mechanical stress throughout the lifetime of the vehicle. Tensile strength test was performed on Acquati AG/7E/306 electronic dynamometer according to ISO 13934-1 (Iso 13934-1:2013, 2013). For each type of fabric, five samples for warp and five for weft direction were tested. This is necessary because fabric properties are affected by the loading direction. Tear strength test was carried out to measure the force to propagate a tear in fabric. This test is useful to evaluate the textile material stress suffered during the process of cover production. The test was

<table><caption>**TABLE 1** | Yarns and fabrics characteristics.</caption><thead><tr><th rowspan="2">Fabrics characteristics</th><th colspan="2">Sample 1</th><th colspan="2">Sample 2</th><th colspan="2">Sample 3</th></tr><tr><th>Hollow s.</th><th>Full s.</th><th>Hollow s.</th><th>Full s.</th><th>Hollow s.</th><th>Full s.</th></tr></thead><tbody><tr><td>Number of warp yarns/cm</td><td>24 ± 1</td><td>24 ± 1</td><td>24 ± 1</td><td>24 ± 1</td><td>24 ± 1</td><td>24 ± 1</td></tr><tr><td>Number of weft yarns/cm</td><td>13 ± 1</td><td>13 ± 1</td><td>14 ± 1</td><td>14 ± 1</td><td>15 ± 1</td><td>15 ± 1</td></tr><tr><td>Fabric total weight (g/m²)</td><td>444 ± 3</td><td>520 ± 5</td><td>444 ± 4</td><td>534 ± 6</td><td>455 ± 3</td><td>541 ± 6</td></tr><tr><td>Fabric weight (g/m²)</td><td>345 ± 3</td><td>432 ± 2</td><td>343 ± 1</td><td>433 ± 2</td><td>354 ± 2</td><td>448 ± 1</td></tr><tr><td>Fabric total thickness (mm)</td><td>3 ± 0.2</td><td>3 ± 0.2</td><td>3.1 ± 0.2</td><td>3 ± 0.2</td><td>3 ± 0.2</td><td>3 ± 0.2</td></tr><tr><td>Fabric thickness (mm)</td><td>0.5 ± 0.1</td><td>0.5 ± 0.1</td><td>0.6 ± 0.1</td><td>0.5 ± 0.1</td><td>0.5 ± 0.1</td><td>0.6 ± 0.1</td></tr><tr><td>Warp yarn count (dtex)</td><td>905 ± 45</td><td>1125 ± 56</td><td>905 ± 45</td><td>1125 ± 56</td><td>905 ± 45</td><td>1125 ± 56</td></tr><tr><td>Weft yarn count (dtex)</td><td>610 ± 30</td><td>753 ± 36</td><td>610 ± 30</td><td>753 ± 36</td><td>610 ± 30</td><td>753 ± 36</td></tr></tbody></table>

The values are reported for each characteristic with standard deviation.
performed according to ISO 9073 (ISO 9073:1999, 1999). Samples were prepared in the format as in **Figure 2** and tore on one side ("cut" in **Figure 2**). The dashed lines point out where the clamps of the dynamometer grab the sample.

According to internal automotive validation test, perforation resistance test has been evaluated. This test reproduce the stress suffered from the fabric of seat cover when a foreign body accidentally perforates it, during the lifetime of the vehicle. The test was performed with the dynamometer and the particular device as in **Figure 3**, placed instead of the clamps, made up of a metallic sphere of 12.7 mm diameter. With the help of the

dynamometer, the sphere moves at 80 mm/min and produce a perforation of the round sample.

Structural wear resistance was evaluated to define the resistance of the yarns composing the fabric. The test was performed on a Taber (Rotary Platform Double Head Tester) abrasimeter, according to ASTM D3884/09 (ASTM D3884/09:2013, 2013). The analyzed fabric was worn against two Calibrase 10 abrasive wheels, moving in opposite directions on its surface, as schematized in **Figure 4**. Three samples for each type of fabric were examined. According to internal automobile specification, 600 cycles of wheels rotation were set for woven fabrics. Flat woven fabrics require a longer period of testing because of their inherently more resistant structure, compared to other kinds of fabric structure, such as knitted ones.

Furthermore, worn surfaces were visually examined and graded by setting values from 3, best result with no yarns breakage, to 1, worse result, with at least a yarn breakage.

Aesthetic wear resistance of all type of fabrics was evaluated with a Cesconi Abrasive tester, comparable to Martindale Abrasimeter, according to ISO 12947/1-2-3-4 (ISO 12947/1-2-3-4:1998, 1998). This test reproduces the mechanical stress suffered by seat cover fabrics during their

<figure><img src="image_301.png" /><figcaption>**FIGURE 2** | Sample template for tear strength test. The dimensions are in mm.</figcaption></figure>

<figure><img src="image_302.png" /><figcaption>**FIGURE 3** | Device for perforation resistance test.</figcaption></figure>

<figure><img src="image_303.png" /><figcaption>**FIGURE 4** | Scheme of the structural wearing test apparatus.</figcaption></figure>

<figure><img src="image_304.png" /><figcaption>**FIGURE 5** | Scheme of wear resistance test apparatus. The substrate to test (D) is placed on the rotating plate (F), through a substrate holder (E). The abrasive fabric, instead, is placed on the fixed plate (A), using an appropriate substrate holder (B), on which a load is applied (P).</figcaption></figure>
<figure><img src="image_305.png" /><figcaption>FIGURE 6 | (A) Hollow fibers section image and (B) full fibers section image.</figcaption></figure>

<figure><img src="image_306.png" /><figcaption>FIGURE 7 | Tensile strength results. Hollow and full section and different number of weft yarns/cm have been evaluated.</figcaption></figure>

<figure><img src="image_307.png" /><figcaption>FIGURE 8 | Tear strength results for warp and weft direction samples. Hollow and full section and different number of warp yarns/cm have been evaluated.</figcaption></figure>
<figure><img src="image_308.png" /><figcaption>**FIGURE 9** | Perforation strength results. Hollow and full sections and different number of warp yarns/cm have been evaluated.</figcaption></figure>

use for an average lifetime of the vehicle. The abrasion tester is generally used for testing textile materials. The apparatus is schematized in **Figure 5**. The abrading standard fabric is made of woolen fibers and fixed on a given plate (point A in **Figure 5**). The tested surface is placed on a rotating disk located under the fixed plate. The rotating plate moves with a revolution movement in order to ensure a complete wear of the fabric sample. 3000 and 6000 cycles were performed with a load of 3 kg, according to internal automobile validation test.

For aesthetic wear resistance test three samples for each kind of fabric were examined and evaluated according to gray scale. The scale quantifies changes in color compared to the reference. It includes a range of shade of gray, from 1, worse result, evident modification of the surface to 5, better result, almost no superficial changes on fabric, with a step of 0.5. Minolta CM-3610 spectrophotometer provided gray scale measurements, under a D65 illuminant using a 10° standard observer with specular component excluded (SCE) mode. Not worn surfaces were taken as standards and worn fabrics as samples. Surfaces pictures were recorded with LEICA M205C optical microscope. Before the tests, all specimens were conditioned for 72 h in a standard atmosphere at 20 ± 2°C with 65 ± 2% relative humidity, according to ISO 139 (ISO 139:2005, 2005).

## RESULTS

Hollow and full sections have been compared in **Figure 6**, which shows fibers transversal section.

On the left, the hollow section of the fibers is visible.

The average diameter of the fibers is 17 µm for hollow section and 19 µm for full section. The inner average diameter of hollow section is 8 µm.

<table><caption>**TABLE 2** | Structural wear resistance test results.</caption><thead><tr><th rowspan="2">Sample</th><th colspan="2">Grade values</th></tr><tr><th>Hollow fibers</th><th>Full fibers</th></tr></thead><tbody><tr><td>Sample 1 600 cycles</td><td>2</td><td>3</td></tr><tr><td>Sample 2 600 cycles</td><td>3</td><td>3</td></tr><tr><td>Sample 3 600 cycles</td><td>3</td><td>3</td></tr></tbody></table>

<table><caption>**TABLE 3** | Aesthetical wear resistance test results.</caption><thead><tr><th rowspan="2">Sample</th><th colspan="2">Gray scale values</th></tr><tr><th>Hollow fibers</th><th>Full fibers</th></tr></thead><tbody><tr><td>Sample 1 3000 cycles</td><td>2.5</td><td>4.5</td></tr><tr><td>Sample 1 6000 cycles</td><td>2.5</td><td>4</td></tr><tr><td>Sample 2 3000 cycles</td><td>2</td><td>4</td></tr><tr><td>Sample 2 6000 cycles</td><td>2</td><td>4</td></tr><tr><td>Sample 3 3000 cycles</td><td>2</td><td>4.5</td></tr><tr><td>Sample 3 6000 cycles</td><td>2</td><td>4</td></tr></tbody></table>

## Tensile Strength Test

**Figure 7** shows strength resistance test for all kind of fabrics. Three samples (Table 1) have been tested: sample 1 (13 weft yarns/cm); sample 2 (14 weft yarns/cm) and sample 3 (15 weft yarns/cm).

Considering warp direction samples, they are all above automotive requirements (≥100 daN) and they don't break under a force of 500 daN, the maximum load detectable for the dynamometer cell. High loads are required during fabric manufacturing and covers assembling steps. These results depend on the particular flat woven structure of the fabric and on the high number of warp yarns/cm. During the test, all warp yarns
<figure><img src="image_309.png" /><figcaption>**FIGURE 10** | Pictures under the microscope of full and hollow section 13 weft yarns/cm PET fabric surfaces before wear resistance test and after 3000 and 6000 cycles of wearing (from left to right).</figcaption></figure>

are stressed simultaneously and contribute to the result. There is no significant difference between hollow and full section fibers fabrics, and hollow section fibers do not seem less strong than full section fibers. Instead, considering weft direction samples, for both hollow and full sections, the load increase with the number of weft yarns/cm, as expected.

## Tear Strength Resistance

In order to evaluate hollow section fibers fabrics performance tear strength test has been performed. **Figure 8** shows the results with a comparison between hollow and full section fibers fabrics with different number of yarns/cm.

Tear strength resistance of hollow fibers fabrics is slightly lower than full fibers fabric, but almost comparable to them. This difference is kept for weft direction samples (**Figure 8**). Maximum load values are higher for warp direction samples, compared to weft direction samples. This is due to higher number of yarns/cm, 24, compared to 13, 14, and 15 for weft direction samples. Among three different yarns density sample there are not significant differences, considering standard deviation, so they are all considered comply with automotive standards.

## Perforation Strength

**Figure 9** shows perforation strength results for hollow and full section fabrics. Different number of warp yarns/cm have been evaluated. Current production fabrics are perforation resistant, with high average values included between 130 and 134 daN. Hollow section fibers fabrics show slightly lower values of perforation strength, due to the particular fiber section, but

acceptable according to automotive standards, for which 25 daN minimum is required.

## Abrasion Resistance

For all kinds of fabrics, structural wear resistance results are summarized in **Table 2**. Not worn fabrics were taken as standard fabrics, and they are evaluated grade 3. After Taber test, full section fibers fabric does not show any yarn breakage, nor structural changes. The worn surface presents a slight shadow, hence it's evaluated grade 3. This result is positive according to automobile standard, for which there must be no yarns breakage.

Sample 1 surface, composed of hollow section fibers, shows some fibers/yarns breakage after structural wear resistance test, compared to sample 2 and 3. The abrasive wheels stress their surface several times and cause the damage of the most superficial fibers. Sample 1 has lower weft yarns density and this can have influence on the result. Furthermore, the hollow structure of the fiber and the less number of weft yarns/cm compared to sample 2 and 3 affect the result.

Afterward, fabrics surface was examined after aesthetic wear resistance test. Values of gray scale have been registered with the spectrophotometer and they are represented in **Table 3**.

For a more accurate analysis, pictures of the surfaces have been taken at different magnification with an optical microscope (Figures 10–12). Worn surfaces of full section fibers fabrics do not present broken yarns nor structural modifications. Hollow section fiber fabrics (sample 1, 2, and 3) show evident modification of the surface after 3000 cycles, fibers lifting and breakage and clear whitening of the surface. After 6000 cycles,
<figure><img src="image_310.png" /><figcaption>**FIGURE 11** | Pictures under the microscope of full and hollow section 14 weft yarns/cm PET fabric surfaces before wear resistance test and after 3000 and 6000 cycles of wearing (from left to right).</figcaption></figure>

<figure><img src="image_311.png" /><figcaption>**FIGURE 12** | Pictures under the microscope of full and hollow section 15 weft yarns/cm PET fabric surfaces before wear resistance test and after 3000 and 6000 cycles of wearing (from left to right).</figcaption></figure>
the surface has lifted fibers and disappearing of fabric structure but it is not worse compared to 3000 cycles results. This is confirmed by gray scale values: their surfaces are evaluated 2 of gray scale after 3000 and 6000 cycles (Table 3), unacceptable according to automotive standards. Despite the slightly better gray scale evaluation (Table 3), sample 1 (hollow section) surface appearance is visually the worst compared to sample 2 and 3, because of lifting and damaging of the fibers. This is a consequence of a difference in yarns density and structural weakness, as observable also after Taber abrasion test (Table 2). Full fiber fabrics bear the abrasive wheels stress of surface and they are evaluated 4.5 of gray scale after 3000 cycles and 4 after 6000 cycles.

For both structural and aesthetical, wear resistance depends on a combination of fiber structure, yarn, and fabric construction characteristics.

## CONCLUSION

In this paper, structural and mechanical characteristics of PET fabrics composed of hollow section fibers were evaluated. They were compared to current production full section fibers PET fabrics. Mechanical tests were performed to evaluate their matching with specific automotive requirements.

Despite good mechanical results, hollow section fibers fabrics can't be applied as cover of very contactable areas, for example sittings areas and back seats. In fact, structural and aesthetic wear resistance test results showed fibers breakages and lifting and structure disappearing. For this reason, they are not in compliance with automotive regulations. Otherwise, hollow section fibers fabric is suitable as "covering textile" for less

contactable areas, lateral zones, ceiling, door panels, etc. With these specific applications, negative effects of aesthetic abrasion may be avoided. Hollow fibers fabric reaches the elevated mechanical performance of current production PET textile materials, and it can replace them where aesthetic abrasion cannot compromise its use. A slight difference has been found among the three hollow section fiber samples tested, regarding abrasion resistance test result for 13 warp yarns/cm density fabric (sample 1). This result can direct fabric choice toward sample 2 and 3, to gain a durability for the lifetime of the vehicle.

Hollow section fiber fabrics can contribute to benefits as reducing vehicle weight of approximately 20% compared to current production textiles materials, being applied as covering of specific parts of car interior. In this way, these fabrics can be environmentally friendly.

## DATA AVAILABILITY STATEMENT

All datasets generated for this study are included in the article/supplementary material.

## AUTHOR CONTRIBUTIONS

VB and BP designed the experiments. GA performed the experiments. GA and VB analyzed the data. VL revised the manuscript. All the authors reviewed and approved the manuscript.

## ACKNOWLEDGMENTS

The authors wish to thank AUNDE for fabrics production.

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**Conflict of Interest:** The authors declare that AUNDE provided materials analyzed in this work. AUNDE did not provide funding and was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.

