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Epoxy Coating of Biofiber: An Effective Modifier of Biofiber Physical and Flow Properties for Improved Tensile Behavior of Biofiber-Reinforced Biocomposite

Oluwafemi A. Oyedeji1,*, Xianhui Zhao1, Jenesis Cochrane2, Hannah Snider3, Hannah Ruth Brown1, Tomas Grejtak4, Jun Qu4, C. Luke Williams5, Erin Webb1


Published in Journal of the ASABE 67(6): 1447-1458 (doi: 10.13031/ja.16018). 2024 American Society of Agricultural and Biological Engineers.


1 Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA.

2 Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, USA.

3 Department of Chemical Engineering, Rose Hulman Institute of Technology, Terre Haute, Indiana, USA.

4 Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA.

5 Energy and Environment Science and Technology, Idaho National Laboratory, Idaho Falls, Idaho, USA.

* Correspondence: oyedejia@ornl.gov, demolaoye@gmail.com

The authors have paid for open access for this article. This work is licensed under a Creative Commons Attribution NonCommercial NoDerivatives 4.0 International License https://creative commons.org/licenses/by nc nd/4.0/

Submitted for review on 29 March 2024 as manuscript number ES 16018; approved for publication as a Research Article by Associate Editor Dr. Deepak Kumar and Community Editor Dr. Kasiviswanathan Muthukumarappan of the Energy Systems Community of ASABE on 19 September 2024.

Mention of company or trade names is for description only and does not imply endorsement by the USDA. The USDA is an equal opportunity provider and employer.

Citation: Oyedeji, O. A., Zhao, X., Cochrane, J., Snider, H., Brown, H. R., Grejtak, T., … Webb, E. (2024). Epoxy coating of biofiber: An effective modifier of biofiber physical and flow properties for improved tensile behavior of biofiber-reinforced biocomposite. J. ASABE, 67(6), 1447-1458. https://doi.org/10.13031/ja.16018

Highlights

Abstract. Biocomposites combine renewable, plant-based fibers with degradable polymers and are an attractive option for sustainable, lightweight, and cost-effective materials with a low carbon footprint, especially for large-scale additive manufacturing. One of the major challenges in the widespread adoption of biocomposites is that their mechanical performance is significantly inferior to that of synthetic composites. Surface treatment is a common and effective technique to improve the mechanical properties of the biofibers used in biocomposites. This study aims to investigate the physical and flow properties of surface-treated biofibers, as well as the tensile properties of their PLA-based biocomposite, to gain insights into how surface treatment changes the fiber’s characteristics and biocomposite’s mechanical properties. Surface treatment was created using a two-component epoxy system by reacting poly(bisphenol A-co-epichlorohydrin) glycidyl end-capped (PBG) and dicyandiamide (DICY). The treatment was tested on two different biofibers (loblolly pine and corn stover fibers) with three different PBG/DICY molar ratios (0.25, 0.5, and 2). Results showed that surface-treated fibers improved the tensile strength and Young’s modulus of the biocomposites. Loblolly pine biocomposites from fibers treated with a PBG/DICY ratio of 0.25 exhibited the best tensile properties. The surface treatment resulted in a more loosely dispersed fiber bulk structure, as evidenced by less fiber agglomeration into smaller particle sizes, higher fiber sphericity, and lower loose bulk density. This can enhance stress distribution and the overall mechanical performance of the biocomposites. Additionally, surface-treated fibers exhibited better dynamic flow properties.

Keywords.Fiber size and shape, Fiber surface roughness, Flow properties, PLA-based biocomposite, Surface treatment.

Biocomposites provide numerous advantages that make them an attractive option for various industries seeking sustainable, lightweight, and cost-effective materials. One key advantage of biocomposites is their low carbon footprint compared to traditional, fossil fuel-based materials like carbon fiber-reinforced composites. Biocomposites combine the benefits of biogenic carbon sequestration within renewable, plant-based fibers (e.g., hemp, bamboo, loblolly pine, and corn stover) with degradable polymers (e.g., polylactic acid (PLA) and polyhydroxyalkanoates (PHA)) to open numerous possibilities for sustainable applications and decarbonize the U.S. manufacturing sector. In addition to their eco-friendliness, biocomposites exhibit a desirable combination of cost-effectiveness and passable mechanical properties, including a good strength-to-weight ratio and stiffness. Numerous researchers have demonstrated the feasibility of manufacturing large-scale objects, such as automotive components, furniture, and construction elements, using large-scale additive manufacturing biocomposites.

This study selected PLA as the polymer matrix of interest due to its unique attributes that align with our sustainability, biodegradability, and environmental impact reduction goals. PLA is a biodegradable, thermoplastic polymer derived from renewable resources, such as corn starch or sugarcane, making it an eco-friendly alternative to traditional petroleum-based polymers (Sinha Ray and Banerjee, 2022). Additionally, when compared to other biodegradable polymers, such as PHA, PLA offers a balance of mechanical performance, availability, and cost (Sinha Ray and Banerjee, 2022), with a tensile strength of 47–54 MPa and Young's modulus of 1.8–3.8 GPa (Herbst et al., 2024; Panaitescu et al., 2017; She and Xu, 2023; Zhao et al., 2019), compared to PHA's tensile strength of about 35 MPa and Young's modulus of 4.7 GPa (Vu et al., 2022).

