A comprehensive platform investigating thermal,
mechanical and rheological properties for biocomposite
based on poly (3-hydroxybutyrate-co-3-hydroxyvalerate)
reinforced with biomass by-products

Vincent Mathel, Theo Le Gagne, Xavier Falourd, Catherine Deborde, Lucie

Le-Bot, Alain Bourmaud, Johnny Beaugrand, Luigi-Jules Vandi

► To cite this version:

Vincent Mathel, Theo Le Gagne, Xavier Falourd, Catherine Deborde, Lucie Le-Bot, et al.. A comprehensive platform investigating thermal, mechanical and rheological properties for biocomposite based on poly (3-hydroxybutyrate-co-3-hydroxyvalerate) reinforced with biomass by-products. Sustainable Materials and Technologies, 2025, 45, pp.e01471. 10.1016/j.susmat.2025.e01471. hal-05319950

HAL Id: hal-05319950

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# A comprehensive platform investigating thermal, mechanical and rheological properties for biocomposite based on poly (3-hydroxybutyrate-co-3-hydroxyvalerate) reinforced with biomass by-products

Vincent Mathel<sup>a,c,*</sup>, Theo Le Gagne<sup>e</sup>, Xavier Falourd<sup>e,f</sup>, Catherine Deborde<sup>e,f</sup>, Lucie Le-Bot<sup>e</sup>, Alain Bourmaud<sup>d</sup>, Johnny Beaugrand<sup>e</sup>, Luigi-Jules Vandi<sup>b,c,*</sup>

## ARTICLE INFO

### Keywords:

- Bioplastic

- Biobased composite

- PHA-based composite

- Lignocellulosic fibres

- Natural fibre

- Organic filler

- Cellulose

## ABSTRACT

Interest in developing polyhydroxyalkanoates (PHAs) -based biocomposites with biomass fillers (biofillers), derived from local organic by-products, to mitigate global plastic pollution has increased significantly in the last decades. These biocomposites not only offer a more cost-effective solution but also contribute to reducing the carbon footprint, enhancing product circularity, and accelerating biodegradation kinetics. However, optimising their mechanical properties and processability to effectively replace conventional plastics remains a challenge. This study holistically investigates key factors influencing the thermal, mechanical, and rheological properties of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) -based biocomposites. The range of biofillers used in this work, including wood sawdust, macadamia / walnut nutshell flour, agave piña fibres, sorghum stem/leaf fibres, wheat bran flakes and treated wood flour, differ significantly in origin, composition and shape. Except for the wood, the addition of biofillers resulted in a decrease in T<sub>m</sub> by 1 to 3 °C, T<sub>c</sub> by 1 to 6 °C, and T<sub>g</sub> by 0.5 to 13.5 °C. The greatest reduction in T<sub>g</sub> was observed with the Walnut biofiller. A significant gap of 60 % in tensile stress and modulus was noted between the best and worst performing biofillers, highlighting the importance of carefully selecting the biomass for biocomposite manufacturing. Consistent correlations were found between mechanical properties and the cellulose content, crystallinity, and the hydrophilic surface of the biofillers. The findings suggest that superior PHBV-based biocomposite performance can be attributed to the presence of hydroxyl groups from carbohydrates on the biofillers' surface and a robust internal cellulose structure. Additionally, the shape of the biofillers, particularly the aspect ratio, shows a stronger correlation with rheological behaviour at low angular frequency than the interactions between biofillers and PHBV. At high angular frequencies, the addition of biofillers leads to a reduction in PHBV viscosity by 40 % to 80 %, depending on biofiller used. To support the development of a comprehensive platform for PHAs-based biocomposites, this study compares and validates various characterisation methods (¹³C ssNMR, TGA, carbohydrate and lignin analysis) that more effectively assess the composition of reinforcing biofillers.

## 1. Introduction

To address the global issue of plastic accumulation in land, sea and landfills, biodegradable bioplastics offer a reliable alternative to

conventional plastics. These materials can be broken down by micro-organisms when released into the environment and composted when properly managed. Among biodegradable bioplastics, poly-hydroxyalkanoates (PHAs) are particularly promising due to their

<footnote><sup>a</sup> School of Chemical Engineering, The University of Queensland, Brisbane, QLD 4072, Australia</footnote>

<footnote><sup>b</sup> School of Mechanical and Mining Engineering, The University of Queensland, Brisbane, QLD 4072, Australia</footnote>

<footnote><sup>c</sup> Centre for Advanced Materials Processing and Manufacturing (AMPAM), The University of Queensland, Brisbane, QLD 4072, Australia</footnote>

<footnote><sup>d</sup> Université Bretagne-Sud, UMR CNRS 6027, IRDL, F-56100 Lorient, France</footnote>

<footnote><sup>e</sup> INRAE, UR1268 BIA, F-44300 Nantes, France</footnote>

<footnote><sup>f</sup> INRAE, PROBE Infrastructure, BIBS Facility, F-44300 Nantes, France</footnote>

<footnote>* Corresponding authors at: Centre for Advanced Materials Processing and Manufacturing (AMPAM), The University of Queensland, Brisbane, QLD 4072, Australia. E-mail addresses: v.mathel@uq.edu.au (V. Mathel), l.vandi@uq.edu.au (L.-J. Vandi).</footnote>
potential to be produced from a variety of organic feedstock and their biodegradability in nearly all natural environments [1]. Furthermore, life cycle assessments have shown that PHAs have lower global warming potential and acidification potential compared to other biodegradable and conventional polymers [2,3]. However, one of the main drawbacks of these materials is their cost [4]. In this study, a poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) with a low hydroxyvalerate (HV) comonomer content (2 mol%) was selected due to its higher commercial availability [5]. The low ratio of comonomer results in a highly crystalline PHA. The high degree of crystallinity increases the polymer's density and reduces its kinetic of biodegradation compared to PHAs with higher comonomer content [6,7].

The addition of plant fibres has been proposed as an effective strategy to reduce material costs while simultaneously improving product circularity and reducing carbon footprint [8]. Lignocellulosic agricultural residues and industrial organic waste are considered suitable sources of biomass fillers (biofillers) for polymer reinforcement. Incorporating biofillers can also accelerate biodegradation and composting kinetics [9]. It can be attributed to the hydrophilic nature of the biomass, the weak interfacial adhesion with the polymer matrix, and the generated porosity, which can act as pathways for water and enzymes to penetrate the biocomposite [10–12]. To meet product certification standard [10], this acceleration of biodegradation should be particularly relevant for highly crystalline PHBV, where the slower kinetic of biodegradation can be counterbalanced by the presence of biofillers. When optimised, these biocomposites are a promising solution to substate a portion of rigid packaging for biodegradable disposable tableware or for niche products such as plan clips for farming [13].

Studies incorporating reinforcing biofillers in PHA-based bio-
composites have gained momentum but also generated some confusion.
A decrease in tensile stress has been observed with the incorporation of
untreated natural fillers in PHAs matrices, likely due to poor interfacial
interaction between the hydrophobic polymer and the hydrophilic bio-
fillers. This lack of interaction leads to the formation of microscopic gaps
or cracks that concentrate stress at the interface and act as initiators of
breakage [14–16]. However, it has also been suggested that PHAs
exhibit better interactions with biofillers compared to other (bio)poly-
mers due to their more hydrophilic nature [17], with some studies even
reporting improved tensile stress when biofillers were included [18–20].

A correlation between Young's modulus, tensile strength, and the fibre aspect ratio is frequently observed in the literature, where a higher aspect ratio leads to greater strength and stiffness [21]. However, this trend is not always consistent for PHAs. For example, Valente et al. did not observe any significant change in tensile strength when the fibre length was reduced from 770 µm (aspect ratio 42) to 149 µm (aspect ratio 11) in a PHB [18]. One potential source of confusion can come from the difficulty in efficiently comparing results obtained under different conditions (e.g., different components, additives, processing techniques, and characterisation standards). While it is well established that factors such as (bio)filler-polymer interaction, (bio)filler shape (e.g., aspect ratio), and polymer molecular weight influence rheological behaviour [22–25], it remains unclear whether one of these factors predominates over the others for PHAs-based biocomposites. In addition, a lack of certain investigations in some studies can hinder the conclusions drawn. For example, PHBV is known to have low thermal stability and may undergo chain scission during the melting process [26]. This effect can be exacerbated by the addition of (bio)fillers, which can increase shear stresses by friction with the solid (bio)filler and consequently thermo-mechanical degradation, chain scission and ultimately the biocomposite mechanical properties [27,28]. It has also been reported that the microcrystalline structure of semi-crystalline materials plays a crucial role in determining the biocomposite properties, and this structure can be influenced by the addition of biofillers [29]. Blend morphology, biofiller dispersion and distribution can also significantly affect bio-composite properties [30].