Copyright © 2020 Brunella, Albini, Lambertini and Placenza. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
<figure><img src="image_312.png" /></figure>

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# Under Glass Weathering of Hemp Fibers Reinforced Polypropylene Biocomposites: Degradation Mechanisms Based on Emitted Volatile Organic Compounds

Célia Badji¹,², Jean-Marc Sotiropoulos³, Joana Beigbeder¹, Hélène Garay¹, Anne Bergeret², Jean-Charles Bénézet² and Valérie Desauziers¹*

¹IPREM, IMT Mines Ales, Université de Pau et des Pays de l'Adour, E2S UPPA, CNRS, Pau, France, ²PCH, IMT Mines Ales, Ales, France, ³IPREM, Université de Pau et des Pays de l'Adour, E2S UPPA, CNRS, Pau, France

OPEN ACCESS

**Edited by:**
Patricia Krawczak,
IMT Lille Douai, France

**Reviewed by:**
Xavier Colin,
École Nationale Supérieure d'Arts et Métiers, ParisTech, France
Dan Maskell,
University of Bath, United Kingdom
Asim Shahzad,
National University of Sciences and Technology (NUST), Pakistan

*Correspondence:
Valérie Desauziers
Valerie.Desauziers@mines-ales.fr

**Specialty section:**
This article was submitted to Polymeric and Composite Materials, a section of the journal Frontiers in Materials

**Received:** 09 March 2020
**Accepted:** 04 May 2020
**Published:** 18 June 2020

**Citation:**
Badji C, Sotiropoulos J-M, Beigbeder J, Garay H, Bergeret A, Bénézet J-C and Desauziers V (2020) *Under Glass Weathering of Hemp Fibers Reinforced Polypropylene Biocomposites: Degradation Mechanisms Based on Emitted Volatile Organic Compounds*. Front. Mater. 7:162. doi: 10.3389/fmats.2020.00162

The durability of hemp fibers reinforced polypropylene biocomposites was investigated after one year under glass exposure. Volatile organic compounds emissions were assessed using a new passive sampling method. Degradation pathways were examined in order to understand the weathering mechanisms. The polymer matrix was decomposed into oxygenated products due to UV rays and high temperatures. As regards hemp fibers, different degradation steps of the carbohydrates were highlighted according to the nature of the detected furans. At a non-weathered state, dehydrations preceded the ring-opening mechanism, often catalyzed by Maillard reactions. The further cyclization induced the formation of 2- or 5-substituted furans emitted by non-weathered materials. Reactions between identified products after weathering which were not yet found in literature were proposed in this paper. They often implied a keto-enol tautomerism but also dehydrations that induced the formation of 3- and 4-substituted furanones. These differences can be explained by a primary decomposition of carbohydrates favored at a non-weathered state and a secondary one occurring at a weathered state.

**Keywords:** hemp fiber, ageing, VOCs, oxidation, dehydration

## INTRODUCTION

Recently, bio-fillers have emerged as an attractive alternative to inorganic fillers in the reinforcement of thermoplastics in response to growing awareness of environmental issues and increasing global waste problems (Liu and Hu, 2008). The main application areas of vegetal filler reinforced composites are the automotive and building industries (John and Thomas, 2008; Azwa et al., 2013). The natural fibers improve the mechanical properties of the composites (Saba et al., 2016; Kumre et al., 2017). Recently, lignin in a lignin-polyethylene (PE) biocomposite showed some antioxidant properties that protect the PE matrix (Van Schoors et al., 2018). Otherwise, with increasing concerns about indoor air quality, volatile organic compounds (VOCs) emissions
behavior in interior materials used as automotive parts has become widely recognized as an important topic for indoor environment air quality (Yu and Crump, 1998; Air quality sciences Inc., 2006; Badji et al., 2018).

During the melt mixing process of biocomposites through extrusion and injection molding, the high manufacturing temperatures exceed the bio-fillers degradation temperature (Dorez et al., 2013; Khazaeian et al., 2015). Also, during their use, climatic conditions weaken their chemical stability because of their high sensitivity (Zou et al., 2008; Ahmad et al., 2011; Badji et al., 2017). Temperature variations induce carbonization and odors emanating from the heated matter. Also, a press molding temperature increase induces biocomposites color turning from brown to close to black (Shibata, 2016). This was thought to be the result of vegetal fibers caramelization. Some solutions for reducing the odors and the amount of VOCs produced by biocomposites have been studied (Kim et al., 2006, 2011). But molecules responsible for the worsening air quality, color changes, and odors must be assessed.

Volatile organic compounds emitted by plastics are generally due to polymer degradation. Studies on thermal and photochemical oxidation of polypropylene (PP) showed that radical processes are responsible for chain scission, leading to low molecular weight products migrating from the polymeric matrix to the atmosphere (François-Heude et al., 2014; Rouillon et al., 2016). It is widely accepted that Norrish type I and II photochemical reactions occur involving C-C cleavage, leading to the formation of oxygenated compounds (Rabek, 1990; Muasher and Sain, 2006). Those generally result from the oxidation of tertiary carbon atoms of the polymer chains, leading to methyl ketones, along with alcohols, aldehydes, and aliphatic hydrocarbons formation.

The pyrolysis of lignocellulosic biomass was widely studied and further identification of the volatile compounds issued from the natural fibers' thermal degradation was sometimes performed. Some products, originating from pyrolysis of cellulose [molecular formula: $(C_6H_{10}O_5)_n$], are identified as low molecular weight compounds. They are formed by ring-opening reactions, while pyrans and furans are obtained from dehydration reactions (Sanders et al., 2003; Nowakowski and Jones, 2008). These molecules are generally stable aromatic compounds and hardly decompose into lower molecular weight compounds (Katō and Komorita, 1968). Their decomposition accounts for the major reactions occurring in the secondary reaction stage of cellulose. Hemicelluloses consist of saccharides such as glucose, mannose, xylose, and arabinose (Nowakowski and Jones, 2008; Binder et al., 2010). Once pyrolyzed, the derivatives of these pentose sugars, such as cyclopentanes and cyclopentenones, are detected in large quantities in addition to furan molecules (Peng and Wu, 2011; Carrier et al., 2012). Lignin component, a highly complex aromatic structure, breaks down into phenolic structures (Wittkowski et al., 1992; Brzonova et al., 2014). It mainly consists of three basic building blocks: guaiacyl, syringyl, and *p*-hydroxyphenyl units. However, non-cellulosic polysaccharides, such as proteins, are also found in lower proportions under amino acid forms (Sari, 2015). Each

component proportion present in the vegetal fibers depends on several parameters such as their nature, retting time, and geographic origin.

Maillard reactions are mainly responsible for the formation of flavor compounds like the 2-furanones with similar structures, unlike those of volatile substances issued from biofillers degradation. Besides the flavoring of food, the interest in Maillard mechanism has grown in fields concerned with the physico-chemical properties of proteins and polysaccharides (Mitsuo, 1988; He et al., 2014). This reaction implies the interaction between the amino group from an amino acid, a protein, or an amine and the carbonyl functional group from the carbohydrate part (glucose, fructose) under heating conditions (Zhang et al., 2008). It produces an unstable N-substituted glycosylamino compound. This first step is reversible but the generated glycosylamine is immediately converted into an Amadori compound (Newton et al., 2012). Amadori intermediate compounds belonging to the 1-amino-1-deoxy-2-ketoses family are important precursors in the formation of flavor compounds from Maillard reactions (Hodge et al., 1972; Zhang et al., 2008). Caramelized sugar aromas furanones, such as furfural and 5-methylfurfural, or pyranones such as maltol, evolving from holocellulose, are generated through sugar-amine condensation. Then, the formed Amadori compound can react along multiple pathways to form Maillard reaction products at lower temperatures than those found in pyrolysis studies of natural fibers, since the presence of nitrogen containing compounds catalyzes the reaction (Newton et al., 2012). For instance, maltol, a well-known carbohydrate derivative, and 4-hydroxy-2,5-dimethyl-3(2H)-furanone, derives from a common intermediate arising by sugar-amine condensation and Amadori rearrangement. 2,3-enolization of the 1-amino-1-deoxy-2-ketose and elimination of the 1-amino group occur at the final step (Hodge et al., 1972). Then, dehydrations and cyclization lead to furans generation (Wang et al., 2012) and ene-diol scissions and retroaldolization to short products (Belitz et al., 2004).

However, formations of the substances found in literature dealing with biomass and their controlled decomposition (pyrolysis) were not explained to be due to this mechanism. Indeed, the reactions involved require the presence of artificial catalysts (chromium, copper) facilitating the conversion (Binder et al., 2010; Perez and Fraga, 2014). Otherwise, when decomposition products are obtained from the pyrolysis process, this includes energetic conditions favorable enough (temperature reaching 800°C) that ring-opening, dehydrogenation, and cracking can occur (Sanders et al., 2003; Peng and Wu, 2011). Moreover, formation of other methylfurans that could issue from thermal decomposition and reactions between volatile chemicals emitted by natural fibers were not reported.

A one-year natural under-glass weathering of hemp fibers reinforced PP biocomposites was investigated to simulate a car interior environment. Volatile organic compounds emissions were assessed throughout the process. The objective was to use the identification of emitted VOCs to understand the components' method of degradation by firstly studying the neat polymer ageing and secondly the aging of the hemp fibers load
in the polymer matrix. The well-known Maillard mechanism for the holocellulose part decomposition has been examined thanks to VOCs identification. Reactions between identified VOCs and their concentration evolution were proposed. Finally, the lignin degradation was also investigated.

# MATERIALS AND METHODS

## Materials

Polypropylene grade H733-07 with a melt flow rate of 7.5 g/10 min (230°C, 2.16 kg) (Braskem, Brazil) was used as a polymer matrix. Hemp fibers were provided by AgroChanvre (France). Two hemp fibers loading, 10 wt% (PP10) and 30 wt% (PP30), were tested. Maleic anhydride grafted polypropylene (MA-g-PP), under the trademark Orevac CA100 (Arkema, France), was added at 3.1 wt% of PP as a coupling agent.

## Process Conditions

Hemp fibers and MA-g-PP were dried for 15 h at 60°C. Then, granules of PP and MA-g-PP were mixed with hemp fibers in a BC21 Cleextral twin-screw extruder (L/D = 36 with D = 25 mm) (Cleextral, France) with the temperature profile 190-190-190-180-175-175-175°C and a screw speed of 220 rpm. Once dried for 3 days at 60°C, extruded pellets were injection molded into specimens in a Krauss Maffei machine (Krauss Maffei, Germany) at 210°C with an injection speed of 30 $cm^3.s^{-1}$. Square samples of 100 mm × 100 mm × 2 mm were obtained.

## Weathering Conditions

Samples were exposed from September 2015 to September 2016 in the south west of France under windshield glass to simulate a car interior environment according to ISO 877-2:2011 (Figure 1). The exposition panels were oriented toward the south at 45° with the ground. The interior environment was naturally ventilated thanks to holes located on stainless steel boxes 2 h per day. Temperature T(°C) and relative humidity RH(%) were

monitored and PP, PP10, and PP30 materials were sampled after 1, 2, 3, 6, 9, and 12 months. Temperatures ranged from -5°C in February to 91°C in August and relative humidity fluctuated between 3% in September and 95% in November.

# Sampling and Analytical Methodology

At each weathering step, three samples of each material were brought from the racks to the laboratory where VOCs emission analysis was carried out through a passive sampling method developed at the laboratory (Bourdin et al., 2014; Badji et al., 2018). It consists of two steps: firstly, a glass cell is placed on the material in order to isolate a part of its surface, and the VOCs are left to diffuse from the material to the air enclosed in the cell. When the VOCs concentration stabilizes, i.e., when material/air equilibrium is reached (Bourdin et al., 2014), a solid phase microextraction (SPME) fiber is introduced in the glass cell through a septum to sample emitted VOCs. Then, the SPME fiber is desorbed in the injector of a gas chromatograph (GC) coupled with mass spectrometer (MS) and flame ionization detector (FID; Varian, France) for identification and quantification of VOCs. The analytical procedure is detailed elsewhere (Bourdin and Desauziers, 2014). Both VOCs screening and specific analysis of formaldehyde and acetaldehyde, which are classified as carcinogen mutagenic and reprotoxic (CMR) substances, were performed (Chemical Risk Prevention Unit [CNRS], 2015). A polydimethylsiloxane-divinylbenzene-Carboxen fiber (PDMS/DVB/CAR, 50/30 µm) was selected for VOCs screening whereas a polydimethylsiloxane-divinylbenzene (PDMS/DVB, 65 µm) fiber impregnated with O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine hydrochloride (PFBHA) (Fluka, Switzerland) was used for formaldehyde and acetaldehyde (Koziel et al., 2001; Bourdin and Desauziers, 2014). The SPME fibers were purchased from Supelco (United States). A sampling temperature of 80°C was tested to simulate extreme car interior conditions. The extraction time was fixed at 5 min.

# Quantitative Analysis

The methodology described above allows for determining the concentration (in $µg.m^{-3}$) of VOCs at the material/air interface. That concentration is related to the emission rate of the considered substance by the first Fick law of diffusion under steady state conditions (Wittkowski et al., 1992). For the screening analysis using a PDMS-DVB-CAR fiber, VOCs were quantified as toluene equivalent using an FID response since it is proportional to the effective carbon atoms number in the molecule (Fedoruk and Kerger, 2003). Furfural and 2-furanmethanol, compounds specific to hemp fibers and listed as CMR substances (Chemical Risk Prevention Unit [CNRS], 2015), as well as formaldehyde and acetaldehyde, were specifically quantified as described in a previous paper (Badji et al., 2018). Standard gases of formaldehyde and acetaldehyde were generated by a permeation device (Badji et al., 2018). For the other standard VOCs (toluene, furfural, and 2-furanmethanol), a continuous syringe injection method was used, as described elsewhere (Nicolle et al., 2008; Desauziers, 2004). The detection limit and quantification limit are around 8 and 23 $µg.m^{-3}$, respectively for

<figure><img src="image_313.png" /><figcaption>FIGURE 1 | Under windshield glass exposure racks.</figcaption></figure>
<figure><img src="image_314.png" /><figcaption>**FIGURE 2** | PP degradation global scheme (Badji, 2017; from Bernstein et al. (2008)).</figcaption></figure>

all compounds and the repeatability (relative standard deviation) is about 3% for three replicates.

# RESULTS AND DISCUSSION

## Polypropylene Oxidation

Some emitted VOCs were issued from the polymer degradation: long-chain aliphatic hydrocarbons and oxygenated products (linear ketones, aldehydes, and carboxylic acids). Acetic acid, acetone, and 2,4-pentanedione were the main compounds emitted by weathered PP. Some pathways are proposed in the literature to explain the formation of molecules containing a carbonyl functional group. Their mechanistic formation is found in literature (François-Heude et al., 2013; François-Heude et al., 2015). Mainly radical reactions lead to intermediate tertiary alkoxy radicals and their β-scission induces the previously identified carbonyl products (Figure 2). 2,4-pentanedione can result from the oxidation of methylketone issued from polymer chain reaction with unstable hydroperoxide. Moreover, 4-hydroxy-4-methyl-2-pentanone was also detected as high-level ketone (65 ± 13 and 82 ± 25 µg·m⁻³ for non-weathered and for one-year weathered PP, respectively (Badji et al., 2018). It has been proposed that it originates from the same methyl ketone precursor. Indeed, the hydroxyl formation resulting from the alkoxy radical reaction with hydrogen followed by scission could form 4-hydroxy-4-methyl-2-pentanone.

Formaldehyde and acetaldehyde were also released by the polymer and biocomposites. Their levels increased with the time of exposure. A polymer degradation way, similar to previous oxygenated chemicals pathway, could explain acetaldehyde generation with secondary alkoxy radical initiator responsible for this low molecular compound formation. Moreover, formaldehyde generation is reported according to the mechanism of Hoff and Jacobsson, which consists of the oxidation of primary alkyl radicals (Hoff and Jacobsson, 1982).

Alcohols, resulting from polymer degradation, could arise from intermediate alkoxy radicals. However, abstracts

of a hydrogen from another molecule yields an hydroxyl group in tertiary carbon rather than a carbonyl group (Bernstein et al., 2008).