In the realm of mechanical properties and performance, biofiber reinforcements are at a disadvantage compared to synthetic fiber reinforcements. Biofibers, comprising natural, organic polymers like cellulose, hemicellulose, and lignin, are characterized by their significant hydrophilicity, resulting in deficient interfacial bonding when combined with polymers (Jawaid and Khalil, 2011). Table 1 summarizes the tensile properties of different natural and synthetic fiber/PLA composites, highlighting the disparity in the mechanical properties of biofiber reinforcements and synthetic fiber reinforcements. The existence of this mechanical performance gap implies that the adoption of sustainable materials is currently constrained to applications requiring low-strength performance. Hence, extensive research endeavors to enhance the mechanical performance of biofiber reinforcements, especially in biocomposites, to accelerate the displacement of traditional composites are imperative.

Table 1. Comparison of the tensile properties of some PLA-based composites.
Fiber[a]Tensile
Strength
(MPa)
Young's
Modulus
(GPa)
Reference
Loblolly pine59 – 714.93 – 5.40Zhao et al. (2020)
Poplar39 – 500.85 – 1.69Yang et al. (2020)
Kenaf45 – 551.41 – 6.97Ismail and Ishak (2018)
Corn stover52 – 574.14 – 4.42Zhao et al. (2022)
Switchgrass50 – 533.93 – 4.23Zhao et al. (2022)
Hemp41 – 455.63 – 7.40Hu and Lim (2007)
Hemp (alkaline)39 – 557.60 – 8.50Hu and Lim (2007)
Hemp51 – 683.50 – 7.52Sawpan et al. (2011)
Hemp (alkaline)51 – 763.50 – 8.15Sawpan et al. (2011)
Hemp (silane)51 – 713.50 – 7.86Sawpan et al. (2011)
Hemp (alkaline + silane)51 – 733.50 – 8.01Sawpan et al. (2011)
Bamboo43 – 602.68 – 6.30Wang et al. (2014)
Silvergrass22 – 250.65 – 0.66Ma et al. (2020)
Reed16 – 190.54 – 0.57Ma et al. (2020)
Switchgrass20 – 230.54Ma et al. (2020)
Pennisetum19 – 220.50 – 0.51Ma et al. (2020)
Silvergrass (alkaline + H2O2)25 – 290.72Ma et al. (2020)
Silvergrass (H2SO4)24 – 260.63 – 0.64Ma et al. (2020)
Silvergrass (steam explosion)25 – 280.68 – 0.69Ma et al. (2020)
Carbon fiber84 – 1086.84 – 14.72Chen et al. (2014)
Glass fiber158 – 1868.50 – 17.50Li et al. (2023)

    [a] Information in parenthesis represented pretreatment performed on biofiber. The tensile strength and Young’s modulus of pure PLA are 58 – 63 MPa and 2740 – 3169 MPa, respectively (Chen et al., 2014; Ma et al., 2020; Zhao et al., 2020; Zhao et al., 2022).

The existing body of literature encompasses a diverse range of biofiber treatment methods, either to improve the mechanical performance of biofiber or strengthen the interfacial bonding between biofibers and the polymer matrix. These treatments include both physical interventions (stretching, calendaring, corona and thermal treatments, plasma treatments, and yarn creation) and chemical processes (alkaline treatment, bleaching, acetylating, benzoylation, vinyl grafting, and peroxide treatment) (Nurazzi et al., 2021). Given the economic appeal of biofibers over synthetic fibers, the logical approach to enhancing the mechanical properties of biofibers involves employing affordable and efficient surface treatment methods. One particularly promising and innovative technique is the epoxy coating of biofiber, which has demonstrated remarkable efficacy in enhancing interfacial bonding and bolstering degradation resistance. In theory, the epoxy coating process uses a dilute resin (epichlorohydrin with bisphenol A and diphenylol propane) to penetrate the pores of the biofibers and envelope the fiber surface with a thin layer of the resin. This results in a cleaner and rougher surface, enabling strong interlocking and binding between the biofibers and polymer matrix. Consequently, the resulting biocomposites exhibit significantly enhanced mechanical properties compared to their untreated counterparts.

Some examples of empirical studies in the literature in which epoxy-coated biofibers were analyzed include Owen et al. (2018), Zhao et al. (2020), and Sujaritjun et al. (2013). Owen et al. (2018) delved into the thermal stability and tensile properties of epoxy-coated (untreated and treated) kenaf fibers incorporated into recycled polyethylene terephthalate (RPET) polymer, with a focus on silane and sodium hydroxide treatments before epoxy coating. The epoxy-coated kenaf/RPET composites produced the best thermal stability and tensile properties among different treatments, suggesting that the preemptive chemical treatment of the kenaf fiber before epoxy coating is unnecessary. Zhao et al. (2020) extended this exploration by investigating the thermal and tensile properties of epoxy-coated pine fibers incorporated into PLA polymer. They found a non-linear correlation between the tensile properties of epoxy-coated pine/PLA composites and the fiber-to-epoxy mass ratio. The fiber-to-epoxy mass ratio of 30:1 produced the highest tensile strength and Young’s modulus, with a 20% improvement in tensile strength and 82% improvement in Young’s modulus relative to neat PLA. Zhao et al. (2020) also proposed a mechanism for the PLA/epoxy/biofiber interaction in which the pores on the surface of the biofibers are filled, enabling the epoxy to penetrate and interlock with the biofibers. The epoxy-modified biofibers interact with PLA through cross-linking reactions of the epoxide groups with the amine and carboxyl groups, enhancing the fiber-matrix interface. Sujaritjun et al. (2013) approached the subject from a broader perspective, investigating the composite performance of different epoxy-coated biofibers (bamboo fiber, vetiver grass fiber, and coconut fiber). They revealed that the enhancement potential of epoxy coating on biocomposites varies according to the type of biofiber employed. Among these, bamboo fiber demonstrated the most pronounced improvement, while vetiver grass fiber exhibited a comparatively modest enhancement.