A study that incorporates all these factors would provide greater

confidence in identifying the key factors that influence the mechanical
and rheological properties of the biocomposite. In this paper, Gel
Permeation Chromatography (GPC) was used to evaluate the molecular
weight of PHBV in the biocomposite. Differential Scanning Calorimetry
(DSC) was conducted to observe the evolution of the PHBV crystalline
phase in response to the addition of biofillers, while Dynamic Mechan-
ical Analysis (DMA) monitored changes in glass transition temperature
associated with the amorphous phase. Blend morphologies were
assessed using optical microscopy on polished surfaces of the bio-
composite specimens. The potential interactions between biofillers and
PHBV were investigated through X-ray Photoelectron Spectroscopy
(XPS) to analyse the hydrophilicity of the biofiller surface. Additionally,
biofiller shapes were evaluated using MorFi, while their composition
were analysed through carbohydrate analysis (cellulose and hemicel-
lulose contents) and lignin content determination. Finally, the ratio of
crystalline cellulose for each biofiller was determined by X-Ray
Diffraction (XRD) and Nuclear Magnetic Resonance (ssNMR). The re-
sults obtained, along with observations of the fractured surface of the
PHBV-based biocomposite using Scanning Electron Microscopy (SEM),
were correlated with rheological and mechanical analyses to identify
key factors influencing these properties. To adopt a holistic approach,
the Australian biomass fillers were deliberately selected with drastically
different nature and lignocellulosic composition, ranging from nutshells
(macadamia, walnut flour), stems (agave piña fibres, Sorghum), and
leaves (Sorghum) to bran (wheat bran flake), woody flour (wood
sawdust and treated wood fibre), all of which are found locally in
Australia as abundant waste streams. By selecting such a diverse range of
biofillers, the aim is to encompass a broader spectrum of intermediate
biofillers which can share some characteristics with those studied. Given
the vast diversity of available biomass, a secondary objective is to assess
various methods for determining the composition of reinforcing bio-
fillers using conventional characterisation techniques such as TGA and
ssNMR, and to compare these results with specific compositional ana-
lyses (e.g., carbohydrate and lignin content). This work aims to
contribute to developing a comprehensive platform for manufacturing
high-performance PHA-based biocomposites.

## 2. Experimental section

### 2.1. *Materials*

The PHBV powder, containing 2 mol% of HV comonomer, 1 wt% of boron nitride as a nucleating agent, and 0.5 wt% of antioxidant, was provided by TianAn Biopolymer (Ningbo, Zhejiang, China) under the trade name ENMAT Y1010. The Sorghum biomass, Leaf and Stem (Sugargraze variety), comes from the University of Queensland's research farm at the Gatton campus near Brisbane, Queensland. The biomass preparation is described in the work from Pennells et al. [31]. The *Pinus radiata* Sawdust (referred Wood), Macadamia Nutshell (referred Macadamia), Walnut Nutshell (referred Walnut) flours were supplied by Micro Milling Australia company. *Blue weber* agave piña (referred Agave) was supplied as industrial organic waste after fermentation by the Australian Agave Project (Top Shelf International company). The received Agave piña was dried and ground using a Retsch SM300 mill at 2500 rpm with a 1 mm trapezoidal mesh screen. The wheat bran flakes were purchased from Woolworths Australian and originated from Australian farming. Treated wood biofiller was treated under a process of holocellulose (water-insoluble carbohydrate fraction including hemicellulose and cellulose) hydrolysis. All the biomass was sieved between a mesh of 125 µm and 60 µm to ensure the same range of sizes during the study. Not-Sieved Wheat Bran (referred NS Wheat Bran) that may contain residual starch was also included in the study. Sieved wheat bran was referred to Wheat Bran in this study. For greater clarity, all the fibres or flours used in this publication will be referred to as biofillers.
## 2.2. Manufacturing of PHBV-based biocomposites

Prior to blending, the biofillers and PHBV powder were dried at 60 °C for 48 h. Under these conditions, a moisture content of 0 wt% was obtained for PHBV, and approximately 0.4 wt% for the biofillers. The dried materials were weighed to obtain a ratio of 20 wt% of biofillers in PHBV matrix and then blended manually by shaking a bag until a uniform powder mixture was achieved. Then, these blends were processed by co-rotative twin-screw extruder (Eurolab 16, Thermo Scientific) with a screw length (L) of 67 cm, a diameter (D) of 1.5 cm, and a temperature of 170 °C along the barrel to obtain PHBV-based biocomposite granulates. The extruder was fed through Brabender volumetric feeders. The screw profile used for PHBV-based biocomposites preparation was composed of three mixing zones separated by conveying zones. The screw speed was fixed at 300 rpm and the estimated residence time was approximately 2 min. Before compounding, the moisture content was carefully measured to ensure it was below 0.5 wt%, thereby preventing any potential hydrolysis of PHBV. After production, the molecular weight of PHBV was assessed by gel permeation chromatography to evaluate the extent of polymer thermal degradation as a potential factor of PHBV-based biocomposite properties. Table 1 lists the compounds produced and the main compounding conditions.

## 2.3. Specimen preparation

Tensile test specimens were produced using a Babyplast 6/10P micro-injector (Ambaldi Group, Italy). The barrel temperatures were set at 178 °C, 180 °C, and 185 °C (for the die), with the mould temperature at 60 °C and injection pressure at 80 bars. Volume fraction of biofillers for biocomposite was calculated from the weight fraction of biofiller added (20 wt%), volume (1.6 mL) and weight (1.95 g) of the PHBV dog bone specimen, weight of biocomposite specimens, PHBV density of 1.25 g/cm³ and assessed biofillers density for each biocomposite (Table 1).

Slab specimens (60x10x1mm) for Dynamic mechanical analysis (DMA) analysis were produced with a HAAKE Minijet Pro Piston Injection Moulding System (Thermo Fisher Scientific Inc., USA) under the same barrel temperature of 180 °C, mould temperature of 60 °C, and injection pressure of 600 psi. Squares (30x30x1mm) were also moulded using these parameters and shaped into 25 mm discs for oscillatory rheology analysis with a cutting press. Prior to processing, all biocomposite granulates were dried at 60 °C for 24 h.

# 3. Testing and characterisation

## 3.1. Biofillers characterisation

To assess the ratio of cellulose in biofiller, carbohydrate analyses (CA) were performed. It is assumed that the weight fraction of glucose represents the cellulose content (%Cell<sub>CA</sub>) [32] whereas hemicellulose

content is represented by sum of weight fractions of mannose, galactose, xylose and arabinose contents (%Hemi<sub>CA</sub>) [33]. Analysis was performed according to Gautreau et al. [34]. Experiments were done in triplicate and the value reported is the average.

The lignin analysis (LA) was performed according to the methodology reported by Mussig and Beaugrand 2025 [35] on micronized powdered particles of sample. Three independent measurements were done, and the lignin content was expressed as a percentage of the dry matter mass (%Lig<sub>LA</sub>).

The starch content was determined on both NS Wheat Bran and Wheat Bran samples in order to determine the quantity of glucose monomer in those samples originating from starch and not cellulose and subtracting those from the total glucose content determined by the total carbohydrate analysis. To do so, three analyses were done by sample according to enzymatic tools as reported in Beaugrand et al. 2004 [36] and slightly modified with a modification for the quantification of glucose by high-performance anion exchange chromatography (HPAEC-PAD ICS-3000, Thermo Scientific Dionex), the column was a CarboPac PA1 (4 mm × 25 mm, Thermo Scientific, USA), thermostated at 25 °C. Elution was isocratic (500 mM NaOH) at a flow rate of 1 mL.min⁻¹. The internal standard was rhamnose.

The qualitative composition of biofillers was determined with a Thermal Gravimetric Analyser (TGA) TA SDT650 (TA Instruments, New Castle, United States) with two replicates. The measurements were performed for approximately 15 mg of each sample, from 50 °C to 800 °C with a heating ramp of 20 °C.min⁻¹, under a nitrogen flow of 50 mL.min⁻¹ to provide an inert atmosphere. Data treatments were conducted by deconvoluting the derivative thermogravimetric (DTG) curves of the weight loss as a function of the temperature to define the proportion of extractive/hemicellulose, cellulose and lignin with Fityk software using the LogNormal function as presented in Fig. 1.a. The peaks below 320 °C correspond to the less thermally stable components of the biofillers such as extractives, pectin, hemicellulose (%Hemi<sub>TGA</sub>) and a part of less stable lignin. The peaks observed between 320 °C and 400 °C correspond mainly to the Cellulose component (%Cell<sub>TGA</sub>). The peaks above 400 °C are mainly attributed to the Lignin component (%Lig<sub>TGA</sub>) [37].