## Cellulose and Hemicelluloses
### Degradation

#### Primary Decomposition

Two specifically quantified furan derivatives, furfural and 2-furanmethanol, were emitted at 1611 ± 20 and 2319 ± 176 µg·m⁻³, respectively by non-weathered PP30. Also, 5-methylfurfural (660 ± 30 µg·m⁻³), 5-methyl-2(3H)-furanone (40 ± 14 µg·m⁻³), furfuryl formate (38 ± 4 µg·m⁻³), and furfuryl acetate (43 ± 4 µg·m⁻³) evolved from biocomposites at the initial state. Apart from the last two compounds, these low molecular weight products were evidenced to be generated by holocellulose sequential degradation (Shen and Gu, 2009; Binder et al., 2010; Mäki-Arvela et al., 2012; Al-Shaal et al., 2015). Figure 3 shows the formation pathways of degradation products identified in this study and issued from the carbohydrate part of hemp fibers. The nominated products were those identified as VOCs issued from biocomposites. The carbohydrates' degradation under high temperature involves the depolymerization of polysaccharides by the glycosidic bonds cleavage between D-glucose units (Wang et al., 2012). This process is followed by dehydrations, leading to D-glucopyranose and D-xylofuranose formation. The formation of 2- or 5-substituted furans is generally explained to occur via glucopyranose ring-opening pathway with acyclic forms such as hexoses and pentoses intermediates (Sanders et al., 2003; Binder et al., 2010). The further cyclization of theseoses leads to the furans formation. Primary subsequent dehydration steps produced specifically followed furfural and 2-furanmethanol emitted at high concentrations by non-weathered biocomposites. In this mechanistic scheme, other cyclic molecules were derived from hydroxymethylfurfural, which was not detected in the conditions of this study. Otherwise, the generation of
<figure><img src="image_315.png" /><figcaption>**FIGURE 3** | Primary holocellulose decomposition products and their dehydrated derivatives through funneling pathways (Shen and Gu, 2009; Binder et al., 2010; Mäki-Arvela et al., 2012; Al-Shaal et al., 2015; Badji, 2017).</figcaption></figure>
<figure><img src="image_316.png" /><figcaption>**FIGURE 4** | Glucose and amino acid interaction (R, amino acid side group) [Badji, 2017; from Fennema (1996)].</figcaption></figure>

levoglucosenone (97 ± 4 µg·m⁻³) derivative does not need the sugar ring-opening.

The products issued from the carbohydrate primary decomposition were mainly emitted by biocomposites at a non-weathered state. It has been supposed that generation could also be favored by Maillard reactions for which non-elevated temperatures (almost 100°C) are required (Newton et al., 2012) (chosen sampling temperature and those found in exposure racks do not exceed 91°C), contrary to the pyrolysis method. Indeed, until now, Maillard reactions have not supported the degradation pathways of vegetal fibers. However, either 1,2- or 2,3-enolization of the Amadori compound, previously mentioned in the introductory part, rising from aldoses such as glucose could effectively lead to furfural and hydroxymethylfurfural. Indeed, these compounds were already explained to originate from sugar-containing food, such as lactose, through Maillard reactions (Newton et al., 2012). But the same mechanism could justify the formation of the products detected here. Also, further intermediate dicarbonyls (reductones) formed after intra-rearrangement (enolization) are responsible for the autocatalytic character of the Maillard reaction (Figure 4). Moreover, as mentioned in the introductory part, proteins present in fibers could allow the glycosylamine precursor formation required for obtaining advanced Maillard reaction products. Otherwise, their presence is demonstrated by the detection of pyrazines

emitted by biocomposites (methylpyrazine and N-acetyl-4(H)-pyridine at 25 ± 2 and 38 ± 4 µg·m⁻³, respectively for PP30). These secondary products of Strecker degradation are due to aminoketones condensation.

Contrary to other compounds, the formation of furfuryl formate and furfuryl acetate (total concentration of 81 ± 8 µg·m⁻³) aroused from non-weathered PP30 composite has not been reported in the literature. Here, it is suggested that they result from the interaction between the hydroxy functional groups of 2-furanmethanol and formaldehyde and acetaldehyde, respectively (Figure 3). Formaldehyde and acetaldehyde could also evolve from the Strecker degradation (Hodge et al., 1972; Newton et al., 2012) by β-scission. Indeed, for biocomposites, lots of aliphatic ketones and aldehydes such as 1-hydroxy-2-propanone, 1-acetyloxy-2-propanone, and nonanal are emitted at the highest levels of their chemical family: 420 ± 81, 366 ± 11, and 160 ± 28 µg·m⁻³, respectively, for unaged PP30. They were identified as hemp fibers by-products at a non-weathered state. These by-products could be linked to the reaction between amino acids and two-carbonyl compounds.

## Secondary Decomposition

After weathering, mainly methyl substituted furanones deriving from carbohydrates were formed. They represented 13% of the level of ketones released by PP30 after one year of weathering,
whereas they only accounted for 8% of ketones by-products emitted by non-weathered PP30. Moreover, contrary to a non-weathered state, only furans compounds containing at least one substitution in 3 and 4 positions were identified after weathering. In addition, contrary to 2- and 5-substituted furanones presented in **Figure 3**, the explanation of 3- or 4-substituted furanones

issued from vegetal fibers decomposition has not yet been reported in the literature. The proposed reactions featured in **Figure 5** involve the interaction between functional groups of identified volatile products. Substances that are designed by their names in **Figure 5** correspond to substances detected in this work. The first reaction (1) implies a radical attack in α position of

<figure><img src="image_317.png" /></figure>
<figure><img src="image_318.png" /><figcaption>**FIGURE 5** | Proposed reaction pathways of furan derivatives.</figcaption></figure>
two identical propionic acid by-products, whose levels increased from 39 ± 4 to 839 ± 75 µg·m⁻³ and 56 ± 16 to 1403 ± 3 µg·m⁻³ for PP10 and PP30, respectively, via a photo-chemical method caused by ultraviolet (UV) rays. It is followed by the dehydration of the generated intermediate symmetrical molecule leading to an intramolecular cyclization giving 3,4-dimethyl-2,5-furanedione (118 ± 32 µg·m⁻³ for weathered PP30).

The reaction (2) occurs through the establishment of a keto-enolization equilibrium thermodynamically driven between the keto and enol forms of 4-hydroxy-4-methyl-2-pentanone (Figure 5). Moreover, this ketone was detected at an extremely high concentration after weathering (until almost 3000 µg·m⁻³ for PP30 after 12 months), especially for biocomposites. Then, the attack of the enone form via C=C hydroformylation by carbon monoxide leads to an instable compound formation. Its further hydrolysis induces a cyclopropane ring-opening. Thus, these two previous steps lead to the functionalization of a formic acid group. Then, two successive dehydrations firstly induce a cyclization into 2-furanone structure. After, the dehydroxylation in the 3-position induces a double bond formation to generate 2,4,4-trimethylbut-2-enolide. This volatile compound was emitted at the highest concentration of the 2-furanones group after one year of weathering. Indeed, since the group of 2-furanones products was emitted at 3285 ± 666 µg·m⁻³ by PP30 weathered for one year, 2,4,4-trimethylbut-2-enolide accounted for almost 40% (1314 ± 30 µg·m⁻³) for PP30 weathered for one year. This can be explained by the extremely high concentration of the 4-hydroxy-4-methyl-2-pentanone reactant previously mentioned, giving way to the formation of 2,4,4-trimethylbut-2-enolide.

1-(2,4-dimethyl-furan-3-yl)-ethanone, whose generation (1063 ± 243 µg·m⁻³ for PP30 and 1807 ± 149 µg·m⁻³ for PP10) is explained in pathway (3) of Figure 5, implies the reaction between propionic acid and 2,4-pentanedione, two volatile compounds emitted in high quantities. Indeed, propionic acid was emitted at almost 800 and 1400 µg·m⁻³ for PP10 and PP30, respectively, and a concentration of almost 7300 µg·m⁻³ of the 2,4-pentanedione was recorded for the two biocomposites after one year. The highly reactive C = C formed through keto-enolization tautomerism of propionic acid is opened by C3 of the diketone. Then, a further keto-enolization of the intermediate compound hydroxydiketone derivative is established and precedes dehydrations occurring in the final stage.

As regards reaction (4.1) shown in Figure 5, the esterification of crotonic acid favored by the condensation of ethanol hydrate hydroxyl group, a molecule easily generated from acetaldehyde hydration on crotonic acid, is followed by the removal of a water molecule. The C–C double bond initially present is opened after cyclization. This produces a 4-hydroxy-4,5-dimethyl-2-furanone. However, as it is difficult for the possible further dehydrogenation process to occur, the reaction (4.2) is an alternative to (4.1) that requires more energy than (4.2). This generates the previously explained structure (4-hydroxy-4,5-dimethyl-2-furanone) at the final stage. A similar esterification way of the diketone intermediate product, followed by a cyclization and dehydration, could explain its formation.

The same precursors as found in reaction (2) may be responsible for the 5-hydroxy-3,3,5-trimethyl-2-furanone formation [pathway (5) of Figure 5]. Indeed, the dehydration and hydroformylation of the methylpentanone due to its reactions with CO and O₂ lead to methyl substituted levulinic acid generation, a well-known biomass derivative (Al-Shaal et al., 2015), that finally cyclizes after its keto-enolization.

Some of these reactions may require high energy conditions to occur. However, the biomass inorganic part contains metals which could catalyze these reactions (Nowakowski and Jones, 2008).

## Lignin Degradation
Primary Decomposition

Two methoxy-substituted phenols, vanillin and 4-vinylguaiacol, were emitted by non-weathered biocomposites. These two compounds are thought to originate from a primary decomposition of lignin favored in the heating conditions of ferulic acid, a well-known by-product evolving from lignin degradation, but not identified in this study (Coghe et al., 2004; Peleg et al., 1992).

Firstly, decarboxylation of ferulic acid may cause the formation of vinylguaiacol through (1.1) pathway (Figure 6; Coghe et al., 2004). Indeed, it is reported that temperatures ranging from 100 to 250°C (including the process temperature) cause severe damage to natural fibers' chemical structure through depolymerization, dehydration, or decarboxylation (Gassan and Bledzki, 2001). Vanillin is known to originate from the oxidation of 4-vinylguaiacol issued from lignin (1.2). The literature also proposed vanillin arises through the hydrolysis of the ferulic acid by-product (2.1) (Peleg et al., 1992). A further deacetylation could induce the formation of vanillin (2.2). This pathway could occur more easily than the vinylguaiacol or eugenol oxidation. Indeed, even if the decarboxylation consists in a naturally occurring step, the oxidation of carbon-carbon double bond must be catalyzed. Moreover, it has been shown that (2) pathways preferentially

<figure><img src="image_319.png" /><figcaption>FIGURE 6 | Lignin primary by-products decomposition.</figcaption></figure>
occur for obtaining vanillin than (1) ones (Peleg et al., 1992). Otherwise, the presence of metalloproteins containing iron, copper, and manganese might catalyze the by-products formation (Pollegioni et al., 2015).

## Secondary Decomposition

3,5-dimethylphenol (3,5-xylenol) was continuously emitted by biocomposites during the weathering. It rose from $94 \pm 30 \ \mu g \cdot m^{-3}$ after 1 month to $471 \pm 75 \ \mu g \cdot m^{-3}$ (PP30) after 12 months of exposition for PP30. At high temperatures, these alkylated phenols are formed by C-O radical cleavage of the methoxy group and further coupling of phenolic radical with the methyl radical group (Wittkowski et al., 1992). However, alkylphenols can appear easily only under pyrolysis conditions of lignin allowing alkylation. In our study, the temperature conditions are not favorable enough to trigger methylation. Nevertheless, as discussed previously, several factors could still contribute to alkylphenols sourcing. Indeed, brown and white-root fungi are recognized to be able to demethoxylize lignin (Lopretti et al., 1998). Moreover, UV radiation leading to demethoxylation (Hon and Chang, 1984; Srinivas and Pandey, 2012) may explain the formation of xylenol emitted only once biocomposites were exposed to climatic conditions. In this work, it has been assumed that this abstraction can give way to combinations between methyl radicals issued from the demethylation of lignin allowed by O-demethylase enzymes active before the hemp fibers process (Peng et al., 2002) and phenol radical. Moreover, enzymes present in lignin and included in proteins could play the role of natural biocatalysts of these reactions before the process of biocomposites (Pollegioni et al., 2015). In addition, the retting process could favor micro-organisms formation, thereby accelerating by-products generation.

## CONCLUSION

Since biocomposites are becoming more and more integrated in vehicles, knowledge about their aging and related mechanisms is needed. Therefore, the aim of this work was to rely on the structure of VOCs issued from non-weathered and under-glass-weathered PP and hemp fibers reinforced biocomposites to understand their degradation pathways. Reaction schemes were proposed according to volatile products that were identified in this study accordingly to an original and non-destructive sampling method.

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## DATA AVAILABILITY STATEMENT

The datasets generated for this study are available on request to the corresponding author.

## AUTHOR CONTRIBUTIONS

CB was the head of the whole project and drafted the manuscript. J-MS gave his expertise on the chemical pathways determination. HG helped for the weathering experiments. JB helped for VOCs measurements. AB and J-CB supervised the hemp fiber composite design and fabrication. VD was expert for the whole projet, designing it and supervising the COVs measurements. All the authors read and approved the manuscript.

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**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Badji, Sotiropoulos, Beigbeder, Garay, Bergeret, Bénézet and Desauziers. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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# Corrigendum: Under Glass Weathering of Hemp Fibers Reinforced Polypropylene Biocomposites: Degradation Mechanisms Based on Emitted Volatile Organic Compounds

**OPEN ACCESS**

**Approved by:**
Frontiers Editorial Office,
Frontiers Media SA, Switzerland

**\*Correspondence:**
Valérie Desauziers
valerie.desauziers@mines-ales.fr

**Specialty section:**
This article was submitted to Polymeric and Composite Materials, a section of the journal Frontiers in Materials

**Received:** 16 July 2020
**Accepted:** 17 July 2020
**Published:** 06 November 2020

**Citation:**
Badji C, Sotiropoulos J-M, Beigbeder J, Garay H, Bergeret A, Bénézet J-C and Desauziers V (2020) Corrigendum: Under Glass Weathering of Hemp Fibers Reinforced Polypropylene Biocomposites: Degradation Mechanisms Based on Emitted Volatile Organic Compounds. Front. Mater. 7:266. doi: 10.3389/fmats.2020.00266

Célia Badji<fnref n="1" />,², Jean-Marc Sotiropoulos³, Joana Beigbeder<fnref n="1" />, Hélène Garay<fnref n="1" />, Anne Bergeret², Jean-Charles Bénézet² and Valérie Desauziers<fnref n="1" />*

**Keywords:** hemp fiber, ageing, VOCs, oxidation, dehydration

## A Corrigendum on

Under Glass Weathering of Hemp Fibers Reinforced Polypropylene Biocomposites: Degradation Mechanisms Based on Emitted Volatile Organic Compounds

by Badji, C., Sotiropoulos, J.-M., Beigbeder, J., Garay, H., Bergeret, A., Bénézet, J.-C., et al. (2020). Front. Mater. 7:162. doi: 10.3389/fmats.2020.00162

In the published article, there was an error in affiliations 2 and 3.

**Affiliation 2:** Instead of "IPREM, Université de Pau et des Pays de l'Adour, E2S UPPA, CNRS, Pau, France," it should be "PCH, IMT Mines Ales, Ales, France."

**Affiliation 3:** Instead of "PCH, IMT Mines Ales, Ales, France," it should be "IPREM, Université de Pau et des Pays de l'Adour, E2S UPPA, CNRS, Pau, France."