Furthermore, in the context of potential commercial applications (such as building, automotive, aerospace, and packaging), the widespread utilization of epoxy coating on biofibers necessitates a comprehensive understanding of the challenges and benefits of large-scale fiber transportation and handling. The efficient and effective design of material handling systems (e.g., conveyors, screw augers, and storage bins) rely heavily on a thorough understanding of the dynamic flow properties of the target bulk particulate material (Fasina, 2006; Oyedeji and Fasina, 2017). We postulate that applying epoxy coating to biofibers will likely induce changes in their dynamic flow properties.

This paper therefore aims to delve into the intricate interplay between epoxy coating and the physical attributes of fibers, including their flow characteristics, and examine the resultant changes in surface properties. By addressing these fundamental aspects, this study seeks to shed light on the pivotal role that epoxy coating plays in shaping the behavior of biofibers within industrial contexts. Through a rigorous investigation of these multifaceted effects, we aim to contribute valuable insights that could inform the design and implementation of efficient and reliable processes for the commercial application of epoxy-coated biofibers.

Materials and Methods

Materials

This study utilized two different biofibers (fig. 1), corn stover (agricultural residue) and loblolly pine (woody energy crop), representing a significant portion of the current and potential lignocellulosic biomass supply in the United States. PLA pellets (biopolymer 4043D) were procured from NatureWorks LLC (Minnetonka, MN). The epoxy utilized in this study comprises a resin and a curing agent, both procured from Sigma-Aldrich Co. (St. Louis, MO). Poly(bisphenol A-co-epichlorohydrin), glycidyl end-capped (PBG, CAS: 25036-25-3, number average molecular weight: ~355), is used as an epoxy resin, and dicyandiamide (CAS: 461-58-5, molecular weight: ~84 g/mol) is used as a curing agent. Methanol (CAS: 67-56-1) was procured from VWR International, LLC (Radnor, PA).

Figure 1. Biomass samples used in this research: (a) loblolly pine fibers and (b) corn stover fibers.

Biofiber Preparation

The Biomass Feedstock National User Facility (BFNUF) at Idaho National Laboratory (INL) provided the loblolly pine and corn stover fibers for the research. The loblolly pine was originally sourced from Edgefield, South Carolina, while the corn stover was obtained from Story, Iowa. Both the loblolly pine and corn stover fibers used in the research were dried to ~12% moisture content and grinded to pass through 0.2 mm sieves. Table 2 summarizes the biochemical properties of the biofibers considered in this study.

Table 2. Biochemical properties (mean ± standard deviation) of the fibers (loblolly pine and corn stover) used in this study.
Biochemical PropertyCorn StoverLoblolly Pine
Ash content (wt.%)4.2 ± 0.40.2 ± 0.0
Extractives content (wt.%)8.0 ± 0.32.6 ± 0.3
Cellulose content (wt.%)33.1 ± 1.440.4 ± 0.1
Hemicellulose content (wt.%)27.2 ± 0.919.7 ± 4.7
Lignin content (wt.%)15.9 ± 1.327.4 ± 0.2
Mass balance (wt.%)95.3 ± 0.697.4 ± 4.6

Biofiber Surface Treatment

Epoxy-coated fibers were prepared using an impregnation method, following the steps described in our earlier work (Zhao et al., 2020). PBG and dicyandiamide (hereafter referred to as the epoxy) were combined in a specific molar ratio (0.25, 0.5, or 2) and dissolved to form 8 wt% solutions of epoxy in methanol (the epoxy counted 8 wt%, and methanol counted 92 wt%). The solution was prepared by sequentially adding PBG to a glass vial, followed by dicyandiamide and methanol. The solution was thoroughly vortexed before use. The epoxy solution was gradually and evenly doped across the fibers to prepare samples with a mass ratio of 1:30 epoxy to biomass fibers. The epoxy solution and fibers were thoroughly mixed and allowed to dry for 15 minutes at room temperature to facilitate methanol evaporation. The samples were then dried at 60°C for ~48 hours before characterization and compounding.