Solid State NMR (ssNMR) experiments were performed at a temperature of 21 °C using a Bruker AVANCE III spectrometer (Bruker, Germany) with a 300 MHz magnet. The powdered samples were placed in a 4 mmØ zirconia rotor with a Kel-F cap. The ¹³C spectra were collected using a 4 mm double air bearing, magic angle-spinning probe under 7 kHz with CPMAS pulse sequence. The ramped cross-polarization time was 2 ms, decoupling was done using tppm 15 sequence with 100 kHz. Recycle delay was 3 s and acquisition time 49 ms. A total number of 2048 scans were collected. Adamantane was used as an external chemical shift reference. Before analyses, the biofillers were dried at 60 °C for 48 h to remove moisture. The peak at 52–56 ppm corresponding to the methoxy groups of lignin was used to determine the evolution of lignin content of sorghum and treated biofillers. The

<table><caption>**Table 1**

Compounding outputs for the manufactured PHBV-based biocomposites produced.</caption><thead><tr><th>Reference</th><th>Blend %MC after drying (%)*</th><th>Torque (N.m)</th><th>Pressure (bar)</th><th>Throughput (g.min<sup>-1</sup>)</th><th>M<sub>w</sub> of PHBV (10<sup>3</sup>g.mol<sup>-1</sup>)*</th><th>Volume fraction of biofillers</th></tr></thead><tbody><tr><td>PHBV</td><td>0</td><td>7.2 ± 3</td><td>8 ± 1</td><td>9 ± 0.1</td><td>133.1 ± 0.7</td><td>—</td></tr><tr><td>Wood</td><td>0.27</td><td>7.8 ± 3</td><td>9 ± 1</td><td>9 ± 0.1</td><td>116.3 ± 1.9</td><td>0.19</td></tr><tr><td>Treated wood</td><td>0.19</td><td>7.4 ± 3</td><td>7 ± 1</td><td>8 ± 0.2</td><td>122.4 ± 1.5</td><td>0.19</td></tr><tr><td>Agave</td><td>0.35</td><td>7.4 ± 3</td><td>8 ± 1</td><td>9 ± 0.1</td><td>127.1 ± 3.4</td><td>0.18</td></tr><tr><td>Macadamia</td><td>0.28</td><td>7.6 ± 3</td><td>9 ± 1</td><td>9 ± 0.6</td><td>120.9 ± 4.6</td><td>0.19</td></tr><tr><td>Walnut</td><td>0.79</td><td>7.1 ± 3</td><td>6 ± 1</td><td>8 ± 0.8</td><td>112.8 ± 3.7</td><td>0.19</td></tr><tr><td>Sorghum stem</td><td>0.26</td><td>7.6 ± 3</td><td>7 ± 1</td><td>9 ± 0.3</td><td>100.7 ± 3.2</td><td>0.19</td></tr><tr><td>Sorghum leaf</td><td>0.45</td><td>7.6 ± 3</td><td>9 ± 1</td><td>10 ± 0.1</td><td>117.3 ± 1.3</td><td>0.19</td></tr><tr><td>NS Wheat Bran</td><td>0.87</td><td>7.1 ± 3</td><td>8 ± 1</td><td>9 ± 0.6</td><td>108.7 ± 4.3</td><td>0.18</td></tr><tr><td>Wheat Bran</td><td>0.46</td><td>7.6 ± 3</td><td>5 ± 1</td><td>9 ± 2.4</td><td>110.1 ± 4.8</td><td>0.19</td></tr></tbody></table>

<footnote>* Moisture content (%MC) measured with a thermobalance analyser HC103 Mettler Toledo at 105 °C.</footnote>

<footnote>** Molecular Weight (M<sub>w</sub>) measured by GPC.</footnote>
<figure><img src="image_2.png" /><figcaption>**Fig. 1.** a. Deconvolution method on DTG curve, b. Method to evaluate the Lignin content in ¹³C solid state NMR spectrum, Deconvolution methods to evaluate %CI of cellulose by c. ¹³C ssNMR and d. X-ray diffraction (XRD).</figcaption></figure>

qualitative content of lignin (%LigSSNMR) was determined according to the area of the integrated peak at 52–56 ppm after normalisation to the unity of area of the integrated peak at 100–112 ppm, which is correlated to acetal carbon atoms (C-1) following the method used by Kostryukov et al. (Fig. 1.b.) [38]. Chemical shifts, peak half-widths, and peak areas of samples were determined using a least-squares fitting approach with Peakfit® software (Systat Software Inc., USA). A simplified version of the advanced approach developed by Larsson et al. was used to determine the crystallinity index of the samples (%CISSNMR) [39]. This method, based on C-4 signal processing, used four lines for the crystalline region and three lines for the amorphous region. In the crystalline domain, three Lorentzian lines were assigned to cellulose Cr (Iα) (88.7–89.1 ppm), cellulose Cr (Iα + β) (88.2 ppm), and cellulose Cr (Iβ) (86.3–86.9 ppm). Additionally, a Gaussian line was used to represent the paracrystalline (PCr) contribution (87.9 ppm). For the amorphous region, two Gaussian lines corresponded to the accessible surface (AS; 82.6 and 83.6 ppm), while a single Gaussian line was associated with the inaccessible surface (IAS; 82.9–83.1 ppm). The actual number of lines used varied from 6 to 2, depending on the spectral resolution. Cellulose crystallinity was evaluated by calculating the peak area ratio of the lines representing the crystalline fraction relative to those corresponding to the cellulose C-4 region. This approach is illustrated on cotton in Fig. 1.c.

A Bruker D8 Advance X-ray diffractometer (Bruker, Germany) was used to perform X-ray diffraction (XRD) analysis with a Cu Kα source (λ = 1.54 Å) at 40 kV and 40 mA. The scanning rate was 3 s per step, 0.02° step size with the range of 5 to 40° 2θ. To define the crystallinity Index of biofillers (%CI<sub>XRD</sub>), deconvolution computation was performed with Fityk software using the Gaussian function. %CI<sub>XRD</sub> was determined from 2θ XRD pattern, by the ratio of the areas under the peak corresponding to the crystalline cellulose to the total area under the diffraction pattern, as presented in Fig. 1.d [40,41]. Before analyses, the biofillers were dried at 60 °C for 48 h to remove moisture and sealed in closed vials.

An X-ray Photoelectron Spectrometry (XPS) Kratos AXIS Supra plus instrument was used to evaluate the surface state of the biofillers. The incident radiation was monochromatic Al Kα X-rays (1486.6 eV) at 100 W (10 kV, 10 mA). The vacuum-dried samples were scanned at an analyser pass energy of 160 eV over 1200–0 eV binding energy range

with 1.0 eV steps and a scan time of 120 s and at 20 eV with 0.1 eV steps and 60 s scan time for narrow high-resolution (HR) scans, with up to 5 sweeps per HR scan. During sample analysis, the base pressure in the analysis chamber remained lower than 10⁻⁸ Torr. Atomic concentrations were calculated using the CasaXPS version 2.3.14 software with Kratos library Relative Sensitivity Factors. Samples were run in duplicates, and one spot on each sample was analysed. Peak fitting of the high-resolution data was also performed using the CasaXPS© software. All high-resolution scans were charge-corrected to the C—C peak at 284.6 eV. The O/C and C-C/C-H ratios were collected.

A MorFi Compact analyser (Techpap, France) equipped with a CCD video camera and a high magnification optical flow cell was used to measure the biofiller's dimension. The arithmetic length (μm), and width (μm) distributions and the aspect ratio were extracted from the data obtained with MorFi R.10.07 automatic analysis software. The average biofiller perimeters were calculated using these measured dimensions and considering biofiller as simple rectangular shape in 2D. Each measure was realized with 100 mg of biofiller suspended in approximately 1 L of distilled water and replicated three times. MorFi is dynamic morpho-granulometric system offering a high throughput, fast turnaround tool to assess biomass morphology and dimensions at the population level in plenty of study as presented in the work of Pennells et al. [42] and Beaugrand et al. [43].

## 3.2. PHBV-based biocomposite characterisation

The molecular weight of PHBV was determined by gel permeation chromatography (GPC) using an Agilent 1260 Infinity II system using guard column (Agilent PL-gel, 10 µm, 7.5 mm × 50 mm), followed by three Agilent PL gel MIXED-B columns (10 µm, 7.5 mm × 300 mm) in series, at 30 °C, with a chloroform flow rate of 1 mL.min⁻¹. Bio-composites and PHBV were dissolved in filtered HPLC-grade chloroform at 80 °C for 120 min. After dissolution, the PHBV was separated from other biofillers using polytetrafluoroethylene syringe filters (0.22 µm, Kinesis, ESF-PT-13-022). Calibration was performed using polystyrene standards and Mark-Houwink constants (K = 7.7 × 10⁻³ mL.g⁻¹, a = 0.82) [44] to correct the measured molecular mass on the Agilent GPC data processing software. Two replicates were realized for each
biocomposite.