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated

Copyright © 2020 Badji, Sotiropoulos, Beigbeder, Garay, Bergeret, Bénézet and Desauziers. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

<footnote n="1">¹IPREM, IMT Mines Ales, Université de Pau et des Pays de l'Adour, E2S UPPA, CNRS, Pau, France, ²PCH, IMT Mines Ales, Ales, France, ³IPREM, Université de Pau et des Pays de l'Adour, E2S UPPA, CNRS, Pau, France</footnote>
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# Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography Characterization

Maria C. Quintana<fnref n="1" />*, Patricia M. Frontini<fnref n="1" />, Aitor Arriaga², Bernhard Plank³ and Zoltan Major⁴

OPEN ACCESS

**Edited by:**

Emilia Morallon,
University of Alicante, Spain

**Reviewed by:**

Jyrki Vuorinen,
Tampere University of
Technology, Finland
Antonio Greco,
University of Salento, Italy

**\*Correspondence:**

Maria C. Quintana
cquintana@fi.mdp.edu.ar

**Specialty section:**

This article was submitted to
Polymeric and Composite Materials,
a section of the journal
Frontiers in Materials

Received: 23 March 2020

Accepted: 07 May 2020

Published: 16 July 2020

**Citation:**

Quintana MC, Frontini PM, Arriaga A, Plank B and Major Z (2020) Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography Characterization. Front. Mater. 7:169. doi: 10.3389/fmats.2020.00169

This work evaluates and compares the accuracy of different fiber orientation prediction models for a short fiber reinforced injection molded Venturi-shaped part which displays variable thickness. The experimental characterization of the specimen fiber orientation distribution (FOD) was carried out by the micro computed tomography technique (micro-CT). The computational study of fiber orientation predictions was performed using Moldex3D. All the possible combinations of the Folgar-Tucker (FT) and improved Anisotropic Rotary Diffusion (iARD) rotary diffusion models and the Hybrid (Hyb), Orthotropic (ORE), and Invariant Based Optimal Fitting (IBOF) closure approximations were considered. The relevance of the Retardant Principal Rate (RPR) model on predictions results was also evaluated. The values of the fiber-fiber (Ci), matrix-fiber (Cm) interaction coefficients and the alpha-RPR parameter were varied in a significant range in order to find the set of parameters that better fits the experimental fiber orientation data. The parameters' sensitivity effect over the second order orientation tensor components was quantified via the Analysis of Variance (ANOVA) statistical method. The experimental micro-CT results show an increase in the fiber orientation degree at the specimen constriction region due to the narrowed cavity and the Venturi effect. The comparison of the experimental and predicted orientation profiles demonstrates that the predictions of the iARD model, in combination with the IBOF closure approximation, are the most accurate for the case studied. However, simulations fail to estimate the change in orientation caused by variable thickness and section. ANOVA results prove that the orientation tensor component in the flow direction (a₁₁) is more sensitive to changes in alpha-RPR and Ci coefficient, while the perpendicular components (a₂₂, a₃₃) are also

<footnote n="1">¹Instituto de Investigaciones en Ciencia y Tecnología de Materiales (INTEMA), Universidad Nacional de Mar del Plata, Mar del Plata, Argentina, ²Leartiker-Lea Artibai Ikastetxea, Markina-Xemein, Spain, ³Technology & Environmental Sciences Department, University of Applied Sciences Upper Austria, Wels, Austria, ⁴Institut für Polymer Product Engineering (IPPE), Johannes Kepler Universität Linz, Linz, Austria</footnote>
significantly affected by Cm. From the predictive error analysis it is seen that the optimal parameters set to capture the orientation state of the specimen is: (i) for the FT model, Ci = 0.005, alpha-RPR = 0.7 and (ii) for the iARD model, Ci = 0.005, Cm = 0.2, and alpha-RPR = 0.7.

**Keywords:** short-fiber composites, micro-CT characterization, injection molding simulation, rotary diffusion models, closure approximations, experimental validation

## INTRODUCTION

Fiber orientation distribution (FOD) prediction consists of determining the degree of fiber alignment as a function of the location through the part. The state of fiber orientation depends upon a molten polymer fluid dynamic coupled with the movement of the fibers in polymer suspension. Thus, both fiber-fiber and polymer-fiber interactions must be taken into account in a pertinent analysis. The models that predict fiber orientation state in concentrated suspensions incorporate the effect of the interaction between fibers as a rotary diffusion term. The Folgar-Tucker model (FT) (Folgar and Tucker, 1984) considers an isotropic rotary diffusion term. The Anisotropic Rotary Diffusion (ARD) models and their improvements (iARD) (Wang et al., 2008; Phelps and Tucker, 2009; Tseng et al., 2016) define an anisotropic rotary diffusion term. On the other hand, the Retardant principal Rate model (RPR) (Tseng et al., 2016) and the Reduced Strain Closure (RSC) (Wang et al., 2008) account for the quick evolution of the FT model and correct it.

Another aspect concerning prediction approaches arises from the use of tensors to describe fiber orientation states (Advani and Tucker, 1987). The evolution equation of the fiber orientation models involves a fourth-order orientation tensor which must be approximated in a mathematically closed expression in order to compute fiber orientation data. A complete summary of existing closure approximations can be found in Zheng et al. (2011). The most commonly used closure approximations are the Hybrid (Hyb) (Advani and Tucker, 1990), the Orthotropic family or Eigenvalue Based Optimal Fitting (EBOF) (Cintra and Tucker, 1995)-among them the denominated ORE-and the Invariant Based Optimal Fitting (IBOF) (Chung and Kwon, 2002).

Most fiber orientation experimental validation works available in the literature mainly focus on the use of two analytical geometries: the center-gated disk and the end-gated plate, which are uniform and display well-known flow patterns (Bay and Tucker, 1992; Gupta and Wang, 1993; Greene and Wilkes, 1997; Papathanasiou, 1997; Larsen, 2000). Two exceptions are found in Kleindel et al. (2015) and Tseng et al. (2018), which use a complex thick-walled piece and a traction bar with a welding line, respectively. Besides, in the past few years, some valuable efforts have been made to develop new closure approximations for the fourth order orientation tensor (Montgomery-Smith et al., 2011; Kuzmin, 2018) as well as to compare the accuracy of the existing mathematically closed expressions (Chung and Kwon, 2000; Wang and Jin, 2010). In these articles, the mentioned typical analytical geometries are also chosen for validation purposes.

Regarding the experimental characterization of the fiber orientation, the typical method used to determine their distribution is a two-dimensional technique based on optical microscopy, which is called the method of ellipses (MoE). The MoE implies the sectioning and polishing of the samples, i.e., it is a destructive technique, followed by optical microscopy or scanning electron microscopy (SEM) in order to determine the in-plane and out-of-plane angles of the projected fibers from the surface characterization. This method has certain limitations, such as the ambiguity in determining the 3D fiber orientation and the difficulty in achieving a proper FOD characterization over a representative area/volume of the material (McGee and McCullough, 1984; Vélez-Garcia, 2012; Sharma et al., 2018; Hanhan et al., 2019). Alternatively, in recent years the application of three-dimensional techniques, such as micro-CT scanning, have become really appealing for non-destructively characterizing composites' microstructural features (Salaberger et al., 2011; Emerson et al., 2017; Hanhan et al., 2019). However, there are few studies using these techniques to validate predictions given by simulation (Kleindel et al., 2015; Tseng et al., 2018).

Taking into account the scope of the previous contributions, the objective of this work is to validate the most relevant fiber orientation models and closure approximations in a specimen different from those already studied-but with characteristics that can be extrapolated to many injected parts-using the novel experimental micro-CT technique to test the accuracy of the predictions. Specifically, the injected part studied here consists of a Venturi-shaped tube that displays variable thickness. The specimen is made of polyamide and it is reinforced with short glass fiber (40 wt%).

This work presents: (i) a brief overview of the fiber orientation prediction models and closure approximations deemed to be evaluated (these being the FT, iARD, and RPR models, and the Hyb, ORE and IBOF closures); (ii) a description of the experimentally measured fiber orientation distribution; (iii) a computational study performed using the injection molding simulation software Moldex3D R.13 to explore the effect of the models and closures on fiber orientation predictions; (iv) a statistical study via the Analysis of Variance (ANOVA) technique to investigate the effect of the models parameters (fiber-fiber Ci and matrix-fiber Cm interaction coefficients and alpha-RPR parameter) on the predicted components of the second order orientation tensor; and (v) a quantitative determination of the FT and iARD prediction errors.
## BACKGROUND

The hydrodynamic effect of the fluid flow over the motion of an infinite aspect ratio particle was first described by Jeffery (2012). This theory applies to dilute suspensions but it has been shown to provide practical qualitative agreement with simple shear flow experiments under certain conditions. Folgar and Tucker (1984) have considered the evolution of the fiber orientation state of non-dilute fiber suspensions as a diffusive process, adding to the theoretical model of Jeffery's Hydrodynamic an isotropic rotary diffusion term to model the randomizing effect of the interaction between fibers. The isotropic rotary diffusion is proportional to the scalar rate of deformation, being the constant of proportionality to a scalar parameter named the interaction coefficient (Ci), adjusted to fit with experimental data. Due to its acceptable accuracy for the prediction of the fiber orientation state in semi-concentrated suspensions, the Folgar-Tucker model (FT) has been the most frequently used for the estimation of the local fiber orientation distribution in the simulation of SFRC so far.

However, the FT model does not match all of the aspects of experimental discontinuous fiber orientation data. For instance, in concentrated suspensions fibers tend to align more slowly with respect to the strain rate than the models based on the Jeffery's equation predict, especially for composites with long discontinuous fibers (Wang et al., 2008; Phelps and Tucker, 2009; Tseng et al., 2016). Wang et al. (2008) introduced the reduced-strain closure (RSC) model, which slows the orientation kinetics in order to achieve better agreement between the experiments and predictions. Phelps and Tucker (2009) developed a fiber orientation model that incorporates an anisotropic rotary diffusion term, namely the Anisotropic Rotary diffusion model (ARD). In the ARD model, the diffusivity is assumed to depend on a second-order space tensor which in turn is a function of the orientation state and the deformation rate. Nowadays, the FT and ARD-RSC models are available in most commercial injection molding simulation software. Some years ago, Tseng et al. (2016) proposed and implemented on Moldex3D an approach named the improved Anisotropic Rotary diffusion (iARD), which also considers anisotropic fiber diffusion and incorporates the effect of the fiber-matrix interaction (like the ARD model) and the slowing down of the orientation through the Retardant Principal Rate model (RPR). The iARD-RPR model has been proved to be suitable for both short and long fiber reinforced composites (Tseng et al., 2016).

When using the tensor description of the fiber orientation state proposed by Advani and Tucker (1987) instead of the probability distribution function (DFC), all the information regarding fiber orientation is represented by the components of a second-order momentum tensor, named the orientation tensor. The mathematical expression for the advection of the second-order orientation tensor involves a fourth-order orientation tensor that has to be defined in a closed form in order to compute fiber data. Then, a closure approximation is defined as an expression of the fourth-order orientation tensor as a function of the second-order orientation tensor. Advani and Tucker (1990) proposed the so-called Hybrid closure

approximation (Hyb), which has been proven to be exact when the fibers are in both random and perfect aligned states, but that accelerates the orientation in transient shearing flows (Zheng et al., 2011). A family of closure approximations called orthotropic or Eigenvalue Based Optimal Fitting closures (EBOF) was developed by Cintra and Tucker (1995). Among them, the version called Orthotropic Fitted Closure Approximation (ORE) improved the non-physical oscillations for low interaction coefficients. Although the EBOF closures adequately predict fiber orientation in most simple flows, its implementation demands much computational time. Later, Chung and Kwon (2000) developed the Invariant Based Optimal Fitting closure approximation (IBOF) whose accuracy is as good as EBOF but requires less computational time to obtain a solution. The Hyb, ORE, and IBOF closure approximations are already implemented in Moldex3D.

## Fiber Orientation and Rotary Diffusion Models

The orientation of a single fiber is determinate by a unit vector named p, which is defined by the in-plane (φ) and out-of-plane (θ) fiber angles. The most general way to describe the orientation state of a group of fibers is given by the probability density distribution function (ψ). The function ψ represents the probability of finding a fiber over the space between (φ, θ) and (φ+dφ, θ+dθ).

Given that the time variation of ψ requires much computational time for its calculation, the tensor description of fiber orientation proposed in Advani and Tucker (1987) is generally implemented in simulations. The second-order orientation tensor (A) is defined so that the probability of a fiber being oriented within an angular range dp of the direction p is equal to ψ(p)dp, Equation 1.

$$A = \int \psi(p) p p dp \quad (1)$$

The second order orientation tensor can be expressed with a matrix that meets the following conditions: it is symmetric, and the sum of its diagonal components are 1.

### The Folgar-Tucker Model

The evolution equation of the 2nd order orientation tensor can be expressed as the contribution of a hydrodynamic (h) and a diffusive term (d), Equation 2. In the so-called standard Folgar-Tucker model, the first term is represented by the Jeffery's Hydrodynamic (H) model, Equation 3 and the second by the Folgar-Tucker isotropic rotary diffusion (IRD) model, Equation 4.

$$\dot{\mathbf{A}} = \mathbf{A}^h + \mathbf{A}^d \quad (2)$$

$$\dot{\mathbf{A}}^H = (W \cdot \mathbf{A} - \mathbf{A} \cdot W) + \lambda (D \cdot \mathbf{A} + \mathbf{A} \cdot D - 2A_4 : D) \quad (3)$$

$$\mathbf{A}^{IRD} = 2\gamma \mathbf{C}_i (I - 3\mathbf{A}) \quad (4)$$

Where, $\dot{\mathbf{A}}$ is the material derivative of the second order orientation tensor; $\lambda$ is a constant that depends on the geometry
of the fiber. In this work, $\lambda$ is the value corresponding to slender particles and is equal to 1; I is the unit tensor, and Ci is the fiber-fiber interaction coefficient.

W is the vorticity tensor and D is the rate of deformation tensor. They are defined from the velocity gradient tensor L:

$$L = \nabla v = W + D \quad (5)$$

$$W = \frac{1}{2}(L - L^T) \quad (6)$$

$$D = \frac{1}{2}(L + L^T) \quad (7)$$

A$_4$ is the fourth-order orientation tensor, also symmetric, defined as:

$$A_4 = \oint \psi(p)pppdp \quad (8)$$

## The iARD Model

The iARD model is formed by the contribution of the Jeffery Hydrodynamics model (H), Equation 3, the improved anisotropic rotary diffusion term (iARD), Equation 10 and the Retardant Principal Rate (RPR) model, Equation 13.]

$$\begin{gathered} \dot{A} = \dot{A}^H + \dot{A}^{iARD} (Ci, Cm) + \dot{A}^{RPR} (\alpha) \quad (9) \\ \dot{A}^{iARD} = \dot{\gamma} [2D_r - 2tr(D_r)A - 5D_r \cdot A - 5A \cdot D_r + 10A_4 : D_r] \quad (10) \end{gathered}$$

Where Ci and Cm are the fiber-fiber and matrix-fiber interaction coefficients and alpha is the RPR model parameter that indicates the slow-down fiber rotation behavior.

The iARD term is:

$$\begin{gathered} \dot{A}^{iARD} = \dot{\gamma} [2D_r - 2tr(D_r)A - 5D_r \cdot A - 5A \cdot D_r + 10A_4 : D_r] \quad (10) \\ \dot{D}_r = C_i(I - C_m \frac{D^2}{\|D^2\|}) \quad (11) \\ \|D^2\| = \sqrt{\frac{1}{2}D^2 : D^2} \quad (12) \end{gathered}$$

Where

$$D_r = C_i(I - C_m \frac{D^2}{\|D^2\|}) \quad (11)$$

$$\|D^2\| = \sqrt{\frac{1}{2}D^2 : D^2} \quad (12)$$

The RPR term is:

$$\dot{A}^{RPR} = -R \cdot \dot{A}^{IOK} \cdot R^T \quad (13)$$

$$\dot{A}_{ii}^{IOK} = \alpha \lambda_i i, j, k = 1, 2, 3 \quad (14)$$

Where $R = [e_1, e_2, e_3]$ is the rotation matrix; $R^T$ is its transpose; $\lambda_i(\lambda_1 \ge \lambda_2 \ge \lambda_3)$ are the eigenvalues of $\Lambda$ and $\dot{A}$ is the material derivative of a particular diagonal tensor (IOK is for intrinsic orientation kinetics).