Particle Size and Shape Measurement

We conducted particle size and shape measurements for each biofiber sample utilizing Microtrac’s PartAn3D dynamic image particle analyzer (PartAn3D, Microtrac Inc., York, PA). About 5 g of the sample was placed in the hopper of the analyzer and traveled along the vibrating feeder before falling through the sensing zone or measurement field, where its size and shape parameters were measured. The analyzer captures high-speed, high-resolution images as particles fall and tumble through its camera’s sensing zone. Subsequently, the analyzer’s software methodically analyzes these images to estimate the size and shape parameters of individual biofibers. The biofiber’s 3D length, width, and thickness were determined as its largest maximum, largest minimum, and smallest minimum Feret diameters, respectively. The biofiber’s area and perimeter were determined as the average area and circumference extracted from a sequence of the 3D images of the biofiber. The following biofiber size and shape parameters were calculated based on the biofiber’s length, width, thickness, and area:

(1)

(2)

(3)

(4)

(5)

(6)

The analyzer has a theoretical capability to measure particles in the range of 0.035 mm to 35 mm. However, during our preliminary investigation, we encountered challenges in effectively and consistently analyzing fine biofibers due to the formation of aggregates caused by static attraction among the biofibers. Consequently, we fractionated each biofiber sample before size and shape measurement, specifically removing biofibers passing through the 180 µm screen. This strategic step enhanced the precision of the biofiber size and shape measurement process. Finally, we recorded the mass fraction of those biofibers passing through the 180 µm screen. The protocol for measuring particle size and shape was repeated three times for each biofiber sample.

Flow Properties Measurement

An FT4 powder rheometer (Freeman Technology, Ltd., Tewkesbury, Gloucestershire, UK) was used to measure the flow properties of each biofiber. For each test, we used a glass sample vessel with a diameter of 50 mm and a volume of 85 ml. We filled the sample vessel, leveled the biofiber material across the top of the vessel to form a flat surface, and then securely positioned the vessel on the rheometer. We conducted various flow tests, including compressibility, stability, variable flow rate, shear cell, and wall friction tests, each with unique testing procedures. We conducted each flow test measurement twice.

To assess compressibility, the biofiber samples were compressed with a vented piston at a steady rate of 0.05 mm/s until consolidating pressures of 0.5, 1, 2, 4, 6, 8, 10, 12, and 14 kPa were attained sequentially. The vented piston was held at each consolidation pressure for 1 minute before compression was continued to attain the subsequent consolidation pressure. The rheometer's software recorded, displayed, and saved real-time bulk density measurements at various consolidating pressures throughout each experimental cycle. Then, we computed the compressibility index (CI) following equation 7 and developed the corresponding compressibility curve.

(7)

The dynamic flow tests (stability and variable flow rate tests) gauge the flowability of the biofiber under varying stress conditions and its tendency to change form due to flow stress. To assess the dynamic flow properties of each biofiber, we moved a rotating FT4 powder rheometer’s blade (helix angle = -5°) through the filled sample vessel, measuring the total energy consumed during the test cycle. The stability test involves seven test cycles (Cycles 1–7) with identical blade tip speed (100 mm/s during the downward traverse and 60 mm/s during the upward traverse). Conversely, the variable flow test involves four test cycles (Cycles 8–11) with different blade tip speed of 100 mm/s, 70 mm/s, 40 mm/s, and 10 mm/s, respectively, during the downward traverse. The upward traverse maintains a constant blade tip speed of 60 mm/s throughout these test cycles. A conditioning cycle (blade tip speed = 60 mm/s during both downward and upward traverse) was performed before each test cycle of the stability test and variable flow test, providing a consistent sample state for the test cycles. Subsequently, we calculated the stability index (SI), specific energy (SE), and flow rate index (FRI) for each biofiber as expressed in equations 8–10, respectively.

(8)

(9)

(10)

We used the shear-cell test to measure the shear properties of each biofiber in accordance with ASTM standard D7891 (2015). The FT4 powder rheometer’s shear cell head was used to simultaneously apply normal stress (15, 9, 8, 7, 6, or 5 kPa) and induce rotational shear stress at 18°/min until a biofiber material bed shears, yielding the point of incipient failure. Then, the FT4 powder rheometer’s software automatedly applied Mohr circle analysis to extract the cohesion, unconfined yield strength, major principal stress, flow function, and ultimately the angle of internal friction (AIF) of each biofiber from the series of points of incipient failure at the different normal stresses.

Finally, we used the wall friction test to measure the flow behavior of biofiber relative to a surface in accordance with ASTM standard D7891. To assess the wall friction properties of the biofibers, we used the FT4 powder rheometer’s wall friction disk assembly (316 stainless steel surface with an average roughness factor of 1.2 µm) to simultaneously apply normal stress (15, 9, 8, 7, 6, or 5 kPa) and induce rotational shear stress at 18°/min until a biofiber material bed shears. The FT4 powder rheometer’s software automatedly determines the wall angle of friction using the data of applied normal stresses and their corresponding wall shear stress.

Biofiber Surface Roughness Measurement

The surface roughness and topography of the biofiber samples were measured using a laser digital microscope (3D Surface Profiler, VK-X3000, Keyence, Itasca, IL). A total of ten measurements were taken on ten particles of each biofiber type. The measurements were performed with a 50X objective on randomly selected regions. To eliminate the effect of the particle edges, the region of interest was selected from a center area of the measured topography. The final surface topography was then flattened using a plane tilt correction method. Two surface roughness parameters, Sa and Sz, were determined to characterize the surface roughness of the biofiber particle. Sa is the arithmetic mean height, and Sz represents the total peak-to-valley height of the measured area. Sa and Sz data were represented as an average and standard deviation of the ten measurements. Postprocessing of the measured surface topography, including calculation of Sa and Sz, was performed with MultiFile Analyzer software (Version 3.3.1.85 Keyence, Itasca, IL). A one-way ANOVA test (a=0.05) was performed to determine statistical differences in Sa and Sz between the means of the analyzed biofiber particles using Excel’s Anova: Single Factor function.