To observe the biofillers dispersion/distribution in the biocomposite, specimens from a middle cross-section where polished as presented in Fig. 3. Then, polished surfaces were observed using an Olympus BX51 optical microscope (Tokyo, Japan) in diffraction mode. ImageJ software version 1.54 was used for the image processing. Average perimeters of biofillers were obtained using calculations performed with the ImageJ software.

Thermal analyses were performed using a DSC Q2000 from TA Instruments, calibrated before measurement with indium as standard material. Samples were encapsulated in an aluminium T-zero standard pan and lid. Sample weights were kept constant in the range of 6–6.25 mg. The DSC cycles included a heating from 20 °C to 185 °C, then a cooling to –50 °C and a second heating to 200 °C at 10 °C.min⁻¹. All experiments were performed under a controlled N₂ flow (50 mL.min⁻¹). Melting temperatures (Tₘ), crystallization temperature (Tc) and melting enthalpy were collected. Melting enthalpy of PHBV (ΔHₘ) in PBHV-based biocomposite was assessed as:

$$ \Delta H_m = \frac{\Delta H_{mcompo}}{\theta_{biofiller}} \qquad (1) $$

With ΔH<sub>mcompo</sub> denoting the enthalpy measured from DSC curve for the PBHV-based biocomposite and θ<sub>biofiller</sub> being the weight fraction of biofillers in the PBHV-based biocomposite equal to 20 wt%. Then, the degree of crystallinity (χ) was calculated by dividing the obtained ΔH<sub>m</sub> with the theoretical melting enthalpy of 100 % crystallized PHB equal to 146 J.g⁻¹ [45]. Two replicates were performed for each sample.

DMA analyses were conducted using a TA Discovery Series Hybrid Rheometer (HR30) equipped with a 3-point bending geometry, featuring a 25 mm frame. The tests were performed over a temperature range of –50 °C to 120 °C under N₂ environment, with a heating rate of 5 °C.min⁻¹, a frequency of 1 Hz, and an axial displacement of 25 µm. Oscillatory rheological analyses were also carried out with the same equipment, using an ETC aluminium parallel-plate flow geometry with a 25 mm diameter and a 1.1 mm plate gap. These experiments were performed at 185 °C with a strain amplitude of 1 %, which is within the linear viscoelastic (LVE) region of the biocomposites. Due to the sensitivity of PHBV to thermal degradation and the longer measurement times at low frequencies, frequency sweeps were conducted from higher to lower frequencies, ranging from 630 rad.s⁻¹ to 0.063 rad.s⁻¹.

Tensile tests were conducted using an Instron 5548 EM load frame equipped with a 1 kN load cell, 1 kN pneumatic grips, and a video extensometer. The tests adhered to ASTM D638 standards, with a tensile rate of 1 mm.min⁻¹. Key properties, including tensile strain at break (%), tensile stress at maximum load (MPa), and tensile modulus (MPa), were recorded. Each sample was tested in quintuplicate.

Fractured/ruptured surfaces of specimens following the tensile test were observed using a JEOL JSM-IT500HR SEM under high vacuum conditions at 3 kV acceleration voltage and a working distance of 15 mm.

All samples analysed were coated with a thin layer of platinum after a vacuum cleaning.

# 4. Results and discussion

## 4.1. Biofillers composition

Cellulose, hemicellulose and lignin contents were investigated for the different biofillers using CA, TGA and ¹³C ssNMR methods and the obtained results are depicted in Table 2 (DTG curves from TGA and ssNMR curves are presented in Fig. S1.a and b in Supplementary Data).

The ratio of cellulose and hemicellulose for Wood [46], Macadamia [47], Walnut [48], Sorghum fibres [40], Agave [49] are aligned with the ratio reported in the literature. Wood, Treated wood, Sorghum Stem and Wheat Bran appear to have the highest ratio of cellulose, whereas NS Wheat Bran and Walnut present the lower ratio. The highest hemicellulose content expressed as % of the dry matter was found in NS Wheat Bran, while the lowest was observed in sieved Wheat Bran and in Treated wood, as expected for the second one, since the treatment is designed to remove hemicellulose.

Unlike the other biofillers which are fully lignocellulosic, Wheat Bran contains a significant proportion of starch granules [36,50]. Because starch consists of a mixture of amylose and amylopectin that hydrolyses to glucose elements (units of glucose joined with an α(1 → 4) bond), leading to difficulties in dissociating cellulose (units of glucose joined with an β(1 → 4) bond) to starch by CA [51], authors have quantified the glucose amount from starch separately, thanks to specific enzymatic tools. In TGA, the thermal decomposition of starch appears between 280 and 350 °C and overlaps with the degradation of cellulose [52]. Using an extra quantification of starch by specific enzymatic hydrolysis, the ratio of glucose from the starch in glucose used to define cellulose content was evaluated at 55 % for the NS Wheat Bran and 27 % to sieved Wheat Bran. The values of cellulose indicated in Table 2 take in account the substitution of these ratios of starch for CA and TGA analyses. It is evident that sieving Wheat Bran results in the selective retention of the more cellulosic components, while removing a high proportion of the hemicellulose components.

In Fig. 2.a, b a positive strong correlation between the CA and TGA analyses for determination of hemicellulose and cellulose contents can be observed, with a Pearson's correlation coefficient r = 0.83 and 0.97 respectively. The complex mix composition of starch and cellulose in Wheat Bran biomass may results in a reduced correlation coefficient for cellulose.

The highest ratio of lignin was observed for the Macadamia whereas the lowest was for Agave, Sorghum Leaf and the NS Wheat Bran biofillers, as also expected from literature and functional services (waterproof, biologic defence) dedicated by lignin polymers in the protectives plan organs (e.g. shellnut). A non-consistency is observed between the lignin content evaluated by CA and TGA with |r| < 0.6 (Fig. 2.c). This

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

Biofillers compositions (% Cellulose, Hemicellulose, Lignin) and crystallinity index (%CI) of cellulose.</caption><thead><tr><th rowspan="2">Characterisation tools<br>Biomass</th><th colspan="2">%Cellulose</th><th colspan="2">%Hemicellulose</th><th colspan="2">%Lignin</th><th colspan="2">%CI</th></tr><tr><th>CA<br>%Cell<sub>CA</sub><br>(w/w)%</th><th>TGA<br>%Cell<sub>TGA</sub><br>(w/w)%</th><th>CA<br>%Hemi<sub>CA</sub><br>(w/w)%</th><th>TGA<br>%Hemi<sub>TGA</sub><br>(w/w)%</th><th>LA<br>%LiG<sub>LA</sub><br>(w/w)%</th><th>ssNMR<br>%LiG<sub>ssNMR</sub><br>(n/n)%</th><th>XRD<br>%CI<sub>XRD</sub><br>(w/w)%</th><th>ssNMR<br>%CI<sub>ssNMR</sub><br>(n/n)%</th></tr></thead><tbody><tr><td>Wood</td><td>37.0 ± 2.3</td><td>47 ± 1</td><td>22 ± 1.7</td><td>36 ± 0</td><td>32.0 ± 0.7</td><td>42</td><td>35</td><td>37</td></tr><tr><td>Treated wood</td><td>45.0 ± 0.6</td><td>64 ± 0</td><td>6 ± 0.1</td><td>5 ± 0</td><td>26.0 ± 0.2</td><td>47</td><td>51</td><td>49</td></tr><tr><td>Agave</td><td>18.0 ± 0.4</td><td>36 ± 0</td><td>20 ± 0.4</td><td>36 ± 0</td><td>7.0 ± 0.1</td><td>7</td><td>37</td><td>22</td></tr><tr><td>Macadamia</td><td>28.0 ± 0.5</td><td>39 ± 0</td><td>21 ± 1.1</td><td>38 ± 0</td><td>41.0 ± 3.1</td><td>63</td><td>29</td><td>39</td></tr><tr><td>Walnut</td><td>17.0 ± 0.7</td><td>30 ± 2</td><td>20 ± 0.1</td><td>42 ± 4</td><td>25.0 ± 0.7</td><td>42</td><td>25</td><td>27</td></tr><tr><td>Sorghum Stem</td><td>36.0 ± 0.6</td><td>39 ± 0</td><td>22 ± 1.2</td><td>38 ± 0</td><td>27.0 ± 0.9</td><td>24</td><td>37</td><td>26</td></tr><tr><td>Sorghum Leaf</td><td>26.0 ± 1.5</td><td>41 ± 0</td><td>23 ± 1.1</td><td>34 ± 1</td><td>18.0 ± 0.7</td><td>15</td><td>27</td><td>22</td></tr><tr><td>NS Wheat Bran</td><td>13.0 ± 0.7</td><td>8 ± 0</td><td>29 ± 0.2</td><td>56 ± 0</td><td>11.0 ± 0.5</td><td>11</td><td>7</td><td>17</td></tr><tr><td>Wheat Bran</td><td>46.0 ± 1.1</td><td>46 ± 0</td><td>9 ± 0.2</td><td>9 ± 0</td><td>5.0 ± 0.3</td><td>1</td><td>16</td><td>17</td></tr></tbody></table>

<footnote>* Values with the substitution of the starch content obtained by enzymatic-assisted quantification.</footnote>
<figure><img src="image_3.png" /><figcaption>Fig. 2. Correlation between CA, TGA to establish the content of a. Cellulose, b. Hemicellulose, c. Correlation between LA, TGA, ssNMR techniques to assess the content of Lignin in biofillers. d. Correlation between XRD and ssNMR to define the %CI.</figcaption></figure>

can be due to difficulties in dissociating the degradation of unstable lignin from the other components below 400 °C because of overlapping of their degradations with the other components [37]. However, the positive strong correlation with r = 0.94 between the proportion of lignin obtained by CA and data treated by ¹³C ssNMR can be observed and supports the assumption that the determination of lignin content using the deconvolution method in TGA analyses is not suitable.