## Closure Approximations

### Hybrid Closure Approximation (Hyb)

Hyb approximation (Advani and Tucker, 1990), Equation 15, is the hybrid from the Linear, Equation 16, and Quadratic, Equation 17, closures. In index notation, Aij and Aijkl represent

the second- and fourth-order orientation tensors, respectively, and Iij is the unit matrix.

$$\begin{align*} \tilde{A}_{ijkl}^{\text{hybrid}} & \approx (1-f)\tilde{A}_{ijkl}^{\text{linear}} + f\tilde{A}_{ijkl}^{\text{quadratic}} \\ f &= 1 - 27 \det(A_{ij}), \quad \text{for three dimensional orientation} \\ f &= 1 - 4 \det(A_{ij}), \quad \text{for planar orientation} \quad (15) \end{align*}$$

$$\begin{align} \tilde{A}_{ijkl}^{\text{linear}} &= -\frac{1}{35}(I_{ij}I_{kl} + I_{ik}I_{jl} + I_{il}I_{jk}) \tag{16} \\ &\quad +\frac{1}{7}(A_{ij}I_{kl} + A_{ik}I_{jl} + A_{il}I_{jk} + A_{kl}I_{ij} + A_{jl}I_{ik} + A_{jk}I_{il}) \nonumber \end{align}$$

$$\tilde{A}_{ijkl}^{\text{quadratic}} \approx A_{ij}A_{kl} \quad (17)$$

Since the Linear approximation has been proved to be exact for random orientations and the Quadratic closure is exact when the fibers are perfectly aligned, it is deduced that the hybrid closure will be exact when the fibers are in both random and perfect alignment states (Chung and Kwon, 2000; Wang and Jin, 2010). This model, however, tends to accelerate the orientation transients in transient shearing flows (Advani and Tucker, 1990). It has been demonstrated that Hyb closure approximation predictions are in a good agreement with experimental fiber orientation data when the value of the interaction coefficient is taken as 0.01 (Advani and Tucker, 1990; Wang and Jin, 2010).

## Orthotropic or Eigenvalue Based Optimal Fitting Closures Family (EBOF)

EBOF approximations assume that only three components of the fourth-order tensor are independent, based on the fact that in the second-order tensor only two of the diagonal components are independent variables (the sum of diagonal components is 1). The directional information of Aijkl is obtained from Aij, both tensors having the same principal axis (Zheng et al., 2011). Then, the three principal components of the fourth-order tensor are expressed as functions of the independent principal components of the second-order tensor, Equation 18. Here aij and aijkl represent the components of the second- and fourth-order tensors, respectively. The superscript p indicates that the components are principal.

$$\tilde{A}_{ijkl}^{\text{orthotropic}} = \begin{Bmatrix} \tilde{a}_{1111}^p \\ \tilde{a}_{2222}^p \\ \tilde{a}_{3333}^p \end{Bmatrix} = \begin{Bmatrix} f_1(a_{11}^p, a_{22}^p) \\ f_2(a_{11}^p, a_{22}^p) \\ f_3(a_{11}^p, a_{22}^p) \end{Bmatrix} \quad (18)$$

In Equation 18, the functions f1, f2, and f3 are determinate by matching predicted values of the second-order components with experimental ones in well-defined flow conditions. These coefficient functions will be different for the different orthotropic approximations.

Among the orthotropic approaches, the so-called ORF provides good results for a range of interaction coefficient values from 0.01 to 0.1. The ORL closure is used in a range of Ci from 0.001 to 0.01, while the Orthotropic fitted closure approximation named ORE corrects the non-physical oscillations for low interaction coefficients (Cintra and Tucker, 1995).
<figure><img src="image_322.png" /><figcaption>**FIGURE 1** | Specimen, regions of interest and micro-CT samples.</figcaption></figure>

<figure><img src="image_323.png" /><figcaption>**FIGURE 2** | Computational model.</figcaption></figure>

the measured CT-data. A complete description of the micro-CT technique and the calculation scheme is presented in Salaberger et al. (2011), Emerson et al. (2017), and Salaberger (2019).

# SIMULATION AND STATISTICAL CALCULATION

## Simulation Details

The mold filling and fiber orientation simulations were performed using Moldex3D R.13, see **Figure 2**. For this case, a 3D analysis was preferable over a 2.5D to capture the potential influence of variable thickness and the Venturi effect over the FOD. Auto tetrahedral 3-dimensional meshing of the model was performed using the Moldex3D Designer. This method

<table><caption>**TABLE 1** | Simulation trials for the evaluation of orientation models and closure approximations.</caption><thead><tr><th rowspan="2">Orientation model</th><th rowspan="2">Closure</th><th colspan="3">Parameter</th></tr><tr><th>Ci</th><th>Cm</th><th>alpha-RPR</th></tr></thead><tbody><tr><td>FT</td><td>Hyb-ORE-IBOF</td><td>0.01</td><td>-</td><td>0</td></tr><tr><td>iARD</td><td>Hyb-ORE-IBOF</td><td>0.01</td><td>0.99</td><td>0</td></tr></tbody></table>

is widely used by commercial simulation codes users due to tetrahedral meshes' ability to fit almost any complex geometry. Despite this, tetrahedral meshes possess some drawbacks, such as the large number of elements and the difficulty in controlling the element layer count of the whole part (it is not constant). To overcome this limitation, the highest meshing reliability level of the Moldex3D Designer with a small enough size of element was chosen to ensure a minimum of 5 elements in the thickness direction.

## Computational Study Details

The computational study was divided into two parts. The first part is the comparison of the experimental profiles with those obtained from all the possible combinations of the rotary diffusion models (FT and iARD) and the closure approximations (Hyb, ORE, and IBOF). The FOD was examined throughout the specimen (regions of interest) and through its thickness. The default values of the model parameters were set for these simulations (Ci = 0.01, Cm = 0.99, and α-RPR = 0). The summary is in **Table 1**. For the comparison, the optimal closure approximation was selected in terms of adjustment to the experimental results and the shorter time consumed. In the second part, the models parameters were varied to establish, via ANOVA, their influence over the fiber orientation tensor components and to calculate predictive errors. The summary is in **Table 2**.
## Statistical and Error Calculation Details

The sensitivity of the principal components of the 2nd-order orientation tensor (responses) as a function of the fiber model parameters listed in Table 2 (factors) was evaluated via the Analysis of Variance (ANOVA) method. The operation of the ANOVA technique broadly follows this scheme: in order to compare the means of the factors associated with their different levels, a measure of the response variation due to their different levels (Mean Square factor, MS-factor) is compared with a measurement of the response variation due to the error (Mean Square error, MS-error). If the MS-factor is significantly larger than the MS-error, it is concluded that the means associated with different levels of the factor are different. That factor then has an important influence over the response. In the ANOVA analysis, the P (%) represents the percentage of contribution of each term (factors and error) to the variation of the dependent variables.

The predictive errors of the FT and iARD models as functions of the parameters levels listed in Table 2 were calculated according to Equation 23.

$$RMSE = \sqrt{(a_i^{\text{prediction}} - a_i^{\text{exp erimental}})^2} \quad (23)$$

This is the Root Mean Squared Error (RMSE) computed from the difference in the predicted and experimental values of the principal components of the orientation tensor. From these results, the combination of parameters per model that lead to the lower prediction error was determined.

<table><caption>TABLE 2 | Simulation trials for ANOVA analysis.</caption><thead><tr><th rowspan="2">Orientation model</th><th rowspan="2">Closure</th><th colspan="7">Parameter</th></tr><tr><th colspan="3">Ci</th><th colspan="2">Cm</th><th colspan="3">alpha-RPR</th></tr></thead><tbody><tr><td>FT-RPR</td><td>IBOF</td><td>0.001</td><td>0.005</td><td>0.01</td><td>-</td><td>-</td><td>0</td><td>0.2</td><td>0.7</td><td>0.95</td></tr><tr><td>iARD-RPR</td><td>IBOF</td><td>0.001</td><td>0.005</td><td>0.01</td><td>0.2</td><td>0.99</td><td>0</td><td>0.2</td><td>0.7</td><td>0.95</td></tr></tbody></table>

## RESULTS AND DISCUSSION

### Experimental Fiber Orientation Description
Fiber Orientation in the Thickness Direction

Figure 3 shows the experimentally determined through-thickness fiber orientation distributions for the regions of interest along the specimen. The degree of fiber alignment in the MFD is indicated by the value of $a_{11}$, whereas $a_{22}$ and $a_{33}$ corresponds to the cross-flow and through-thickness fiber orientations, respectively.

It is observed that the part exhibits a gap-wise three-layered laminated structure which corresponds to the so-called shell-core-shell structure. The fibers in the shell layers are mainly aligned in the MFD, this implies high $a_{11}$ values and low $a_{22}$ values. The core layer, located approximately at the specimen mid-plane (z/H = 0.5) and between the shell layers, is characterized by a high cross-flow fiber orientation with high $a_{22}$ values and low $a_{11}$ values. Also, a fraction of the fibers aligned in the thickness direction can be observed in the core layer ($a_{33}$ value different from zero).

### Fiber Orientation Along the Specimen

The experimental results in Figure 3 reveal that, at the entrance and central regions, the distributions are essentially flat (the fibers remain parallel to the XY plane). Whereas, at the filling completion region, the portion of fibers aligned in the thickness direction is larger.

Furthermore, it can be seen from Figure 3 that the fiber alignment degree in the MFD changes after the fluid experiences the convergent and divergent transitions between R1 and R2 and between R2 and R3, respectively (Figure 1). In the convergent transition an increase in the $a_{11}$ component occurs, both in the shell and core layers (through-thickness averaged values from 0.74 to 0.85), while the remaining components decrease. Since the orientation in the MFD is governed by the shear flow, the increase in $a_{11}$ is associated with the increase of the fluid velocity caused by the Venturi effect and the increase in the shear rate due to the narrower cavity. On the contrary, in the divergent transition, $a_{11}$ decreases (through-thickness averaged values from 0.85 to 0.7) and the remaining components increase, specially $a_{33}$ (through-thickness averaged values from 0.03 to 0.1). This

<figure><img src="image_324.png" /><figcaption>FIGURE 3 | Experimental $a_{11}$, $a_{22}$, and $a_{33}$ orientation profiles at the regions of interest.</figcaption></figure>
<figure><img src="image_325.png" /><figcaption>**FIGURE 4** | Experimental and predicted $a_{11}$ and $a_{33}$ profiles at the entrance region (R1).</figcaption></figure>

<figure><img src="image_326.png" /><figcaption>**FIGURE 5** | Experimental and predicted $a_{11}$ and $a_{33}$ profiles at the central region (R2).</figcaption></figure>

<figure><img src="image_327.png" /><figcaption>**FIGURE 6** | Experimental and predicted $a_{11}$ and $a_{33}$ profiles at the filling completion region (R2).</figcaption></figure>

last can be attributed to the rotation of the fibers being located completely outside the XY plane at the cavity enlargement.

## Computational Study Results
### Comparisons Between Experimental and Predicted FODs

**Figures 4–6** show the comparison between the experimental and predicted orientation components along the flow and

through-thickness directions, i.e., $a_{11}$ and $a_{33}$, for each region of interest, respectively. Results are reported in terms of these components since they contain most of the qualitative information about the layered microstructure and, as it was demonstrated by the experimental results, they are more sensitive to flow and geometrical changes. Predicted profiles correspond to the combinations of rotary diffusion models, closure approximations and models parameters listed in
<figure><img src="image_328.png" /><figcaption>**FIGURE 7** | Experimental and predicted $a_{11}$, $a_{22}$, and $a_{33}$ orientation profiles at the central region.</figcaption></figure>

**Table 1.** The following observations arise from the analysis of the results.

### Comparison of fiber orientation in the thickness direction

The Hyb approximation leads to an over-estimation of the orientation in the flow direction. When using the Hyb closure, the $a_{11}$ predicted value is higher than the experimental one with respect to the prediction using ORE and IBOF closures for all the through-thickness profiles. The ORE and IBOF approximations estimate the orientation of the shell layers fairly closely to the experimental one; however, they over-predict the orientation of the core layer. The results provided by these closures are essentially the same, but the computational time consumed by the IBOF closure calculation is approximately half of the ORE closure. Due to its higher accuracy and computational efficiency, the IBOF has been selected as the optimum closure.

### Comparison of fiber orientation along the specimen

At the entrance and filling completion regions (Figures 4, 6), it is observed that, using the IBOF closure with the iARD model, there is a reasonably good correlation between the predicted and experimental values of all the principal orientation components. While using the IBOF closure in combination with the FT model, the results of $a_{11}$ correlate well, but $a_{22}$ is under-predicted and $a_{33}$ is over-predicted.

On the other hand, at the central region (Figure 5), although the simulations predict an increase of fluid velocity and an increase of the shear rate caused by the convergent transition, none of the orientation models predict the expected increase of the fiber alignment ($a_{11}$) that was observed experimentally. This discrepancy is more likely attributable to the estimation error of the remaining components, see Figure 7. As explained in the experimental section, when the wall thickness is narrowed, the fibers tend to align in the MFD; hence, the central region is characterized by a high value of $a_{11}$ and a very low $a_{22}$. However, simulation results for this region evidence that $a_{22}$ and $a_{33}$ are highly overestimated for both orientation models. So then, considering that the sum of the principal components is equal to $1 (a_{11}+a_{22}+a_{33} = 1)$, $a_{11}$ is consequently underestimated.

Taking into account the degree of adjustment to the experimental results, it follows that the iARD model in combination with the IBOF closure approximation are the most accurate for the case studied.

### ANOVA Analysis

The results of the ANOVA analysis are described in terms of the P(%), i.e., the percentage of contribution of each parameter (varied according to Table 2) and of the error to the variation of the principal components of the orientation tensor. These are: (i) FT model: P(%) over $a_{11}$, Ci = 10.35%, alpha-RPR = 88.01% and error = 1.64%; P(%) over $a_{22}$, Ci = 8.27%, alpha-RPR = 91.03% and error = 0.7%, and P(%) over $a_{33}$, Ci = 12.39%, alpha-RPR = 84.84% and error = 2.77%. (ii) iARD model: P(%) over $a_{11}$, Ci = 11.8%, Cm = 1.89%, alpha-RPR = 82.88%, and error = 3.42%; P(%) over $a_{22}$, Ci = 1.3%, Cm = 3.76%, alpha-RPR = 93.11%, and error = 1.84% and P(%) over $a_{33}$, Ci = 23.02%, Cm = 16.15%, alpha-RPR = 47.88%, and error = 12.95%.

Additionally, Figures 8, 9 show the principal effects and interactions of the same parameters over the component in the MFD. From the P(%) results, it is observed that for both models, the alpha-RPR parameter has the higher impact on the value of $a_{11}$, $a_{22}$, and $a_{33}$. However, in light of the results shown in the figures, it can be noted that this behavior is not valid for all the factors' levels; an abrupt change in the trend occurs from alpha-RPR = 0.7 due to a stronger interaction of the factors. Below this point, the effect of Ci and Cm can be considered practically independent of each other and of alpha-RPR. While above it, the interaction between the factors become significant and the orientation prediction is dominated by alpha-RPR.

With this in mind, a new ANOVA analysis was performed taking the alpha-RPR parameter up to 0.7, i.e., in the levels range in which the population means are not considerably different. The results are: (i) FT model: P(%) over $a_{11}$, Ci = 85.44%, alpha-RPR = 13.59%, and error = 0.97%; P(%) over $a_{22}$, Ci = 79.49%, alpha-RPR = 20.01%, and error = 0.5%, and P(%) over $a_{33}$, Ci = 88.92%, alpha-RPR = 9.47%, and error = 1.61%. (ii) iARD model: P(%) over $a_{11}$, Ci = 77.38%, Cm = 15.35%, alpha-RPR = 3.64%, and error = 3.62%; P(%) over $a_{22}$, Ci = 13.29%,
<figure><img src="image_329.png" /><figcaption>**FIGURE 8** | Main effects and interaction of the FT-RPR model parameters.</figcaption></figure>

<figure><img src="image_330.png" /><figcaption>**FIGURE 9** | Main effects and interaction of the iARD-RPR model parameters.</figcaption></figure>

$C_m = 44.46\%$, $\alpha$-RPR = 29.07%, and error = 13.17%; and $P(\%)$ over $a_{33}$, $C_i = 52.88\%$, $C_m = 39.85\%$, $\alpha$-RPR = 0.03%, and error = 7.24%.

It is observed now that: (i) for the FT model, the fiber-fiber interaction coefficient $C_i$ is the one that has the higher effect on all the principal orientation components; (ii) for the iARD model, as $C_i$ is the one with the higher impact on $a_{11}$, the matrix-fiber interaction coefficient $C_m$ significantly impacts the perpendicular components ($a_{22}$ and $a_{33}$) and (iii) the error on the estimation of $a_{22}$ and $a_{33}$ is confirmed to be considerable.