Biocomposite Preparation

The biocomposite preparation procedure aligns with the methodologies elucidated in our prior publications (Zhao et al., 2020; Zhao et al., 2022). Forming the biocomposite samples involved melt compounding, hot-pressing, and compression molding the fibers with PLA. PLA particles were gradually loaded into a shear mixer (C.W. Brabender Instruments, Inc.) operating at 180°C and 60 revolutions per minute (rpm). After mixing the PLA for 2 minutes, the fibers were gradually loaded into the shear mixer. The compounding of the fibers and PLA was conducted for 5 minutes, and the collected biocomposite material was used for hot-pressing. The total fiber content in all biocomposites was fixed at 30 wt% with an epoxy content (1 wt%) during epoxy-coating cases. Samples were loaded into a mold (length x width x thickness: 100 mm x 100 mm x 1.65 mm) and hot pressed at approximately 4536 kg (5 tons) for 5 minutes in a Carver Laboratory press (Fred S. Carver Inc.). The plates were then cooled to 60°C within the press until they were removed and further cooled to room temperature. The resulting sample was cut into multiple slit-shaped bars. The slit-shaped bars were then vertically stacked (like envelope stacking) and compression-molded in the Carver press at 180°C to form uniform bars. The bars were then cooled to 60°C within the press until they were removed and further cooled to room temperature. After forming the bars, the edges were routed using a Tensilkut router (model number: 10-21, Tensilkut Engineering Division Sieburg Industries, Inc.) to form dog bones with a width between 0.3175 – 0.3429 cm (0.12 – 0.135 inches).

Biocomposite Tensile Properties Measurement

Tensile of dog-bone specimens were conducted on a servo-hydraulic testing machine (assembled at Oak Ridge National Laboratory (Zhao et al., 2022)) to determine Young’s modulus and tensile strength of the biocomposites. We used a Universal MX8 Vi software with a strain stroke channel set at 3 inches, a rate of 0.001 inch/sec, and a true strain rate of 0.001. The width, thickness, and gauge length of each sample were measured before each test. A custom four-post frame was used for the test frame, and an extensometer was used for strain measurements. The tensile strength and Young’s modulus data were calibrated using neat PLA dog-bone specimens. The tensile testing for each sample was replicated at least twice.

Results And Discussion

Fiber Size, Fiber Shape, and Loose Bulk Density

The data on fiber size indicates that the loblolly pine fibers are larger than those of corn stover, as shown by their lower fines contents (fig. 2a) and higher Rosin-Rammler size distribution location parameters (fig. 2b). Additionally, surface-treated fibers exhibited smaller fiber size compared to the untreated fibers. It is crucial to highlight that the smaller fiber size observed in the surface-treated fibers, as compared to the untreated fibers, results from the separation of agglomerates into individual fibers rather than the fragmentation of individual fibers. Illustrations of the individual fibers and fiber agglomerates are provided in the Appendix (fig. A1). We conducted a comparison analysis of the particle size distributions of loblolly pine fibers and corn stover fibers. The findings indicated that, in general, the particle size distribution of loblolly pine fibers was narrower than that of corn stover fibers (fig. 2c). However, the corn stover fibers treated with PBG/DICY = 0.25 exhibited the narrowest particle size distribution among all the fibers considered, deviating from the general trend.

The mean fiber sphericity values ranged between 0.68 and 0.76, with fairly minimal difference between the two fiber types (fig. 2d). However, surface treatment effects had a greater impact on the fiber sphericity than the differences between the fiber types. The sphericity values for raw loblolly pine and corn stover fibers were 0.68 and 0.69, respectively. After surface treatment, the sphericity values of the fibers increased, indicating a more spherical particle shape. The sphericity of surface-treated loblolly pine fibers ranged from 0.73 to 0.74, while surface-treated corn stover fibers had a sphericity of approximately 0.76. The roundness and aspect ratio values also showed similar trends, as detailed in the Appendix (table A1).

Figure 2e shows that loblolly pine fibers exhibited generally higher loose bulk density than the corn stover fibers. For instance, the loose bulk density of the untreated loblolly pine fiber was 253.6 kg/m3, whereas the loose bulk density of the untreated corn stover fiber was 202.6 kg/m3. This bulk density data is comparable to previously reported values of 259–296 kg/m3 for loblolly pine (Oyedeji and Fasina, 2017; Oyedeji et al., 2016) and 158–207 kg/m3 for corn stover (Mani et al., 2004; Tumuluru and Heikkila, 2019). What is most striking about the loose bulk density data is that the loose bulk density of the surface-treated fibers was significantly lower than their untreated counterpart. Additionally, the loose bulk density of the surface-treated fibers, in general, increased as the PBG/DICY ratio increased. These findings demonstrate that the surface treatment process pulverizes (or deagglomerates) the fiber bulk structure in addition to surface coating. The notion of fiber clump deagglomeration is further validated by the fact that (1) the surface-treated fibers were found to have smaller particle sizes compared to their untreated counterparts (fig. 2b), (2) the percentage of fines in the surface-treated fibers was higher than in their untreated counterparts (fig. 2a), and (3) the mean sphericity of the surface-treated fibers was higher than in their untreated counterparts (fig. 2d). These findings suggest that the treatment process resulted in a change in fiber characteristics that should be considered in further analysis or applications.