The ratio of crystalline cellulose in the biofillers was also investigated by ¹³C ssNMR and XRD (XRD patterns are presented Fig. S1.c in Supplementary Data). In Fig. 2.d, a positive moderate relationship between the ratio of %CI of cellulose obtained by XRD and ¹³C ssNMR (r = 0.76) can be observed. The discrepancy between the two characterisation methods can be explained by the fact that XRD accounts for the %CI from all amorphous components of the biofillers (including lignin and hemicellulose), whereas the deconvolution method used with ssNMR separates the cellulosic contribution (amorphous and crystalline) from that of the amorphous polysaccharides such as hemicellulose. Moreover, XRD is more sensitive to crystalline phase than amorphous phase and ssNMR is equally sensitive to both phases [53].

From the data, Treated wood presented the highest %CI, following by the Wood. The significantly higher %CI for Treated wood aligns with the expectation that the treatment it underwent effectively removed the amorphous cellulose. The Wheat Bran, followed by Sorghum Leaf and Agave biofillers, presented the lower %CI.

## 4.2. Biofillers dimensions

Biofiller length, diameter and aspect ratio were evaluated by MorFi analyses and results are presented in Table 3 and Fig. S2 in Supplementary Data. A similar distribution of biofiller lengths for the reinforcing biomass used, although the Treated wood biomass exhibits a slightly wider biofiller length distribution (see Fig. S2.a in Supplementary Data). Although the biofiller width distributions of all the biomass types are within similar size ranges, sorghum leaf, Treated wood, wheat bran, and agave exhibit a distribution with higher values compared to the other biofiller (see Fig. S2.b in Supplementary Data). As a general observation, the distribution curve illustrates the effectiveness of the

<table><caption>Table 3
Biofillers dimension.</caption><thead><tr><th>Biomass</th><th>Mean biofiller width (d) (µm)</th><th>Mean arithmetic length (l) (µm)</th><th>Aspect ratio (l/d)</th></tr></thead><tbody><tr><td>Wood</td><td>35 ± 17</td><td>176 ± 69</td><td>5.0</td></tr><tr><td>Treated wood</td><td>52 ± 15</td><td>200 ± 72</td><td>3.8</td></tr><tr><td>Agave</td><td>41 ± 19</td><td>142 ± 70</td><td>3.5</td></tr><tr><td>Macadamia</td><td>42 ± 16</td><td>142 ± 58</td><td>3.4</td></tr><tr><td>Walnut</td><td>39 ± 19</td><td>136 ± 27</td><td>3.5</td></tr><tr><td>Sorghum Stem</td><td>36 ± 18</td><td>192 ± 92</td><td>5.3</td></tr><tr><td>Sorghum Leaf</td><td>54 ± 17</td><td>192 ± 87</td><td>3.6</td></tr><tr><td>NS Wheat Bran</td><td>43 ± 19</td><td>168 ± 85</td><td>3.9</td></tr><tr><td>Wheat Bran</td><td>48 ± 18</td><td>161 ± 57</td><td>3.4</td></tr></tbody></table>

sieving process in obtaining biofillers with dimensions within the same size range. The mean values of biofiller dimensions, calculated directly using the MorFi software, highlight the slight difference in biofiller dimensions, as observed in the distribution curves. Two groups of biofiller sizes represented by their aspect ratio have emerged: macadamia, walnut, agave, Treated wood, sorghum leaf, (NS) wheat bran with an aspect ratio below 4 and wood, sorghum stem, with an aspect ratio of 5 and above. The MorFi results for NS wheat bran exclude biofillers larger than 1 mm, which explains the discrepancy between the expected outcome from the sieving process and dimensions measured for sieved and non-sieved wheat bran.

## 4.3. Biofillers dispersion in PHBV-based biocomposite

Figure 3 presents optical images of polished surface of PHBV-based biocomposite in the middle of the specimen width. As a general observation, all biocomposites exhibit a relatively uniform dispersion of biofillers on the surface (black spots on the treated image by Image J), along with a visible size distribution of the biofillers. Some porosities are visible and indicated by green arrows. The observed porosities represent
<figure><img src="image_4.png" /><figcaption>Fig. 3. Optical images of biofillers dispersion and distribution in PHBV-based biocomposite.</figcaption></figure>

less than 2 % of the analysed surface (case of Treated wood bio-
composite) Biofillers display an orientation along the flow direction near
the specimen edge and a more random orientation within the specimen
mass. This is particularly evident in the Wood, Treated wood, and Agave
biocomposites. It is probably the result of flow turbulence in the middle
of specimen during the injection process. This phenomenon is well
described in literature and called skin-core effect, the part of melt flow in
contact with the thermoregulated mould edges being solidified imme-
diately during the cavity filling; oppositely, in the core of the sample, the
flow can re circulate until the temperature decreases. This structural
effect has been previously described for flax or jute fibre-reinforced
injected biocomposite materials [54].

The high density of biofiller particles larger than 1 mm in the NS
Wheat Bran observed on the optical image confirms the limitations of
the MorFi analysis for fibres above 1 mm, highlighting the inconsistency
in the measurement of the NS Wheat Bran dimensions by MorFi. A
corrected aspect ratio of NS Wheat Bran of 4.6 was determined from
direct measurement on the optical image. Fibres breakage during pro-
cessing is commonly reported in the literature [55]. Excluding NS Wheat
Bran biocomposite for the reason explained below, a strong correlation
was observed (Fig. S3 in Supplementary data) between the measured
average perimeters of biofillers from optical image (processed biofillers)
and the calculated average perimeters from the MorFi data (non-pro-
cessed biofillers). The discrepancy observed between perimeters values
between optical and MorFi analyses may result from several factors,
including differences in characterisation techniques, data collection and
processing methods, potential size reduction of the biofillers during
processing, partial coverage of biofillers by the PHA matrix in optical
images, and the use of an overly simplified shape model (more accu-
rately described as spheroid-shaped). Despite these differences in
values, it can be concluded that the biofillers are in same order of size

difference before and after processing, even though some degree of
breakage may occur.

4.4. *Thermal analyses*

From DSC measurement, a T<sub>m</sub> around 173 °C, a T<sub>c</sub> of around 126 °C and degree of crystallinity around 71 % were observed for PHBV. The high T<sub>m</sub>, T<sub>c</sub> and χ were expected for a PHBV with low ratio of %mol HV, included a nucleating agent present in the polymer. Except for the Wood and Treated wood biofillers, which do not appear to impact the crystalline properties of PHBV, the other biofillers cause a reduction in T<sub>m</sub> by 1 to 3 °C, T<sub>c</sub> by 1 to 6 °C. This represents a moderate decrease compared to other studies, such as the work by Mazur et al., who reported a reduction in the crystallization temperature (T<sub>c</sub>) of PHBV by 16 °C and 22 °C with the addition of nettle stalks, and by 8 °C and 7 °C with the incorporation of pinecone flour [56]. DSC curves of the different PHBV-based biocomposites are presented in Fig. S4.a, b in Supplementary Data. It can correspond to a decrease in the free volume necessary for the nucleation process, preventing the development of the crystalline phase or/and interference with biofillers which impact the macromolecules organization [14,56,57]. Sorghum leaf appears to have the greatest effect on the crystallization process of PHBV (highest drop of T<sub>c</sub> and χ). DSC results are summarized in the Table 4.