Finally, the effect of the factors is summarized as follows: (i) increasing $\alpha$-RPR produces a decrease in $a_{11}$ and an increase in $a_{22}$ and $a_{33}$. Above $\alpha$-RPR = 0.7 these variations become very pronounced; (ii) increasing $C_i$ produces a decrease in $a_{11}$ and an increase in $a_{22}$ and $a_{33}$; (iii) increasing $C_m$ produces a decrease in $a_{11}$ and $a_{22}$ and an increase in $a_{33}$. The amount (%) of these variations will depend upon the level of $\alpha$-RPR considered, being below $\alpha$-RPR = 0.7 those corresponding to the first ANOVA, and above $\alpha$-RPR = 0.7 those corresponding to the second ANOVA.

## Prediction Error Analysis

Figures 10, 11 show the prediction error of the FT and iARD models, respectively (computed from Equation 23) as

functions of the different model parameters. Based on the fact that there are certain deficiencies of the models in predicting the orientation changes that occur due to the specimen geometrical variations, and that the model parameters affected the principal orientation tensor components in a different way, the criterion used to find the optimal parameters set was that of trying to capture the best the global orientation state of the specimen. For this reason, $a_{11}$, $a_{22}$, and $a_{33}$ were analyzed by averaging their values across the thickness and the three regions of interest of the specimen. It should be noted that this analysis will not tell much about the precision of each model (best determined by comparison with the experimental profiles), since information from the predictions is lost locally.

Parameter values were chosen to minimize the error of each component without maximizing the error of the others. The optimal sets are as follows: (i) FT model, $C_i = 0.005$, $\alpha$-RPR = 0.7, and (ii) iARD model, $C_i = 0.005$, $C_m = 0.2$, and $\alpha$-RPR = 0.7.

These results show that the $\alpha$-RPR parameter must be chosen carefully, since after a certain value (coincident with that obtained from the ANOVA above which its effect is predominant) it induces a significant error in the predictions. The same is valid for the interaction coefficients ($C_i$ and $C_m$) regarding the prediction of the components perpendicular to the
<figure><img src="image_331.png" /><figcaption>**FIGURE 10** | Prediction error of the FT-RPR model.</figcaption></figure>

<figure><img src="image_332.png" /><figcaption>**FIGURE 11** | Prediction error of the iARD-RPR model.</figcaption></figure>

flow ($a_{22}$ and $a_{33}$), due to these parameters' variation strongly influencing their respective prediction errors.

## SUMMARY AND CONCLUSIONS

This paper evaluates the predictions of the fiber orientation distribution (FOD) of an injected Venturi-shaped specimen. The choice of the specimen was made in order to study a different case from the specimens traditionally used for validation purposes (usually the center gated-disk and the film-gated strip), which in turn presents characteristics common to many injected parts, such as variable thickness, section changes, convergent, and divergent transitions among others. The experimental characterization was performed using the novel micro computed tomography technique.

The experimental results describe the physical phenomenon to be modeled by the simulation. The orientation pattern measured through the CT technique is in accordance with the expectations arisen from previous knowledge and from the patterns measured by the standard method of optical microscopy (the ellipse method). These are broadly: the presence of a shell-core-shell layered structure across the part thickness, with the fibers aligned in the main flow direction in the shell layers and the

fibers aligned in the cross flow direction in the layer core. It is also demonstrated that the convergent and divergent transitions that the flow experiences through this specimen and the variations of its thickness induce changes in the fibers' alignment degree. In this way, in the convergent transition that occurs at the specimen constriction, characterized by an increase in the flow rate caused by the Venturi effect and an increase in the shear rate due to the narrower cavity, there is an increase in orientation in the main flow direction in both the shell and core layers. Whereas, at the divergent transition that occurs after the constriction there is a decrease in orientation in the main flow direction and an increase in orientation perpendicular to flow.

The computational study evaluates the ability of present theories to predict fiber orientation, revealing certain deficiencies in both the orientation models and the second-order orientation tensor closure approximations. Specifically, it is observed that the hybrid (Hyb) closure overestimates the orientation with respect to the experimental orientation and that obtained when using the ORE and IBOF closures. For their part, it is observed that the results obtained from ORE and IBOF closures are closer to the experimental ones, being essentially the same. However, the computational time consumed by the IBOF closure is approximately half that of the ORE. Due to its higher accuracy and computational efficiency, the IBOF
approximation is selected as the optimum. Moreover, at the entrance and filling completion regions of specimen, using the IBOF closure, it is observed that the iARD model fairly estimates the orientation components, while the FT model underestimates the a₂₂ component and overestimates the a₃₃ component. Then, from the comparison of experimental and predicted profiles it follows that the predictions of the iARD model in combination with the IBOF closure approximation are the most accurate for the case studied.

On the other hand, from the analysis of the predictions corresponding to the central region (thinner gap), a very important result of this work emerges: it is the demonstration that both orientation models fail to predict the increase in orientation that occurs in the specimen constriction. The a₁₁ component depends on the flow in the main direction, and simulations effectively predict the increase in the flow velocity and shear rate that should cause the increase of a₁₁. Then, this discrepancy may be attributed to the error in estimating the components in the directions perpendicular to the flow rather than to the estimation of a₁₁.

The ANOVA technique is used in order to objectively explore and quantify the effect of model parameters on predicting second-order tensor components. In strictly statistical terms, it is possible to demonstrate that after a certain level of the alpha-RPR parameter, the interaction between the different factors become significant, and alpha-RPR dominates the orientation prediction regardless the value taken by the rest of the parameters. However, for values below this alpha-RPR level, it is shown that for both the FT and iARD models, the fiber-fiber interaction coefficient (Ci) is the one that most influences the component in the main flow direction (a₁₁); whereas for the iARD model, the fiber-matrix interaction coefficient (Cm) has a significant impact on the prediction of the components perpendicular to the main flow direction (a₂₂ and a₃₃). The effect of the factors is as follows: (i) increasing alpha-RPR produces a decrease in a₁₁ and an increase in a₂₂ and a₃₃; (ii) increasing Ci produces a decrease in a₁₁ and an increase in a₂₂ and a₃₃, and (iii) increasing Cm produces a decrease in a₁₁ and a₂₂ and an increase in a₃₃. These results suggest that since Ci, Cm and alpha-RPR are fitting parameters, which affect the orientation components differently, the adjustment to the experimental results will never be entirely accurate.

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Finally, and taking into account the described limitations of the models and the adjustment of their parameters, predictive error analysis is used to find the optimal parameter that better captures the global orientation state of the component. The optimal set for this case, recommended for application in similar cases, is as follows: (i) for the FT model, Ci = 0.005, alpha-RPR = 0.7, and (ii) for the iARD model, Ci = 0.005, Cm = 0.2, and alpha-RPR = 0.7. It can be concluded that it is of fundamental importance to carefully define the models' parameters values (especially alpha-RPR) because their variation is closely related to the prediction error.

## DATA AVAILABILITY STATEMENT

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

## AUTHOR CONTRIBUTIONS

AA provided the injected part which was injected in the installations of the Leartiker group. BP performed the characterization of the samples via micro-CT and provided the experimental curves. MQ performed the simulations and the statistical calculations, performed the analysis of the results, and wrote the manuscript. PF and ZM has given significant intellectual inputs and supervised the work. ZM coordinated the working groups. All authors contributed to the article and approved the submitted version.

## ACKNOWLEDGMENTS

The authors want to thank all the institutions involved in the elaboration of this work. Particularly to the Institute of Polymer Product Engineering directed by Dr. ZM—Johannes Kepler University at Linz (Austria)—for kindly inviting MQ to carry out a research stay at its facilities, from which this work emerged, to the National Research Council of Argentina (CONICET) and the MINCyT (Argentina). Micro-CT results were gained within the projects DigiCT-Sim (project number: 862015) and pore3D (project number: 868735). Both micro-CT projects were funded by the State Government of Upper Austria and Austrian Research Promotion Agency (FFG).

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**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Quintana, Frontini, Arriaga, Plank and Major. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
<figure><img src="image_333.png" /></figure>

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# Processing-Structure-Properties of Cork Polymer Composites

Carla I. Martins* and Vitória Gil

Institute for Polymers and Composites (IPC), University of Minho, Guimarães, Portugal

This work aims at presenting a new strategy for the use of cork by-products on the development of sustainable composites with potential applications in rotational molding. In this study, different cork granulometries (0.15–3 mm) and matrix/cork ratios (90/10, 85/15, 80/20) are analyzed to access the processability of medium-density polyethylene (MDPE) with cork by rotational molding. The influence of processing parameters, such as the mold peak internal air temperature (PIAT) (200–240°C), is analyzed and correlated with the aesthetics, morphological and mechanical properties of the parts. The aim is to obtain a complete understanding of the processing-structure-property relationships. Defect-free parts are obtained with thin granulometric cork powders at a maximum of 10% by weight in PE/cork composites. The increase in cork content reduces the sintering capability and increases the porosity, wall thickness, and surface defects, simultaneously weakening the mechanical properties. The increase in PIAT favors a more compact structure and reveals better impact properties. All the parts are soft on touch and transmit the comfort and sensation of warm feeling of the cork. Moreover, lightweight parts and hydrophobic surfaces are achieved from the cork intrinsic properties. As a natural material, cork darkens its color with temperature, which is attributed to the reactions of the extractives within the components of cork, with no degradation associated. The work shows that polymer cork composites (CPC) are suitable for rotational molding within the processing window characteristic of PE, to achieve innovative and sustainable products with unique aesthetics and functionalities given by the cork material.

**Keywords:** rotational molding, cork-polymer-composites, cork, polyethylene, thermal properties, morphology, mechanical properties

**OPEN ACCESS**

**Edited by:**

Jacqueline Anne Johnson,
University of Tennessee Space
Institute (UTSI), United States

**Reviewed by:**

Veronique Michaud,
École Polytechnique Fédérale
de Lausanne, Switzerland
Liqing Wei,
United States Forest Service (USDA),
United States

*Correspondence:

Carla I. Martins
cmartins@dep.uminho.pt

**Specialty section:**

This article was submitted to
Polymeric and Composite Materials,
a section of the journal
Frontiers in Materials

**Received:** 13 June 2020

**Accepted:** 10 August 2020

**Published:** 25 September 2020

**Citation:**

Martins CI and Gil V (2020)
Processing-Structure-Properties
of Cork Polymer Composites.
Front. Mater. 7:297.
doi: 10.3389/fmats.2020.00297

## INTRODUCTION

Cork is a natural product obtained from the outer bark of an oak tree known botanically as Quercus suber L (Gibson et al., 1981). This material has a unique combination of properties such as low density, excellent acoustic and thermal properties, impermeability to liquids and gases, a high coefficient of friction, resilience, high energy absorption, excellent insulation properties, and a near-zero Poisson coefficient, which makes it an optimum material for a variety of applications (Fortes and Nogueira, 1989; Mano, 2002; Gibson, 2003). In addition, it is a natural, reusable, and renewable product and offers a unique look and touch which makes it difficult to be replaced by synthetic materials (Silva et al., 2005).
In terms of morphology, cork can be described as anisotropic material with thin-walled cells, regularly arranged without intercellular space. The cells are rectangular prisms like an alveolar structure and similar to a honeycomb, with their axes along the tree's radial direction, stacked in columns (Pereira, 2007).

In cork, the structural components of cell wall are as follows: suberin, an aliphatic polyester (42%); lignin, an aromatic polymer (21,5%); polysaccharides, including cellulose and hemicelluloses (16%); extractives (13%); and ashes (7%) (Pereira, 1988). The cell wall of cork is chemically made up of two types of components: the structural components (suberin, lignin, and polysaccharides) build up the cell wall and define its structure; they are insoluble and cannot be removed from the cell wall without profoundly affecting the cell structure and properties; and the nonstructural components (extractives or inorganic minerals), either low-molecular organic compounds that may be solubilized by appropriate solvents (Pereira, 2007).

This cellular configuration has a strong influence on the mechanical properties of cork-based materials (Gibson, 2005). Castro et al. (2010) presented a compilation of the main mechanical properties of natural cork obtained from different experimental tests. They concluded that natural cork has a poor mechanical behavior when compared with other types of core materials for sandwich components of lightweight structures, such as synthetic foams. However, its low thermal conductivity combined with a reasonable compressive strength makes it an excellent material for thermal insulation purposes as well as for applications in which compressive loads are present.

From the reuse of by-products resulting from the transformation of cork, composites were created. Cork was incorporated into polymeric matrices, which allowed the combination of the ecological properties with the good mechanical performance of polymeric materials (Fernandes et al., 2011; Soares et al., 2011). The combination of cork with polymers through melt-based technologies brought added value to cork-based materials, promoting the development of a wide range of innovative applications.

Studies can be found on the combination of cork and cork by-products with polyolefins such as polyethylene (PE) and polypropylene (PP) (Fernandes et al., 2010) as well as biodegradable matrices such as PLA (Vilela et al., 2013). The effect of adding a coupling agent (Fernandes and Correlo, 2014) and chemical surface modification (Pereira and Velez Marques, 1988; Abenojar et al., 2014) was also studied to improve the compatibility and the mechanical properties. Fernandes et al. (2010) concluded that the mechanical performance of the composites decreased with the increase in cork content but increased with the introduction of coupling agents that promoted the adhesion between cork-polymer phases.

The structural properties of cork were found to be strongly dependent on temperature and may affect its color. A darkening effect was observed in samples treated at lower temperatures (150°C). The thermal decomposition of cork studied by thermogravimetry analysis has shown a mass decrease of about 30% upon heating at 300°C and less than 10% at 200°C (Rosa and Fortes, 1988a,b; Rosa and Fortes, 1988a,b; Şen et al., 2014).

Therefore, the color changes observed at 150 and 200°C, when cork did not undergo significant chemical decomposition, were originated from extractives and hydrolyzed carbohydrates and their reactions with cork cell wall components particularly with cork lignin, while above 200°C it resulted from decomposition of hemicelluloses and formation of oxidation products. According to Pereira (2007), the cork extractives were the first to be volatilized, hemicelluloses were the first structural components to be degraded, and lignin and suberin were the most stable components, therefore degraded at last.

Most of these studies were based on injection molding and extrusion processes for the production of cork-polymer materials and applications. There is no knowledge in the processing of this material by rotational molding. This technique is used to produce hollow parts for various applications like liquid storage tanks, containers, toys, indoor and outdoor furniture, and playgrounds, among other applications. The advantages are the production of stress-free parts; the low costs for tooling's and molds; the little or no waste production; and the low restriction on mold design allowing the production of multilayer materials, especially when different compositions and thicknesses are required (Jansri and O-charoen, 2018; Fletes et al., 2020). This process is based on the rotation of polymeric powder material in an externally heated and cooled mold. Therefore, larger cycle times are involved compared to other plastic processing techniques such as injection molding or extrusion blow molding used to process similar parts (Crawford and Throne, 2002; Crawford and Kearns, 2003; Crawford and Gibson, 2012; Pereira, 2015; Nugent, 2017). Moreover, rotomolding is a challenge for several materials due to the possibility of thermo-oxidative degradation during processing, as a result of high temperature and large cycle time applied with impact on morphological and mechanical properties (Oliveira et al., 1996, 2007; Cramez et al., 2001). Due to that, this paper focuses on the processability of PE/cork by rotational molding and the relationship between material, processing, and product characteristics. The parts are characterized by aesthetic (color), chemical (evaluation of chemical composition), thermal (mass loss with temperature), physical (contact angles and density), morphological (microscopy), and mechanical (impact resistance) tests. The aim is to explore and characterize new materials to be used on the rotational molding process to produce differentiated new products with high value, sustainability, aesthetics, and functionality. This study is in line with other recently published articles in the finding of new materials for rotational molding (Greco et al., 2019; Vignali et al., 2019; Fletes et al., 2020).