Figure 2. Bar plot showing the influence of surface treatment on (a) fines content, (b) mean fiber size, (c) fiber size distribution spread, (d) mean fiber sphericity, and (e) loose bulk density for distinct fiber types (corn stover and loblolly pine). The abbreviation "R-R" indicates the Rosin-Rammler size distribution.

Compressibility, Dynamic Flow, Shear Flow, and Friction Properties

The compressibility, dynamic flow, shear flow, and friction properties of biofiber are important bulk flow characteristics. These properties significantly impact the handling, operational safety, and performance of various unit operations and the quality of their product (Cheng et al., 2021; Oyedeji and Fasina, 2017). Poor flow behavior can negatively impact system efficiency, resulting in higher operational costs and handling challenges (Gong et al., 2023; Hamed et al., 2023). Moreover, it can jeopardize product quality by causing irregular material deposition and performance issues. Baserinia et al. (2022) demonstrated that the flow characteristics of polyamide powder play a vital role in the mechanical behavior of their additive-manufactured product. The CI, FRI, and SI characterize the sensitivity of biofibers to changes in compressive pressure, flow rate, and repeated testing, respectively. Values of CI, FRI, and SI closer to one suggest better bulk flow behavior. The SE value measures the energy required to induce flow, whereas AIF and WFA measure the ability of the biofibers to resist shear force. Lower values of SE, AIF, and WFA indicate better bulk flow behavior.

We found that the compressibility index of corn stover fibers ranged from 1.41 to 1.44, and loblolly pine fibers ranged from 1.32 to 1.39 (fig. 3a). The higher compressibility index for the corn stover fibers relative to the loblolly pine ones is attributable to the fact that corn stover fibers exhibited significantly lower loose bulk density than loblolly pine fibers (Barretto et al., 2022; Goncalves et al., 2015). This means that the corn stover fibers possess higher inter-fiber porosity that can be closed during compression, producing a higher compressibility index. Furthermore, the compressibility curve (fig. 3b) showed that the surface-treated fibers had distinct compressibility profiles compared to their untreated counterparts, as evident in the slope of the curve. The slopes of the compressibility curves for the untreated fibers were higher than those of the surface-treated fibers, suggesting that the untreated fibers were more compressible than the surface-treated fibers. This evidence is corroborated by the higher compressibility index observed for the untreated fibers. The magnitude of the effect of the surface treatment on the compressibility index was more pronounced in the loblolly pine fibers than in the corn stover fibers.

The observation that surface-treated fibers have a lower compressibility index and loose bulk density compared to untreated fibers appears contradictory. This is because we expect a negative correlation between loose bulk density and compressibility index (Barretto et al., 2022; Goncalves et al., 2015). We posit that the observed phenomenon can be attributed to the surface treatment applied to the fibers, which enhances their hardness and, subsequently, their compressive resistance compared to the untreated fibers.

Figure 3. (a) Bar plot illustrating the effect of surface treatment on the compressibility index for two different fiber types: corn stover and loblolly pine. (b) Compressibility curves for untreated and surface-treated corn stover and loblolly pine fibers. In (b), the legend uses color to represent surface treatment and shape to indicate the biofiber type.

Table 3 lists the dynamic flow, shear, and friction properties of both untreated and surface-treated fibers. The dynamic flow properties of the fibers generally improved when surface treatment was applied. The FRI for the surface-treated fibers was lower than that of the untreated fibers, except for the corn stover fibers treated with PBG/DICY = 0.5, which remained unchanged. Similar trends were observed in the SE, suggesting lower energy is required to induce flow of the surface-treated compared to their untreated counterparts. However, the SI values for both untreated and surface-treated fibers were largely unchanged, ranging between 1.0 and 1.1.

The results show that the AIF values decreased for the surface-treated fibers compared to their untreated counterparts (table 3). This indicates that surface treatment enhances the flowability of the bulk material, which is consistent with the findings obtained from dynamic flow properties. The WFA values showed contrasting results, where the WFA values for surface-treated corn stover fibers were lower than the untreated corn stover fibers, while the WFA values for surface-treated loblolly pine fibers were higher than the untreated loblolly pine fibers.

Fiber Surface Roughness

The analysis of the surface roughness measurements showed large standard deviations in Sa and Sz in both corn stover and loblolly pine biofibers for all surface treatments, which suggests a significant variation from biofiber to biofiber (fig. 4). A one-way ANOVA test (a=0.05) was performed to determine whether the surface roughness data is statistically significant. The Sa and Sz in corn stover seem to decrease because of the surface treatment, as illustrated in figure 4. However, the results from the ANOVA test showed that the values are not statistically significant, p=0.140 and p=0.605, respectively. On the other hand, a statistically significant difference was found in loblolly pine fibers for both Sa and Sz, p=0.022 and p=0.019, respectively. Untreated loblolly pine fibers have, on average, lower Sa and Sz. The data in table 3 indicate that applying surface treatment improves the flowability of the fibers. One would expect that the improvement in the flowability is correlated with decreasing the surface roughness. However, in the case of loblolly pine fibers, the highest SE and AIF were achieved with the raw untreated fibers, which have the lowest Sa and Sz. While this correlation might be counterintuitive, it is important to note that applying surface treatment modifies the surface composition of the fibers, which can also affect the flowability and friction properties, which could explain why smoother raw fibers have lower flowability than rougher treated fibers.