No measured key factor related to the biofiller properties (biofiller
composition and dimension), PHBV-based biocomposite characteristics
(including biofiller dispersion and distribution), or PHBV molecular
weight was identified to account for the changes in the crystalline
properties. This suggests that the evolution of the crystalline phase of
PHBV results from a synergistic combination of factors specific for each
biofiller. It is also worth noting that while DSC provides a general
indication of crystallinity evolution, more in-depth characterizations,
<table><caption>**Table 4**

Thermal and crystalline properties of PHBV and PHBV-based biocomposites.</caption><thead><tr><th></th><th><i>T</i><sub>m</sub> (°C)</th><th><i>T</i><sub>c</sub> (°C)</th><th><i>χ</i> (%)</th><th><i>T</i><sub>g</sub> (°C)<sup>*</sup></th></tr></thead><tbody><tr><td>PHBV</td><td>173.3 ± 0.2</td><td>125.6 ± 0.0</td><td>71 ± 6.1</td><td>20.0</td></tr><tr><td>Wood</td><td>172.4 ± 0.5</td><td>125.1 ± 0.5</td><td>73 ± 0.8</td><td>20.5</td></tr><tr><td>Treated wood</td><td>172.9 ± 0.2</td><td>125.3 ± 0.1</td><td>74 ± 4.5</td><td>18.5</td></tr><tr><td>Agave</td><td>172.4 ± 0.0</td><td>122.8 ± 0.2</td><td>73 ± 2.8</td><td>20.0</td></tr><tr><td>Macadamia</td><td>172.3 ± 0.2</td><td>124.9 ± 0.1</td><td>68 ± 5.3</td><td>15.0</td></tr><tr><td>Walnut</td><td>170.5 ± 0.1</td><td>123.1 ± 0.1</td><td>72 ± 1.2</td><td>6.5</td></tr><tr><td>Sorghum Stem</td><td>171.0 ± 0.0</td><td>121.5 ± 0.4</td><td>73 ± 1.8</td><td>16.0</td></tr><tr><td>Sorghum Leaf</td><td>171.6 ± 0.3</td><td>119.7 ± 0.2</td><td>67 ± 0.4</td><td>17.0</td></tr><tr><td>NS Wheat Bran</td><td>171.4 ± 0.1</td><td>122.6 ± 0.2</td><td>71 ± 2.3</td><td>14.0</td></tr><tr><td>Wheat Bran</td><td>171.3 ± 0.1</td><td>123.2 ± 0.0</td><td>71 ± 0.4</td><td>11.5</td></tr></tbody></table>

using for example Small- and Wide-Angle X-ray Scattering, are necessary to better understand the impact of biofillers on the microcrystalline structure and the properties of PHBV-based biocomposites. For example, transcrystallinity process has been shown to influence the biofiller-polymer interface and varies depending on the type of biofiller used [58].

## 4.5. Dynamic mechanical analysis

Temperature dependence of Tan δ measured for each PHBV-based biocomposite is plotted in Fig. 4. Tan δ evolution represents the energy dissipated during dynamic tests and reflects the mobility of polymer macromolecule relaxations in the amorphous regions. These relaxations produce distinct peaks on the DMA curves. In the glassy region, where the macromolecular chains are rigid, only local motions of short molecular groups or backbone movements, known as secondary relaxations (γ and/or β), can occur. The glass transition region, where long-range coordinated molecular motions are activated with increasing temperature, is characterized by α-relaxation. In this region, the peak of Tan δ observed at 20 °C for PHBV is associated with the polymer's glass transition temperature ($T_g$) which could not be observed by DSC. Indeed, the low amorphous fraction of the PHBV matrix (because of high degree of crystallinity), leads to only a slight change in heat flow at $T_g$ which is further attenuated by the addition of biofillers, ultimately reducing the sensitivity of the DSC to detect the transition. The high $T_g$ assessed for PHBV and its biocomposites are the consequence of the micro-crystalline structure formed during the injection moulding process and the high degree of crystallinity of the materials [59] (Table 4). PHBV-based biocomposite with Wood and Agave depicted a similar $T_g$ than PHBV whereas the other biofillers show a shift to the lower temperatures.

A lower $T_g$ indicates an increased capability of chain mobility at lower temperatures, which is unexpected given that the addition of biofillers typically restricts chain mobility [57,60]. Z.C Lule et al. observed also a drop by about 10 °C of $T_g$ with addition of 20 wt% lignocellulosic biofiller in polylactic acid polymer [61]. They associated

it with potential moisture absorption behaviour of lignocellulose materials that led to the formation of hydrogen bonds which increased the free volume and decreased the $T_g$ but it can be also a consequence of weak interfacial adhesion between biofiller and polymer [62]. $T_g$ can also be influenced by decrease in the crystalline fraction (which it is not observed here) [63], the PHBV molecular weight (reduction of molecular entanglements) [22], or by the plasticizing effect of some components in the biofillers, allowing greater freedom of chain motion. For example, the biocomposite with Walnut obtained the most remarkable shift of 13.5 °C. Walnut nutshell is knowing to have a significant proportion of fatty acid esters [48] that are already reported as potential natural-based plasticizers [64]. As also reported, lignin, in certain case, can play the role of plasticizer that could reduce the $T_g$ [40,65,66].

## 4.6. Tensile properties and fracture morphology

Tensile tests were performed to evaluate the mechanical performance of both neat PHBV and PHBV-based biocomposite specimens. Results are summarized in Table 5 and typical tensile test curves are presented in Fig. S4.c in Supplementary Data. PHBV exhibits a high tensile modulus of 3.3 GPa, a tensile strength of 35.4 MPa, and a low tensile strain at break of approximately 3.3%, characterizing it as a stiff, strong and brittle PHA. It is consistent with its high degree of crystallinity. A relationship can be observed between the tensile stress and tensile modulus of PHBV-based biocomposites (Fig. 5.a), which depends on the biofiller and is associated with their reinforcement effects [67–69]. The alignment between the evolution of tensile modulus and stress as a function of biofillers suggests that these properties are influenced by the same underlying factors. It is also worth noting that the good alignment between the storage modulus (E') measured at 25 °C in DMA and the tensile modulus supports the reliability of their extracted values despite the differences in specimen preparation. DMA curves of storage modulus are presented in the Fig. S4.d in Supplementary Data.

As a common trend, all the PHBV-based biocomposites present a higher tensile modulus but a lower tensile stress in comparison to neat PHBV, except for Wood biocomposites. The best mechanical properties were achieved with this last biofiller. The increase of young modulus by 73% and the highest tensile strength, approximately 5% greater than PHBV indicates stronger biopolymer-biofillers interaction compared to other biofillers. It results to a stiffer and stronger material in comparison to the neat PHBV. These results are consistent with previous studies, where an increase in the tensile strength of PHBV was observed upon the addition of wood [70]. For other biofillers, it was also reported, a reduction in mechanical properties. Mazur et al. observed a 21% decrease in tensile strength and a 5% increase in tensile modulus for

<table><caption>**Table 5**

Average values of tensile properties for PHBV and PHBV-based biocomposites.</caption><thead><tr><th></th><th>Tensile Modulus (GPa)</th><th>Tensile Strength (MPa)</th><th>Tensile strain at break (%)</th><th>Storage Modulus at 25 °C (GPa)</th></tr></thead><tbody><tr><td>PHBV</td><td>3.3 ± 0.5</td><td>35.4 ± 1.1</td><td>3.3 ± 0.1</td><td>6.7</td></tr><tr><td>Wood</td><td>5.7 ± 0.3</td><td>37.0 ± 0.7</td><td>1.1 ± 0.1</td><td>11.9</td></tr><tr><td>Treated wood</td><td>5.1 ± 0.2</td><td>33.3 ± 0.8</td><td>1.0 ± 0.1</td><td>9.8</td></tr><tr><td>Agave</td><td>4.4 ± 0.3</td><td>29.3 ± 0.4</td><td>1.2 ± 0.2</td><td>9.6</td></tr><tr><td>Macadamia</td><td>4.6 ± 0.1</td><td>28.2 ± 0.5</td><td>1.0 ± 0.1</td><td>9.5</td></tr><tr><td>Walnut</td><td>3.9 ± 0.5</td><td>24.2 ± 2.6</td><td>0.9 ± 0.1</td><td>7.5</td></tr><tr><td>Sorghum Stem</td><td>5.3 ± 0.2</td><td>31.3 ± 0.7</td><td>1.1 ± 0.2</td><td>10.0</td></tr><tr><td>Sorghum Leaf</td><td>4.4 ± 0.3</td><td>27.0 ± 0.8</td><td>1.0 ± 0.1</td><td>8.8</td></tr><tr><td>NS Wheat Bran</td><td>3.4 ± 0.5</td><td>21.7 ± 1.2</td><td>1.6 ± 1.8</td><td>6.0</td></tr><tr><td>Wheat Bran</td><td>4.5 ± 0.6</td><td>25.3 ± 0.7</td><td>1.0 ± 1.1</td><td>7.7</td></tr></tbody></table>

<figure><img src="image_5.png" /><figcaption>**Fig. 4.** Temperature dependence of Tan δ curves of PHBV and its PHBV-based biocomposites.</figcaption></figure>

<footnote>* From the Tan δ curve (DMA).</footnote>

<footnote>* Obtained by DMA analyses.</footnote>
<figure><img src="image_6.png" /><figcaption>Fig. 5. a. Tensile properties of PHBV and its PHBV-based biocomposites; Correlation between Tensile stress and b. Cellulose content, c. O/C ratio and d. %CI of cellulose.</figcaption></figure>

PHBV blended with 15 % walnut flour [56]. Similar trends were reported by Gallardo-Cervantes et al., who noted a 23 % reduction in tensile strength alongside an 11 % increase in tensile modulus with the incorporation of 20 wt% agave fibres [15]. As commonly reported in literature, the addition of organic biofillers leads to an embrittlement of the polymer with a drop in tensile strain [56]. Except for the NS Wheat Bran, PHBV-based biocomposites show a similar tensile strain with a three-fold reduction in comparison to the PHBV. The more moderate decrease in tensile strain for the NS Wheat Bran may be attributed to the less dispersed smaller biofillers in the PHBV matrix (Fig. 3.) which allow for a part of macromolecules greater freedom of motion during the tensile test.