# MATERIALS AND METHODS

## Cork and Polymer Materials

Different cork powders and granules, from cork processing stages, were kindly supplied by Amorim Cork Composites, SA (Portugal). The polymer used in the preparation of the cork-based composites was medium-density polyethylene (MDPE) (Advancene EM-3405-UVH) with MFI of 5 g/10 min
(190°C/2.16 kg) obtained from Ethydco (Egypt). The bulk density, particle size, and visual aspect of the cork are shown in Table 1 and Figure 1, respectively.

## Compounding and Processing

Different cork powders were dry blended with MDPE in the proportions of 90/10, 85/15, and 80/20 wt% and processed by rotational molding. For each sample, 150 g of material was used. The oven was heated by electrical resistances and its temperature was set to 290°C. The peak internal air temperature inside the mold (PIAT) was set to 210°C, and it was monitored by a thermocouple placed inside the mold through the vent conduct during processing. Cooling by air was applied until the temperature inside the mold dropped to 60°C before demolding the parts.

In a second part of the study, there was a need to understand the influence of the processing conditions applied on the aesthetics and morphological and mechanical characteristics of the parts. Therefore, parts of MDPE with 10 wt% MF8 cork were produced with PIAT ranging from 185 to 235°C.

For the processing of the parts, a laboratory rotational molding equipment with characteristics of a Rock and Roll and Shuttle machine was used, with an aluminum mold with parallelepipedic dimensions of 140 × 90 × 90 mm and 5 mm of mold wall thickness. This is a prototype machine developed at the Department of Polymer Engineering at the University of Minho (Pontes et al., 2014). In this type of machine, the mold rotates 360° through the axis of the support arm and the oven performs a swinging motion (from 45° to 45° to the right to the left) perpendicular to the support arm, allowing the spreading of the material for the ends of the part. The rotation speed of the mold and the pendulum swing were 7 rpm and 1.5 rpm, respectively.

<table><caption>TABLE 1 | Bulk density and maximum particle size of MDPE and cork powders.</caption><thead><tr><td>Sample code</td><td>Type</td><td>Bulk density (kg/m³)</td><td>Max. particle size (mm)</td></tr></thead><tbody><tr><td>MDPE</td><td>Powder</td><td>330–390</td><td>0.50</td></tr><tr><td>MF5</td><td>Powder</td><td>50–70</td><td>&lt;0.60</td></tr><tr><td>MF8</td><td>Powder</td><td>75–95</td><td>&lt;0.15</td></tr><tr><td>BD-0.5/1</td><td>Granules</td><td>50–60</td><td>0.5/1</td></tr><tr><td>BD-2/3</td><td>Granules</td><td>55–65</td><td>2/3</td></tr></tbody></table>

<figure><img src="image_334.png" /></figure>

## Color Determination

The aesthetic characteristics of the MDPE/cork parts were evaluated by visual inspection and by color measurements using a Spetro-Guide BYK portable colorimeter and a Shimadzu UV-2401PC reflectance spectrophotometer operating in the range of visible light between 380 to 740 nm with a 2 nm spectral resolution. The color parameters L, a, and b were determined according to the CIELab method. The system is based on the measurement of three coordinates: lightness L* between 0 (black) and 100 (white), a* representing red-green levels (+60 red, -60 green), and b* representing yellow-blue levels (+60 yellow, -60 blue). The color of a material is a mixture of these three parameters. The color variation was calculated according to the following formula (Bekhta and Niemz, 2003), where ΔL, Δa, and Δb correspond, respectively, to the variation of the coordinates L*, a*, and b* relative to the reference sample of a virgin cork powder.

$$ \Delta E = \sqrt{\Delta L^2 + \Delta a^2 + \Delta b^2} $$

## Thermal Properties

The thermal stability studies determined by thermogravimetric analysis (TGA) were performed to understand the degradation characteristics of the cork powder and the CPCs using a TGA Q500 series thermogravimetric analyzer from TA Instruments. Experiments were performed in platinum pans, at a heating rate of 10°C/min from 40 to 800°C under air atmosphere with an air flow rate of 40 mL/min. This atmosphere was used to replicate the atmosphere condition inside the mold during the rotational molding process.

## FTIR Analysis

To evaluate changes in the functional groups on the CPC after heating treatment, FTIR-ATR spectra were recorded using a MKII Golden Gate Single Reflection ATR System equipped with an ATR Golden Gate cell. Each spectrum was an average of 64 scans taken with 8 cm⁻¹ resolution in the 4000–600 cm⁻¹ range.

## Contact Angles

Contact angle measurements of the parts were determined according to the standard D7334-08 using a DataPhysics Contact Angle System OCA-20. Distilled water was used for sample analysis, and the volume of the sessile drop on the top surface was maintained at 2 µL in all cases, using a micro-syringe. For accuracy, all measurements were performed right after deposition of the droplet and repeated 10 times on different pieces of the same sample.

## Density

To determine the density of the parts, the samples were weighted in air and propanol according to the standard ISO 1183-1, Method A, using an OHAUS PioneerTM analytical balance equipped with a stationary support for the immersion vessel. The tested specimens were rectangular bars with 20 mm length and 10 mm width. Five specimens were tested for each sample.
## Scanning Electron Microscopy

The morphology of the cork structure and the fracture of the CPC parts were analyzed using an ultra-high-resolution field-emission gun scanning electron microscope (FEG-SEM) (Nova 200 NanoSEM, FEI Company, at SEMAT, Guimarães, Portugal). Secondary electron images were performed with an acceleration voltage of 10 kV.

Prior to the morphological analyses, the samples were covered with a very thin film (20 nm) of Au-Pd (80-20 wt%), in a high-resolution sputter coater (208HR Cressington Company), coupled to a MTM-20 Cressington High Resolution Thickness Controller.

## Mechanical Tests

The mechanical properties of the parts were determined by Izod and puncture impact tests. The Izod impact tests were performed according to the standard ISO 180 on a Ceast Resil Impactor instrument falling-weight impact tester with a pendulum energy of 7.5 J. The notched specimens were rectangular bars with 80 mm length and 10 mm width. Ten specimens were tested for each sample.

The puncture impact tests were performed according to the standard ISO 6603-1:2000 and ISO 6603-2:2000 on a Ceast Fractovis Plus instrument falling-weight impact tester. All the specimens were subjected to the same energy level (147.5 J), with an impact velocity of 4.4 m/s resulting from a drop height of 1 m of a carriage of total mass of 3 kg. The tested specimens were squared with a 60 mm side. Ten specimens were tested for each sample.

# RESULTS AND DISCUSSION

## Effect of Cork Powder Granulometry on Part Quality

Figure 2 and Table 2 depict the appearance of rotomolded parts produced with different granulometries and compositions of cork powders. The parts are soft on touch and transmit the sensation of comfort and warm feeling of the cork. This unique characteristic of natural cork material is maintained when CPC are processed by rotational molding. Parts processed by other plastic processing techniques like extrusion or injection molding lose this property as plastic shiny look and plastic touch are obtained.

Several difficulties were encountered in the attempt to process good-quality parts when using MDPE/cork of big particle size (0.5/1 and 2/3 mm) (Figure 2). The apparent density of these materials prevents their easy fitting on the mold cavity and facilitates the appearance of defects such as incomplete parts at the corner and heterogeneous surfaces due to the poor mixing, phase separation of polymer/cork, and lack of polymer wetting.

Parts of good quality were obtained using fine cork powders (Table 2). However, the increase in cork percentage resulted in the reduction of the sintering capability of the composite material increasing its porosity, wall thickness, and surface defects. These effects were more pronounced for MF5 than for MF8, given its difference in the powder size and powder characteristics as

<figure><img src="image_335.png" /><figcaption>**FIGURE 2** | Main defects obtained for parts produced by MDPE with 20% of BD-0.5/1 (A) and BD-2/3 (B).</figcaption></figure>

<table><caption>**TABLE 2** | Images of parts produced by MDPE with different compositions of MF5 and MF8 cork.</caption><thead><tr><th>Cork type</th><th>10%</th><th>15%</th><th>20%</th></tr></thead><tbody><tr><td>MF5</td><td></td><td></td><td></td></tr><tr><td>MF8</td><td></td><td></td><td></td></tr><tr><td>MF5</td><td></td><td></td><td></td></tr><tr><td>MF8</td><td></td><td></td><td></td></tr></tbody></table>

revealed by SEM images (Figure 3). MF5 powder particles are larger in size (<0.6 mm) and form a well-defined honeycomb cellular structure, whereas MF8 was grinded to a much smaller particle size (<0.15 mm) resulting in almost individual cells.

In terms of processing, rotational molding is defined by the rotation of the material inside the mold that is only subjected to a thermal environment and free coalescence of the particles; therefore, sintering is favored for MDPE/MF8. This result reveals that MF8 cork powder has the preferred material characteristics for the production of CPC by this processing technique.
A

<figure><img src="image_336.png" /></figure>

B

<figure><img src="image_337.png" /><figcaption>**FIGURE 3** | Effect of MDPE/cork composition on the structure of the parts. (A) Images obtained by optical magnification of the cross section along the wall thickness. (B) Images obtained by SEM analysis of MF5 and MF8 cork powder and its MDPE/cork composites.</figcaption></figure>

## Effect of Mold Internal Air Temperature

Rotomolding is a challenge for several materials due to the possibility of thermo-oxidative degradation during processing. Since cork is prone to color and structural changes at high temperatures, a study was carried out on the effect of mold internal air temperature (IAT) on the properties of MDPE/10 wt% MF8.

The processing cycle, generally monitored by the changes in the internal air temperature of the mold with time, is shown in **Figure 4A**. The incorporation of cork material has an important influence on the processing cycle when compared to MDPE. The difference starts at the moment of melting and adhesion of the PE particles to the mold surface (plateau observed between 110 and 150°C). In the case of PE/cork, there is a significant delay on that process, which also delays the rapid increase in the temperature inside the mold observed when all the material reaches the molten state and adheres completely to the mold surface (cooking stage of the material). Once the setup PIAT is reached, the mold is transferred to the cooling chamber. The temperature drops, and a small plateau occurs due to the crystallization process. It follows the solidification of the material until the part is demolded. The difference in the processing cycle of both materials is justified by the lower thermal conductivity of cork material (0.039–0.045 W/mK) as compared to PE (0.32–0.40 W/mK) (Hansen and Bernier, 1972; Silva et al., 2005; Gil, 2007). Therefore, the heat transferred from the mold to the particles is delayed by the presence of cork that affects not only the melt of the material (observed by the delay on reaching the PIAT) but also the transferring of the heat trapped inside the mold during cooling,

leading to an overshooting of temperature and longer cycle times. It is important to note that both samples were transferred to the cooling chamber at the same time, corresponding to the abrupt drop of the oven temperature. While MDPE starts the cooling phase, MDPE/cork temperature is still rising, delaying for some minutes the cooling of the material.

The effect of mold temperature, namely, the PIAT, on the cycle time is depicted in **Figure 4B**. As observed, the higher the temperature at which the parts are processed, the longer it takes to reach PIAT and the longer is the cycle time. The shortest cycle time recorded for PIAT of 185°C (real PIAT of 201°C due to overshooting) was about 38 min, whereas the longest cycle time recorded for PIAT of 235°C (real PIAT of 238°C) was about 43 min. The variations in the mold internal air temperature can be directly related to the materials and processing conditions and are very sensitive to differentiate between the samples as reported in other studies (Cramez et al., 2002; Ramkumar et al., 2014).

**Table 3** depicts the image of parts obtained at each PIAT and its effect on the color parameters in comparison to natural cork. The repeatability of part production is observed most of the time, with the darkening of the color with the increase in PIAT being clear. This is observed by the lightness parameter, ΔL, whose values change from 22.4 to 35.1. The total color difference, ΔE, follows this trend by increasing steadily with the increase in PIAT (22.5–37.6).

The effect caused by the processing at high temperatures is a decrease in lightness, which means the parts are darker than the parts processed at the lowest temperatures. These results are in agreement with the findings obtained using Q.
<figure><img src="image_338.png" /></figure>

<figure><img src="image_339.png" /><figcaption>**FIGURE 4** | Mold internal air temperature profiles during the rotational molding process of (A) MDPE and MDPE/10% cork parts and (B) MDPE/10% cork parts processed at different IAT. The arrow indicates the direction of increase in the IAT setup used for processing the parts.</figcaption></figure>

<table><caption>**TABLE 3** | Repeatability studies of MDPE/10% MF8 cork parts at different processing temperatures and CIELab color parameter variations in relation to the neat cork powder.</caption><thead><tr><th rowspan="2">PIAT (°C)<br>Setup (Real)</th><th rowspan="2">Rotomolded parts</th><th colspan="4">CIELab parameters variation</th></tr><tr><th>ΔL</th><th>Δa</th><th>Δb</th><th>ΔE</th></tr></thead><tbody><tr><td>185°C (201°C)</td><td></td><td>22.38</td><td>2.13</td><td>1.38</td><td>22.52</td></tr><tr><td>195°C (204°C)</td><td></td><td>22.08</td><td>1.54</td><td>3.37</td><td>22.39</td></tr><tr><td>205°C (210°C)</td><td></td><td>25.41</td><td>1.53</td><td>3.64</td><td>25.71</td></tr><tr><td>215°C (227°C)</td><td></td><td>28.89</td><td>0.23</td><td>8.57</td><td>30.13</td></tr><tr><td>225°C (232°C)</td><td></td><td>31.62</td><td>1.60</td><td>9.79</td><td>33.14</td></tr><tr><td>235°C (238°C)</td><td></td><td>35.05</td><td>3.52</td><td>13.42</td><td>37.69</td></tr></tbody></table>

<figure><img src="image_340.png" /></figure>

cerris cork (Şen et al., 2012). The authors found that the change in color at low temperatures (150°C) can occur even if there is no significant chemical decomposition of cork as a result of the reactions between extractives and hydrolyzed carbohydrates with cork cell wall components particularly with lignin. Above 200°C, decomposition of hemicelluloses may occur and the formation of oxidation products contributes to the color change of the cork. Further details are given in the following sections.

From now on the real PIAT is described on the figures and tables, and the data discussed according to real PIAT.

## Evaluation of Cork by Thermal Analysis

Thermogravimetry analysis (TGA) of neat cork material was carried out to understand the thermodegradation behavior of cork and to identify the temperatures at which the main chemical processes occur. TGA was carried under air atmosphere to evaluate the thermal stability of cork at high temperature and to have a similar environment as that occurring inside the mold during processing. The TGA/DTG curves for cork are presented in Figure 5.

Four regions can be identified in the thermogravimetric curves. The cork powder shows an initial region of mass loss between room temperature and 100°C corresponding to the elimination of water. However, water is only completely eliminated at 200°C, corresponding to 1% of mass loss. The second region of the curve, between 200 and 350°C and about 500°C, is characterized by a rapid mass loss. The first peak (351.8°C) corresponds to polysaccharides composed of cellulose and hemicellulose that have degradation temperatures in the range between 300 and 400°C (Silva et al., 2005; Kim et al., 2006; Wei et al., 2013). Suberin and lignin also contribute to this reaction but with smaller magnitudes. It is at this peak that the greatest loss of mass is found, which indicates that the reactions that contribute to the first exothermal peak are those that induce the darkening of the samples and that there is no further color change with the subsequent reactions (Şen et al., 2014). Lignin and suberin are relatively more thermal stable components when compared to polysaccharides and extractives, which means these components contribute mainly to the second reaction (455.5°C) in cork. Hence, the color changes in cork are the result of hemicellulose decomposition and formation of
<figure><img src="image_341.png" /><figcaption>**FIGURE 5** | TGA and DTG curves of cork powder under air atmosphere.</figcaption></figure>

oxidation products. In the final region, above about 500°C, the rate of mass loss is lower until the cork reduces to ashes (about 3.79% by weight).

Furthermore, the loss mass at 250°C was 6% and at 300°C was less than 30%. The thermal degradation of cork, in air atmosphere, starts at 258.4°C. This suggests that the cork powder can be processed at temperatures lower than 250°C without induced irreversible changes in cork chemical composition, and it can also be processed with polymers having processing temperatures lower than this value, such as the case of polyethylene.