More measurements are needed to get a statistical variance in Sa and Sz. Unfortunately, the surface roughness measurements and analysis are not high-throughput, and characterizing a larger number of fibers than conducted in this study is very time-consuming. Another possible source of measurement error is due to local variations in the surface topography of individual fibers. Optical images and corresponding surface topography maps in figure 5 show that selecting a slightly larger or smaller region of interest could affect the surface roughness results.

Table 3. Effects of surface treatment on some dynamic flow, shear flow, and wall friction properties (mean ± standard deviation) of distinct fiber types.[a]
FiberTreatmentFRISISE
(J/kg)
AIF
(°)
WFA
(°)
Corn stoverRaw1.3 ± 0.01.0 ± 0.14.7 ± 0.142.3 ± 1.915.8 ± 2.9
Corn stoverPBG/DICY = 0.251.0 ± 0.11.0 ± 0.04.3 ± 0.341.0 ± 1.814.0 ± 0.2
Corn stoverPBG/DICY = 0.51.3 ± 0.31.0 ± 0.04.2 ± 0.141.3 ± 1.015.4 ± 2.8
Corn stoverPBG/DICY = 21.1 ± 0.11.0 ± 0.14.2 ± 0.141.5 ± 1.914.0 ± 0.8
Loblolly pineRaw1.1 ± 0.11.1 ± 0.14.8 ± 0.343.9 ± 2.513.2 ± 5.7
Loblolly pinePBG/DICY = 0.251.0 ± 0.11.1 ± 0.14.1 ± 0.141.5 ± 1.214.8 ± 1.8
Loblolly pinePBG/DICY = 0.51.0 ± 0.01.0 ± 0.13.9 ± 0.040.5 ± 1.215.9 ± 2.3
Loblolly pinePBG/DICY = 21.0 ± 0.11.0 ± 0.04.1 ± 0.141.4 ± 0.714.3 ± 0.4

    [a] FRI = flow rate index, SI = stability index, SE = specific energy, AIF = angle of internal friction, and WFA = wall friction angle.

Figure 4. Bar plot showing the influence of surface treatment on (a) Sa mean surface roughness and (b) Sz maximum surface roughness for distinct fiber types (corn stover and loblolly pine).

Biocomposite Tensile Properties

The tensile strength and Young's modulus of the biocomposites made from untreated loblolly pine and corn stover were determined to be 47 MPa and 4.7 GPa, and 32 MPa, and 4.3 GPa, respectively. These values are consistent with our prior findings (Zhao et al., 2020, 2022, 2019), reinforcing the reliability of our methodology. The tensile strength of loblolly pine biocomposites consistently exceeded that of corn stover biocomposites after comparable surface treatments of the fibers (fig. 6a), demonstrating the relative superiority of loblolly pine fibers. Additionally, Young's modulus of the loblolly pine biocomposites was notably higher or comparable to that of corn stover biocomposites from fibers subjected to similar surface treatments (fig. 6b). Notably, loblolly pine biocomposites from fibers treated with PBG/DICY = 0.25 exhibited the most superior tensile properties (both in tensile strength and Young's modulus) compared to other biocomposites considered in this study.

Surface-treated fibers resulted in biocomposites with significantly higher tensile strength than untreated fibers, demonstrating the efficacy of surface treatment. The PBG/DICY = 0.25 surface treatment produced the highest tensile strength for both corn stover biocomposite (50 MPa) and loblolly pine biocomposite (58 MPa). However, the impact of surface treatment on Young’s modulus of the biocomposites was more complex in comparison to its effect on the tensile strength of the biocomposites. Surface treatment of fibers did not produce consistent improvement in the Young's modulus of their biocomposite. Notably, the PBG/DICY = 0.25 surface treatment resulted in a significant increase in Young's modulus of the biocomposite for both loblolly pine and corn stover. However, using PBG/DICY = 2 surface treatment did not improve Young's modulus for either fiber.

In previous research (Zhao et al., 2019), we reported the tensile strength and Young’s modulus of the neat PLA used in this research as 54 MPa and 3.2 GPa, respectively. The incorporation of biofiber into the PLA matrix markedly altered its mechanical properties, resulting in a decrease in tensile strength and an increase in Young’s modulus (stiffness). This is consistent with other studies (Saleh et al., 2024; Zhao et al., 2019). The reduction in tensile strength is likely due to failure at the interphase between the biofiber and PLA polymer. However, the application of an epoxy coating improved interfacial adhesion, as evidenced by the enhanced tensile strength of surface-treated biofibers compared to their untreated counterparts.