Correlation between biofillers composition and tensile stress (and indirectly tensile modulus) were investigated. Pearson correlation coefficient of *r* = 0.49 (%Lig<sub>LA</sub>) and 0.40 (%Lig<sub>NMR</sub>), *r* = -0.27 (%Hemi<sub>CA</sub>) and -0.35 (%Hemi<sub>TGA</sub>), *r* = 0.58 (%Cell<sub>CA</sub>) and 0.72 (%Cell<sub>TGA</sub>) were observed. The Pearson correlation coefficient reveals a weak, positive correlation between lignin content and the mechanical properties (Fig. S5 in Supplementary Data). In fact, native lignin, also referred to as protolignin (non-extracted lignin), is primarily hydrophobic with a low proportion of polar hydroxyl groups. This limited polarity restricts its ability to effectively interact with PHBV, which may explain its relatively nonspecific contribution to the material's mechanical properties [71]. Similarly, the evolution of mechanical properties with hemicellulose content shows a negative weak correlation (Fig. S6 in Supplementary Data). Hemicellulose contains a large amount of hydroxyl groups, which interact naturally with lignin methoxy groups [72] and β-glucan backbone chains of amorphous cellulose [73–76]. Covalent interactions between lignin and hemicelluloses were also reported [77]. The hemicellulose bridging role between lignin and amorphous cellulose may limit its ability to interact with PHBV biopolymer, thereby reducing its potential for acting as a key factor in tensile properties. However, the low tensile strength of hemicellulose [78,79], means that it could lead to a reduction in mechanical properties if it is directly interacting with PHBV. This is somewhat reflected by the negative correlation coefficient. On the other hand, cellulose content shows a positive moderate correlation with mechanical properties (Fig. 5.b). Nuez et al. already reported the relationship between cellulose content in organic biofillers and tensile stress [21].

The O/C ratio obtained from XPS analysis serves as an indicator of the surface hydrophilicity of the biofillers [80]. A higher O/C ratio correlates with an increased concentration of hydroxyl groups on the

biofiller surface. The strong positive correlation (*r* = 0.78) between O/C ratio and tensile stress could suggests that higher hydroxyl group content facilitates formation of hydrogen bonds between the biofiller and the PHBV matrix, leading to improved mechanical performance (Fig. 5. c). Additionally, a positive strong relationship is observed between the Crystallinity Index (CI) of cellulose observed by XRD (%CI<sub>XRD</sub>) and the tensile stress, with correlation coefficients of *r* = 0.81. This correlation is more moderate with the Crystallinity Index (CI) of cellulose defined by ssNMR (%CI<sub>SSNMR</sub>) with *r* = 0.68 (Fig. 5.d). Cellulose microfibrils naturally reinforce organic fibres/fillers, and the CI of cellulose is one of the key indicators of their performance [81,82]. Furthermore, crystalline cellulose is known for its amphiphilic properties, with crystal surfaces (110) and (11̄0) displaying hydroxyl groups (Iβ allomorph). It can be hypothesized that the high mechanical properties of PHBV-based biocomposite result from PHBV's ability to interact with the biofiller's cellulose at their interface. Cellulose microfibrils effectively facilitate stress transfer from the interface to the bulk biofiller. Therefore, a combination of hydrophilic cellulose at the surface of reinforcing biofiller and a strong internal cellulose structure (network of microfibrils) could be key factors contributing to the high mechanical properties of the PHBV-based biocomposite. These explanations could account for the higher correlation observed with CI<sub>XRD</sub> compared to CI<sub>SSNMR</sub>, as the former considers the %CI from the overall composition of the biofillers (amorphous cellulose, hemicellulose, lignin...).

Regarding other materials or PHBV-based biocomposite characteristics that could influence mechanical properties, such as the biofiller shape (aspect ratio), PHBV molecular weight, or PHBV crystallinity, biofiller dispersion, porosity in the PHBV-based biocomposite, the correlation coefficients are all *r* < 0.2. This suggests that these factors have a minimal or negligible impact on the evolution of the mechanical properties in the context of this study.

The failure surfaces of specimens after tensile test were observed by SEM and presented in Fig. 6. The biofiller footprints observed on the failure surface of Agave, Sorghum Leaf and Stem, NS Wheat Bran biocomposites suggest a biofiller pull-out mechanism from the PHBV matrix during the tensile test. A closer examination reveals residual biofiller components within the footprint, indicating biofiller delamination during mechanical stress. A significant proportion of broken biofillers is also visible on the failure surface. Beyond interfacial considerations, this observation supports the assumption that the weak internal structure of the biofillers contributes to the lower mechanical properties. According to the theory of critical embedded length (Lc), calculated using the
<figure><img src="image_7.png" /><figcaption>Fig. 6. Surface fractures observed by SEM of PHBV-based biocomposite after tensile test.</figcaption></figure>

Kelly-Tyson formula, the breakage of these biofillers, which have a very low aspect ratio (≤ 5), may seem surprising [83]. Given that the Interfacial Shear Strength (IFSS) of PHB ranges from 5 to 10 [83] and the tensile strength of Sorghum stem is between 208 and 280 MPa [84], the expected Lc for this biofiller, in the worst case, should be approximately 400 µm. Since the length of the biofiller is only half of the expected value, a pull-out process is more likely to occur than delamination of the biofillers, which has not been observed in this case. Furthermore, for the Agave biomass obtained after the fermentation process (which involves temperature and water immersion), hydrolytic cleavage of cellulose chains may occur, leading to a reduction in the performance of the microfibrils and a subsequent decline in the mechanical properties of the PHBV-based biocomposite [85]. For these biocomposites a strong positive correlation of r = 0.98 with XRD and r = 0.96 with ssNMR (Fig. S7 in Supplementary Data), is observed between the %CI and tensile strength.

NS wheat bran, which undergoes a delamination process and breakage due to the weak interfacial properties between its structural layers [86], exhibits the lowest biocomposite tensile strength. In contrast, the sorghum stem biocomposite, which also exhibits delamination but shows a higher potential for interfacial interaction with PHBV, presents the highest tensile strength for this range of biofillers.

For Wood and Treated wood biocomposites, distinct deep and clean footprints suggest a pull-out process without biofiller delamination, which is consistent with the strong biofiller structure expected from these biomass sources (indicated by the higher CI of cellulose). The smooth surface of the pulled-out biofillers further suggests a PHBV coating, indicating good interfacial properties between the biofiller and PHBV. For the Macadamia, Walnut, and Wheat Bran biofillers, the circular shape and shallower footprints from biofiller on the failure surface may be a key factor explaining the reduced mechanical properties of the PHBV-based biocomposite (as less energy is required to pull out the biofillers). For this range of biofillers a strong positive correlation of r = 0.87 (Fig. S8 in Supplementary Data) between the biofiller's aspect ratio and tensile strength is notable. These imaging observations suggest a complex combination of different mechanisms leading to failure, including shape considerations and material properties. However, the strong relationship with cellulose content, hydrophilic surface, and cellulose crystallinity (CI) indicates that these factors play a more

dominant role than others.

## 4.7. Rheological behaviour

Complex viscosity of PHBV and its PHBV-based biocomposites as a function of angular frequency at 185 °C is presented in Fig. 7.a and all the extracted data are summarized in the Table 6. The rheological test was conducted over a range of angular frequencies, from high to low (from 630 to 0.063 rad·s⁻¹). For the neat PHBV, the observed increase in viscosity with decreasing angular frequency is attributed to the shear-thinning behaviour of the polymer. At approximately 10 rad·s⁻¹, the viscosity curve exhibits a maximum, followed by a decline at lower frequencies. It is likely due to the limited thermal stability of PHBV at 185 °C, which can lead to thermal degradation through chain scission and as consequent reduction in viscosity over the time of analysis. All the PHBV-based biocomposites exhibited a reduction in magnitude of complex viscosity at high angular frequency (>10 rad·s⁻¹). Contrary to what is typically observed in filled biocomposites [87,88], addition of biofillers did not result in an increased shear-thinning effect (i.e., stronger slopes of the viscosity curves) compared to neat PHBV. Reduction in viscosity magnitude is likely attributed to a decrease in the molecular weight of PHBV within the biocomposites, leading to fewer chain entanglements, and/or to a plasticizing effect from certain biofiller components present in the matrix, such as extractives or lignin [66,89]. For example, Mousavioun et al. have already highlighted the possible plasticising effect of lignin in PHBV-based biocomposite [65]. The positive strong correlation (r = 0.86) between the Tg and viscosity at 630 rad/s could support this last assumption (Fig. 7.b).