## Evaluation of Cork Structural Changes by FTIR Analysis

**Figure 6** shows the FTIR spectrum of cork powder, MDPE powder, and MDPE/10% cork produced at 238°C. Natural cork powder was subjected to a heat treatment of 48 h at 255°C in an oven prior to FTIR so that color and possible structural changes could be identified and compared to the material changes occurring during the rotational molding process.

The FTIR spectrum of cork powder before heat treatment shows a band between 3600 and 3200 $cm^{-1}$, assigned to the O-H vibration from carbohydrates and lignin (Şen et al., 2012). The spectrum is dominated by the absorbance bands of suberin: two peaks at 2920 and 2847 $cm^{-1}$, corresponding to the asymmetric and symmetric vibration, respectively, of C-H in the olefinic chains and an intense band at 1732 $cm^{-1}$ corresponding to the carbonyl C = O in aliphatic acids and esters (Pereira, 2007). The band at 1128 $cm^{-1}$ can also be attributed to the C-O-C of the ester group in suberin. Suberin also contributes to the 1242 $cm^{-1}$ peak corresponding to the C-O stretch, through the epoxide group (Fernandes et al., 2014). The band at approximately 1466 $cm^{-1}$ is typical for lignin, and the peaks at 1087 and 1035 $cm^{-1}$ correspond to the C-O bond and are characteristic of polysaccharides (cellulose and hemicelluloses) (Abenojar et al., 2014).

<figure><img src="image_342.png" /><figcaption>**FIGURE 6** | FTIR spectrum for untreated cork powder, heat-treated cork powder for 48 h in the oven at 255°C, virgin MDPE and MDPE/10% cork part processed at 238°C.</figcaption></figure>

The comparison of the FTIR spectrum of cork powder, before and after heat treatment, confirmed the occurrence of chemical modifications. The largest modification in the chemical composition of cork observed in the FTIR spectrum was the substantial intensity reduction in the O-H (3600-3200 $cm^{-1}$) with temperature and treatment time. This means that carbohydrate content reduced substantially with temperature, and carbohydrate is the most heat-sensitive component of cork. Thus, temperature-induced alterations in the chemical composition of the components are condensation of carbohydrate products with suberin in the lower temperature range and heavy condensation of all remaining components at higher temperatures.

The FTIR spectrum of a CPC sample produced at 238°C and the pure materials (cork and MDPE) show significant differences in the absorption patterns. The absorption of the C-O band between 1030 and 1000 $cm^{-1}$ and the O-H band between 3600 and 3200 $cm^{-1}$, corresponding to O-H stretching, decreased after heating, indicating the loss of polysaccharides and condensation of lignin side chains with phenyl nuclei. The bands at 3000 and 2800 $cm^{-1}$ did not decrease by heating, indicating the stability of suberin in these conditions. In addition, these bands are more pronounced in the CPC sample because MDPE is composed of long chains of C-H and due to the presence of C-H in cork from suberin. The band at 1466 $cm^{-1}$, corresponding to the vibration of aromatic ring of lignin increased by heating, indicating the stability of lignin in these conditions (Dekier, 2012). The results are in agreement with findings by Pereira (1992, 2007), Şen et al. (2012), and Fernandes et al. (2014).

## Effect of PIAT on the Contact Angles of Parts

The purpose of the contact angle tests was to study the wettability of MDPE as compared to MDPE/cork parts.
**Figure 7** shows the measurement of the contact angles and the drop plain view digital image taken right after the sessile drop test.

The MDPE part has a contact angle of 86°, which is close to the value reported in the literature (Subedi, 2011). The incorporation of cork results in the increase in the contact angle to values above 100°. This proves that the liquid does not wet the surface, and therefore, there is a more pronounced hydrophobic and impermeable behavior of the parts with the incorporation of cork. In fact, cork is impermeable to liquids and gases, because its cell walls are closed and essentially composed of suberin, which is a hydrophobic component (Abenojar et al., 2014).

With the increase in PIAT, there is a decrease in the contact angle between the drop and the surface of the parts. At 201°C, the contact angle was 118.9° and at the highest temperature of 238°C was 109°, however, the parts still have a hydrophobic character. This result reveals that the surface of the part changes with the processing cycle applied, namely, the PIAT. The increase in PIAT leads to a slight decrease in the contact angle, which may indicate a better wettability of the cork powder by the polymer with the increase in temperature and a transition of parts with a touch of cork to a more plastic touch. This characteristic allows the liquid to have a better tendency to wet the surface, and consequently, there is a decrease in the contact angle.

## Morphology of CPC Parts

The morphology of the impact-fracture surface of MDPE/10%MF8 at different processing temperatures was evaluated by SEM (Figure 8). The first observation is that all

<figure><img src="image_343.png" /><figcaption>**FIGURE 8** | Morphology of the impact-fracture surface of MDPE/10% cork produced at (A) 201°C, (B) 227°C, and (C) 238°C.</figcaption></figure>

<figure><img src="image_344.png" /></figure>

<table><caption>**FIGURE 7** | Contact angles between a drop of water and the surface of virgin MDPE and MDPE/10% cork parts.</caption><thead><tr><th></th><th>MDPE</th><th colspan="6">MDPE/10% cork</th></tr><tr><th>PIAT (°C)</th><th>198</th><th>201</th><th>204</th><th>210</th><th>227</th><th>232</th><th>238</th></tr></thead><tbody><tr><th>Contact angles (°)</th><td>86.4<br>±3.8</td><td>118.9<br>±2.1</td><td>118.5<br>±4.8</td><td>116.6<br>±3.3</td><td>117.1<br>±3.6</td><td>113.6<br>±3.9</td><td>109.0<br>±4.0</td></tr></tbody></table>

<figure><img src="image_345.png" /></figure>

<table><caption>**FIGURE 9** | Effect of PIAT on the impact strength of MDPE and MDPE/10 wt% cork parts.</caption><thead><tr><th></th><th>MDPE</th><th colspan="6">MDPE/10% cork</th></tr><tr><th>PIAT (°C)</th><th>198</th><th>201</th><th>204</th><th>210</th><th>227</th><th>232</th><th>238</th></tr></thead><tbody><tr><th>Impact strength (kJ/m²)</th><td>12.3<br>±1.9</td><td>1.8<br>±0.3</td><td>2.2<br>±0.4</td><td>2.3<br>±0.2</td><td>2.5<br>±0.2</td><td>3.0<br>±0.4</td><td>3.0<br>±0.4</td></tr></tbody></table>

the parts are very porous, but there seems to be evidence of good interfacial adhesion between the two components, as cork powder particles are embedded in the thermoplastic matrix. According to the micrographs, the peculiar morphology of the cork was maintained after compounding and processing (compare to Figure 3B – MF8). The increase in processing
<figure><img src="image_346.png" /></figure>

<figure><img src="image_347.png" /></figure>

<figure><img src="image_348.png" /></figure>

<figure><img src="image_349.png" /></figure>

<table><caption>**FIGURE 10** | Effect of PIAT on the impact behavior of MDPE and MDPE/10% cork parts. (A) Force over time; (B) Energy over time; (C) Maximum force as a function of PIAT and related samples fracture surfaces; (D) Energy at maximum force as a function of PIAT.</caption><thead><tr><th></th><th>MDPE</th><th colspan="6">MDPE/10% cork</th></tr></thead><tbody><tr><th>PIAT (°C)</th><td>198</td><td>201</td><td>204</td><td>210</td><td>227</td><td>232</td><td>238</td></tr><tr><th>Maximum force (N)</th><td>2920.0±<br>446.9</td><td>318.7±<br>46.2</td><td>377.6±<br>68.6</td><td>349.1±<br>56.5</td><td>382.3±<br>64.1</td><td>430.9±<br>79.9</td><td>431.0±<br>63.7</td></tr><tr><th>Energy (J)</th><td>21.0<br>± 4.1</td><td>1.51<br>± 0.3</td><td>1.76<br>± 0.4</td><td>1.50<br>± 0.3</td><td>1.83<br>± 0.4</td><td>1.91<br>± 0.4</td><td>2.03<br>± 0.4</td></tr></tbody></table>

<table><caption>**TABLE 4** | Density of the parts.</caption><thead><tr><th></th><th>MDPE</th><th colspan="6">MDPE/10% cork</th></tr></thead><tbody><tr><th>PIAT (°C)</th><td>198</td><td>201</td><td>204</td><td>210</td><td>227</td><td>232</td><td>238</td></tr><tr><th>Density (g/cm³)</th><td>0.924 ± 0.001</td><td>0.909 ± 0.009</td><td>0.913 ± 0.007</td><td>0.887 ± 0.006</td><td>0.885 ± 0.019</td><td>0.8897 ± 0.015</td><td>0.889 ± 0.012</td></tr></tbody></table>

temperature favors a better sintering of materials reducing the porosity level of the part.

## Mechanical Properties of Parts

Impact strength results are shown in **Figure 9**. It can be seen that the impact strength decreased greatly with the addition of 10% of cork powder (1.83 kJ/m²) compared with neat MDPE

(12.30 kJ/m²). This tendency is mostly related to the presence of voids and porous structure observed (see **Figure 3**), which contributes to stress concentration points and a weak ability to transfer energy between materials. Previous studies (Xu and Crawford, 1993; Oliveira et al., 1996, 2007; Pick and Harkin-Jones, 2004) reported a correlation between the number of voids and the impact strength in rotational molded parts; the
<figure><img src="image_350.png" /><figcaption>FIGURE 11 | Relationship between processing and properties of parts.</figcaption></figure>

greater the number of voids, the lower the impact resistance. Moreover, according to Oliveira et al. (2007) and Ramkumar et al. (2016), there is a processing window that maximizes the mechanical properties as a result of better sintering (reduction of voids) and the absence of thermal degradation of the polymer matrix. In the present study, cork hinders the formation of a well-compacted structure, as observed previously by SEM. Nevertheless, CPC parts increase their impact strength from PIAT at 201 to 238°C. This result can be attributed to the diminishing of voids and the building up of a more compact structure at higher PIATs. This means that the composites can absorb more energy and, consequently, their mechanical properties are improved.

Puncture impact tests are depicted in **Figure 10**. The results indicate that MDPE and MDPE/10% cork parts exhibit a quite different failure and deformation behavior. While MDPE suffers a ductile fracture, the CPC parts fracture in a fragile way, as observed by the images of the fracture surfaces presented in **Figure 10C**.

The maximum contact force between the impactor and specimen and the absorbed energy in the crushing process were determined for all the impact tests carried (Figures 10C,D). The reduction in the puncture impact behavior of the CPC compared to MDPE is clear. In the force-time curves, MDPE samples got to a maximum load peak around 2900 N, while all the samples with cork present values between 300 and 450 N (decrease up to 84%). Thus, the use of cork affects the maximum allowed loads related to impact. These values (in terms of percentage) are similar to those obtained by other authors working with fibers in rotomolding, where reductions up to 90% in impact properties were reported (Torres and Aragon, 2006; Yuan et al., 2007; Ortega et al., 2013; Cisneros-López et al., 2017).

With the increase in temperature (PIAT), there is a tendency for the maximum force to be higher and the curve to be more

extensive over time, which indicates that energy absorption is achieved in a longer period of time. This can prevent the appearance of undesirable fracture accelerations resulting from the impact.

Regarding the energy curves, it can also be seen that upon CPC reaching the maximum of absorbed energy, the curve tends to show a negative slope. Thus, in CPC parts there is a slight tendency to increase the strength supported by the sample before fracture and the absorbed energy with the increase in PIAT. Due to the heterogeneity of the samples, the fluctuations in the force and energy absorbed from the materials are expected.

## Density of Parts

The density of the parts is shown in **Table 4** and reveals a significant decrease with the addition of 10% of cork powder (0.909 g/cm³) as compared to neat MDPE (0.924 g/cm³). This result is expected given the difference in the density of both materials, namely, cork (0.11–0.25 g/cm³) (Anjos et al., 2014) and MDPE (0.934 g/cm³) (Datasheet of Medium Density Polyethylene, 2016), and the fact that the amount of polymer in the composite was reduced.

Cork is composed of closed cells with a gas similar to the air inside, which promotes a decrease in the density of the parts in which the cork is incorporated (Gul et al., 2013). With the increase in PIAT, it seems to have a slight decrease in density of the parts. The values may vary due to the heterogeneity of the samples.

## Relationship Between Processing-Morphological-Properties of Parts

**Figure 11** summarizes the relationship between processing, morphology, and properties of the PE/cork parts obtained by rotational molding. The mechanical properties of CPC parts are greatly affected when compared to pure PE, because the sintering ability of PE material becomes more difficult in the presence of cork, resulting in a high level of porosity and voids. This changes the fracture behavior of PE from ductile to fragile behavior. The increase in processing temperature (seen by the PIAT) results in a more compact structure, improving the mechanical properties of the composite. It also influences the appearance of the final parts, by the darkening of the color with the increase in PIAT. No significant chemical degradation of the cork structural components occurs during processing at these temperatures; therefore, the hydrophobic character of the surface of the parts is achieved and maintained during processing. It is important to notice that the parts preserve the texture and soft touch of the cork natural material, although its color depends greatly on the processing conditions used.

Despite the decrease in the mechanical properties of the PE/cork composite parts produced by rotational molding, there are some benefits to be pointed out, namely, the aesthetics of cork, touch (soft and warm feeling), the hydrophobicity of the surface, and the lightness of the final part. Therefore, different functionalities can be achieved by using PE/cork composites on the production of parts by rotational molding.
## CONCLUSION

The rotational molding of PE/cork composites was investigated to understand the relationship between processing, morphology, and characteristics of the parts. The effect of cork powder granulometry (0.15–2/3 mm), the composition of MDPE/cork (10–15–20 wt% cork), and processing window (200–240°C) were analyzed. Good-quality parts were obtained by rotomolding using fine cork powders (<0.6 mm particle size) and a maximum of 10 of cork by weight. The increase of cork reduced the sintering capability of the materials, increasing part porosity, wall thickness, and surface defects. These effects were more pronounced in MF5 (<0.6 mm, honeycomb cellular structure) than for MF8 (<0.15 mm, individual cells), given its difference in size and morphological characteristics. Part defects such as incomplete parts at the corners and heterogeneous surfaces due to poor mixing and lack of polymer wetting were observed for large particle sizes. These results allow the selection of MF8 cork as the preferred material for the composition of PE/cork composites.

Cork characteristics such as soft touch and warm feeling were obtained regardless of the processing conditions applied. However, the brownish tone, typical of cork, gradually became darker with the increase in processing temperature. The color change was due to the reaction of the extractives within the components of the cork cell wall, and not by degradation of cork, indicating that a typical processing window for rotomolding of PE can be adopted for MDPE/cork composites. Higher temperatures favor the sintering of the PE material and the construction of a more compact structure, which in turn results in the improvement of the impact properties (from 318.69 N at 201°C to 430.98 N at 238°C). Nevertheless, virgin PE parts have a ductile behavior and absorb seven times more energy than PE/cork parts.

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This work presents a different strategy for the upgrading of cork by-product (cork powder) and simultaneously the development of sustainable composites with potential applications in rotational molding. This processing technique allows the cork characteristics to be preserved in the processing window typical for PE, giving rise to products with lightweight, unique visual appearance, soft touch, sensation of comfort, and warm feeling of cork.

## DATA AVAILABILITY STATEMENT

The datasets generated for this study are available on request to the corresponding author.

## AUTHOR CONTRIBUTIONS

CM was the scientific mentor of the work, conceiving and designing the experiments. VG performed the experimental work and analyses of results. CM and VG analyzed the data and wrote the manuscript. Both authors have read and agreed to the published version of the manuscript.

## FUNDING

The authors acknowledge the financial support of the Project RoTMI-Rotomolding Technology and Materials Innovations (POCI-01-0247-FEDER-33095), cofinanced by the European Regional Development Fund (FEDER) through the Operational Program for Competitiveness and Internationalization (POCI) under the “Portugal 2020” framework. IPC acknowledges the support of the Portuguese Foundation for Science and Technology (FCT) through the National Funds References UIDB/05256/2020 and UIDP/05256/2020.

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