Conclusions

We examined the physical properties, flow behavior, and surface roughness of loblolly pine and corn stover fibers before and after surface treatment. A surface treatment was created using a two-component epoxy system formed by reacting PBG with DICY. Three different PBG/DICY molar ratios (0.25, 0.5, and 2) were employed. We then used these fibers to produce a PLA-based biocomposite and evaluated the tensile strength and Young's modulus of each biocomposite. The surface-treated fibers exhibited lower fiber agglomeration and particle size, higher sphericity, and lower loose bulk density compared with the untreated counterpart. We attribute these observations to the deagglomeration of fiber clumps during the surface treatment. We also hypothesize that this, along with the coating of the fiber surface, would promote better dispersion of the fibers inside the biocomposite matrix. This, in turn, would result in improved stress distribution and mechanical performance. Additionally, the data on dynamic flow shows that surface treatment improved the flow of both loblolly pine and corn stover fiber. Finally, we observed significant improvement (9%–56%) in the tensile strength of the biocomposite after treating the fiber surface, with Young's modulus with either no improvement or a corresponding improvement (up to 14%). This research has provided insights into how a surface treatment enhances the properties of biofiber materials and their biocomposites, which could have significant implications for developing high-performance fiber materials for sustainable applications in various industries.

Figure 5. Optical images and corresponding surface topography maps of selected biofibers used for surface roughness analysis. (a) corn stover, (b) loblolly pine.
Figure 6. Bar plot showing the influence of surface treatment on (a) tensile strength and (b) Young’s modulus for distinct fiber types (corn stover and loblolly pine).

A notable constraint identified in this study is the low throughput of the surface roughness measurement and analysis process, which makes it challenging to characterize a larger sample size and yields large variance in the generated surface roughness data. Additionally, the analyses and findings of this research reveal a few promising avenues for further fundamental investigation and industrial applications. These areas include exploring the effect of surface treatment on the performance of biocomposite during service, microscale characterization of surface-treated biofibers, and process modeling (including technoeconomic and life cycle analysis) to understand the economic and environmental impact.

Acknowledgments

The authors gratefully acknowledge support from the U.S. Department of Energy's Bioenergy Technology Office (DOE-BETO). This work was partly supported by the U.S. Department of Energy, Office of Science, and Office of Workforce Development for Teachers and Scientists (WDTS) under the Science Undergraduate Laboratory Internships (SULI) program. This manuscript was authored in part by UT-Battelle LLC under contract DE-AC05-00OR22725 with DOE. The US government retains, and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Nomenclature

A = Average biofiber area of a sequence of 3D images (m2)

P = Average biofiber perimeter of a sequence of 3D images (m)

Da = Area equivalent diameter (m)

Dp = Equivalent perimeter diameter (m)

FL = Longest maximum Feret diameter (m)

FW = Longest minimum Feret diameter (m)

FT = Shortest minimum Feret diameter (m)

Ar1 = Elongation factor (-)

Ar2 = Flatness factor (-)

Rd = Roundness (-)

Sph = Sphericity (-)

CI = Compressibility index (-)

SI = Stability index (-)

SE = Specific energy (J/kg)

FRI = Flow rate index (-)

Appendix

Table A1. Effects of surface treatment on fiber width, length, thickness, aspect ratios, and roundness (mean ± standard deviation) of distinct fiber types.[a]
FiberTreatmentFWi_dFLe_dFTh_dW/L_dT/W_dT/L_dRou_d
Corn stoverRaw0.66 ± 0.041.35 ± 0.000.19 ± 0.050.56 ± 0.020.56 ± 0.000.24 ± 0.000.19 ± 0.00
Corn stoverPBG/DICY = 0.250.56 ± 0.041.24 ± 0.010.15 ± 0.030.53 ± 0.000.43 ± 0.000.18 ± 0.000.16 ± 0.00
Corn stoverPBG/DICY = 0.50.45 ± 0.011.02 ± 0.000.15 ± 0.020.53 ± 0.000.74 ± 0.000.28 ± 0.000.22 ± 0.00
Corn stoverPBG/DICY = 20.53 ± 0.131.17 ± 0.020.15 ± 0.120.53 ± 0.020.55 ± 0.000.23 ± 0.000.19 ± 0.00
Loblolly pineRaw1.00 ± 0.021.85 ± 0.020.42 ± 0.030.59 ± 0.010.53 ± 0.000.28 ± 0.000.22 ± 0.00
Loblolly pinePBG/DICY = 0.250.79 ± 0.011.59 ± 0.020.34 ± 0.030.55 ± 0.010.57 ± 0.000.27 ± 0.000.24 ± 0.00
Loblolly pinePBG/DICY = 0.50.78 ± 0.031.56 ± 0.010.32 ± 0.030.55 ± 0.010.53 ± 0.000.25 ± 0.000.23 ± 0.00
Loblolly pinePBG/DICY = 20.78 ± 0.091.56 ± 0.070.35 ± 0.030.55 ± 0.010.59 ± 0.000.28 ± 0.000.25 ± 0.00

    [a] FWi_d, FLe_d, FTh_d, W/L_d, T/W_d, T/L_d, and Rou_d are the average fiber width (mm), fiber length (mm), fiber thickness (mm), fiber width to length aspect ratio, fiber thickness to width aspect ratio, fiber thickness to length aspect ratio, and fiber roundness.

Figure A1. Illustration of the (a) individual fibers and (b) fiber agglomerates observed by the particle image analyzer (images are not to scale).

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