An abrupt viscosity increase at low frequency is observed for the Wood, NS Wheat Bran, and Sorghum Stem (Fig. 7.a). This effect is known as rheological percolation threshold and comes from disturbing individual chains' mobility of polymer under shear force by the presence of (bio)fillers network, which increases the complex viscosity. In fact, at lower angular frequency, the polymer chain has more time to recover (relax) to its original state after the strain, but (bio)fillers can act as obstacles to macromolecule relaxation which increases the viscosity. The percolation threshold is less pronounced or does not appear for Agave, Treated wood, Sorghum Leaf, Macadamia, Wheat Bran and
<figure><img src="image_8.png" /><figcaption>Fig. 7. a. Angular frequency dependence of Complex viscosity for PHBV and its PHBV-based biocomposites; Correlation between b. Complex viscosity at 630 rad/s and Tg, c. Complex viscosity at 0.630 rad/s and biofiller aspect ratio and d. Storage Modulus at 0.630 rad/s and biofiller aspect ratio.</figcaption></figure>

<table><caption>**Table 6**

Extracted data from oscillatory rheology analyses.</caption><thead><tr><th></th><th>Complex viscosity<br>at 0.63 rad/s (Pa·S)</th><th>Complex viscosity<br>at 630 rad/s (Pa·S)</th><th>Storage modulus G'<br>at 0.63 rad/s (MPa)</th></tr></thead><tbody><tr><td>PHBV</td><td>107</td><td>154</td><td>8.7E-07</td></tr><tr><td>Wood</td><td>685</td><td>95</td><td>1.5E-05</td></tr><tr><td>Treated<br>wood</td><td>114</td><td>75</td><td>1.9E-06</td></tr><tr><td>Agave</td><td>147</td><td>59</td><td>2.5E-06</td></tr><tr><td>Macadamia</td><td>103</td><td>59</td><td>1.4E-06</td></tr><tr><td>Walnut</td><td>40</td><td>27</td><td>5.5E-07</td></tr><tr><td>Sorghum<br>Stem</td><td>382</td><td>54</td><td>1.1E-05</td></tr><tr><td>Sorghum<br>Leaf</td><td>254</td><td>81</td><td>4.3E-06</td></tr><tr><td>NS Wheat</td><td>527</td><td>54</td><td>1.3E-05</td></tr><tr><td>Bran</td><td></td><td></td><td></td></tr><tr><td>Wheat Bran</td><td>55</td><td>38</td><td>1.0E-06</td></tr></tbody></table>

Walnut biofillers. A positive strong coefficient of correlation *r* = 0.85 was observed between the biofiller shape (given by aspect ratio) and the viscosity at 0.063 rad/s (Fig. 7.c). A higher aspect ratio generates a more randomly oriented biofiller network, higher specific surface, which creates more flow resistance (extra energy for dissipation) and increases the viscosity. On the other hand, a more circular shape reduces biofillers orientation, specific surface in contact with polymer and the induced friction with macromolecules, which can flow more freely around the reinforcement [25].

It appears an even stronger relationship between the biofiller aspect ratio and the storage modulus (G', *r* = 0.92) (Fig. 7.d). G' reflects the elasticity of the material and this increase can be directly correlated by the mobility restriction of macromolecules due to the physical presence of biofillers. The high viscosity of the NS Wheat Bran biocomposite at low shear rates may also result from the broader size distribution of the biofillers as observed in Fig. 3.

No correlation (*r* < 0.1) with other factors such as cellulose content, O/C, CI of cellulose, or PHBV molecular weight where observed. It can be assumed that change in viscosity at low frequency is more related to

the physical presence of the reinforcing biofillers (packing effect) characterized by their shapes than to the specific biofillers-polymer interaction.

From an engineering perspective, the observed reduction in viscosity for PHBV-based biocomposites at higher shear rates can be seen as a beneficial effect for their processability on industrial equipment such as injection moulding.

## 5. Conclusions

In the first part of this study, the composition and shape of various biomass fillers derived from biomass (Australian industrial co-products) were assessed. Using Pearson's correlation coefficient, the analyses revealed a strong correlation between evaluation of the biofillers' composition by carbohydrate (hemicellulose and cellulose), lignin analyses and indirect methods using TGA and ssNMR. Given the wide variety of reinforcing biofillers available around the world, this creates an opportunity for using conventional characterisation equipment to compare and assess the composition of biofillers effectively.

In the second part of the study, the contribution of key characteristics from biofillers on the thermal, mechanical, and rheological properties of PHBV-based biocomposites were investigated. Although no single key factor was identified to explain the evolution of the thermal properties of PHBV-based biocomposites, a positive relationship was observed between the mechanical properties and the following factors, listed in order of the highest Pearson's coefficient correlation assessed: the cellulose ratio, the hydrophilicity of the biofillers, and the crystallinity index of cellulose (%CI). This suggests that optimal mechanical performance of PHBV-based biocomposites can be achieved with biofillers that have a high proportion of hydroxyl groups from cellulose on their surface and a robust internal cellulosic structure. In this study, the performance of the cellulosic structure was correlated with %CI, though it likely also involves factors such as the molecular weight of cellulose, fibril orientation, organization, and entanglement.

Additionally, a 60 % difference in mechanical properties between the worst and best biofillers highlight the critical importance of selecting the appropriate biofiller when manufacturing PHBV-based biocomposites
and how this process alone can sometimes result in better mechanical enhancements than using chemical treatments.

Regarding the rheology behaviour, a strong correlation was observed between the complex viscosity at low shear rate and the aspect ratio of biofillers whereas the complex viscosity at higher shear rate could be influenced by as plasticizing effect from biofillers component such as extractives or/and lignin.

Despite the significant differences in the nature and composition of the biofillers, as well as the various mechanisms influencing the bio- composite properties, some key factors were identified to have a remarkable impact on the mechanical performance and rheological behaviour of PHBV-based biocomposites, independently of the biofiller nature (e.g., nutshell, stem, leaf) and origin (e.g., date and location of growth). These findings provide a solid foundation for establishing a comprehensive platform for the development of high-performance PHA- based biocomposites reinforced biofillers, as a promising base to design, develop and manufacture, eco-friendly products such as rigid packaging or plan clips for farming. Further studies are needed to enhance our understanding, including more detailed characterisation of the cellu- losic properties and their organization within the biofillers, as well as a more in-deep assessment of the crystalline microstructure evolution, such as the interfacial transcrystallinity process between PHBV and the biofillers. Finally, the effect of biofillers on water absorption and the biodegradation behaviour of PHBV-based biocomposites should be investigated as another biocomposite characteristic, to complete this framework.

CRediT authorship contribution statement

**Vincent Mathel:** Writing – review & editing, Writing – original draft, Visualization, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Theo Le Gagne:** Investigation, Formal analysis, Data curation. **Xavier Falourd:** Writing – review & editing, Visualization, Investigation, Formal analysis. **Catherine Deborde:** Writing – review & editing, Investigation. **Lucie Le-Bot:** Investigation, Formal analysis, Data curation. **Alain Bourmaud:** Writing – review & editing, Resources, Methodology, Investiga- tion, Formal analysis. **Johnny Beaugrand:** Writing – review & editing, Resources, Methodology, Investigation, Formal analysis. **Luigi-Jules Vandi:** Writing – review & editing, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization.

Declaration of competing interest

The authors declare no conflict of interest.

Acknowledgements

The authors would like to thank the Queensland Government for funding through the Advance Queensland Industry Research Fellowships Scheme (Grant No. AQIRF065-2019RD2) and the funding from the PEPR program RECYCOMP from France 2030The authors also wish to thank the Materials Testing Laboratory from School of Mechanical & Mining Engineering. VM and LV acknowledge the contribution of Dugalunji Aboriginal Corporation on behalf of the Indjalandji-Dhidhanu peoples through use of the MorFI equipment. The authors would like to sincerely thank Anthony Magueresse (Université Bretagne Sud) for his support in producing the SEM images of the biocomposite surface fractures. The authors would like to express their sincere gratitude to experts on INRAE for their time and expertise, especially Lèna Brionne for characterizing the composition of biofillers by the carbohydrate and lignin methods.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.susmat.2025.e01471.

Data availability

Data will be made available on reasonable request.

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