Physical and Mechanical Inherent Characteristic Investigations of Various Jordanian Natural Fiber Species to Reveal Their Potential for Green Biomaterials

Hayajneh, Mohammed T.; AL‐Oqla, Faris M.; Aldhirat, Amal

doi:10.1080/15440478.2021.1944432

Cited by 32 publications

(7 citation statements)

References 26 publications

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“…They were collected and utilized in this work as they have demonstrated proper characteristics for biomaterials. [18] They were washed with distilled water and air-dried for 24 h before being utilized in the composites. Fibers were then chopped to lengths of (8-12) mm and mixed with polypropylene via a hot mixture machine with various fiber content for each fiber type as shown in Figure 1.…”

Section: Composite Processingmentioning

confidence: 99%

Tribological and mechanical fracture performance of Mediterranean lignocellulosic fiber reinforced polypropylene composites

2021

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Natural fiber-reinforced polymeric composites are considered one of the newest materials in the industry. Ecological concerns have led to a growing need of using ecofriendly materials. This work aimed to study the dynamic and quasi-static performance as well as tribological characteristics of Mediterranean lignocellulosic fiber-reinforced polypropylene composites. Various types of Jordanian lignocellulosic fibers were utilized in the study, namely, hay, lemon, palm, and reed. Composites with various reinforcement structures were designed, prepared, and utilized for the investigations. Wear performance and coefficient of friction as well as various mechanical performance characteristics including tensile strength, tensile modulus, elongation to break, and impact strength were performed. Results have demonstrated that composites have led to different significant characteristics. The hay/polypropylene composites were revealed to have good mechanical performance enhancements. Their maximum value of the tensile modulus was 1557.2 MPa in the case of 30 wt% fiber content. It was also demonstrated that their maximum value of toughness was about 1031 kJ/m 3 in the case of 20 wt% fiber content. However, the increase of fiber loading more than 20 wt% was found to make negative effects on the toughness characteristics. Moreover, it was found that most of the considered Jordanian lignocellulosic fibers were capable of enhancing most of the mechanical performance characteristics of the composites, particularly, the stiffness property. The coefficient of friction was also found variable with fiber loading as well as fiber type. The maximum coefficient of friction value was for the composites with 30 wt% hay, while the lowest was found for composites that contained palm and reed at 10 wt%. The work had demonstrated that the features of Jordanian natural fibers were potential and competitive regarding their elasticity, toughness, interfacial adhesive potency, accessibility, and polypropylene compatibility due to their desired intrinsic mechanical characteristics. This would contribute to the finding of low-cost environmentally friendly materials for various bio-product applications with reliable

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Section: Composite Processingmentioning

confidence: 99%

Tribological and mechanical fracture performance of Mediterranean lignocellulosic fiber reinforced polypropylene composites

2021

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“…As researchers have become more mindful of the environment, more attention has been paid to the suppliers of cellulosic fibers-such as kenaf, cotton, jute, and hemp-since these fibers are used in an extensive range of products and composites [10][11][12][13]. In particular, the use of these fibers as reinforcements in polymer composites has garnered this interest [14][15][16][17][18][19]. Table 1 presents the results of numerous experimental investigations into the mechanical characteristics of the natural fibers.…”

Section: Introductionmentioning

confidence: 99%

An effective hybrid particle swarm—artificial neural network optimization for predicting green bio-fiber mechanical characteristics and optimizing biomaterial performance

Nawafleh,

Al-Oqla

2024

Funct. Compos. Struct.

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Natural fiber-reinforced composites are currently utilized in several applications due to worldwide environmental and cost concerns. However, these composites have production challenges such as poor reinforcement-matrix adhesion, that sophisticates the prediction of their mechanical properties. This study presents a novel, robust hybrid particle swarm – artificial neural network optimization (PSO-ANN) methodology to assess and create accurate predictions of the green bio-fibers to optimize and improve the mechanical features of biomaterials for green bio-products instead of performing tedious experimental works. As the mechanical qualities of green bio-fibers might differ from one fiber to another due to several interacted parameters, high complexity in predicting the bio-fiber capabilities exists. Therefore, this work utilizes suitable methods with a non-linear activation function to predict the mechanical characteristics of natural fibers that allow the researchers to improve the choices of natural fibers for biomaterials on the basis of cellulose content, the microfibrillar angle, and the diameter of natural fibers, decreasing the duration of the process required to characterize materials experimentally. The reliability of the introduced PSO-ANN model was verified by the investigations of the fiber’s tensile stress and Young’s modulus. Results showed that the presented model is capable of consistently and accurately monitoring the mechanical performance to a large degree, in comparison with experimental results. This in fact would facilitate and simplify the process of selecting the best natural fiber composites, which speeds up the experimental characterization phase and improves energy efficiency in the process of converting energy into monetary income, which would have ramifications for both economies and ecosystems. The anticipated method would also boost scientific evaluation of green fibers, confirming their role as a replacement material for green product fulfillment in future eco-friendly manufacturing.

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“…Natural fiber composites are potential bio-based materials that contain lignocellulosic fibers as reinforcement. Natural fibers are complex and unpredictable, which make the properties of bio-composites are very sensitive to the manufacturing processes [5][6][7]. Natural fiber extraction is also important as it can affect its properties [8,9].…”

Section: Introductionmentioning

confidence: 99%

Investigating and Predicting the Effects of Fiber Chemical Composition and Treatment on the Mechanical Properties of Natural Fiber Composites by Response Surface Method

Gharaibeh¹,

AL‐Oqla²

2023

MME

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This paper aims to integrate the response surface methodologies to investigate the effect of the cellulose and hemicellulose contents on the mechanical properties of the polypropylene-based composites with green fiber reinforcement conditions. In this study, the tested data are collected from various literature resources demonstrating the green fiber type, the chemical treatment condition, and the resultant mechanical properties, i.e., the tensile modulus and tensile strength. Accordingly, the response surface analysis is utilized to obtain a high-accuracy first order regression model to formulate the influence of the cellulose, hemicellulose, and the treatment condition on the tensile characteristics of the green composite. The results showed that the biocomposites samples with higher cellulose and lower hemicellulose percentages have significantly better tensile modulus properties. However, such samples would have lower tensile strength qualities. Additionally, the presence of chemical treatment can significantly improve the tensile properties of the polypropylene-based composites.

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Physical and Mechanical Inherent Characteristic Investigations of Various Jordanian Natural Fiber Species to Reveal Their Potential for Green Biomaterials

Cited by 32 publications

References 26 publications

Tribological and mechanical fracture performance of Mediterranean lignocellulosic fiber reinforced polypropylene composites

Tribological and mechanical fracture performance of Mediterranean lignocellulosic fiber reinforced polypropylene composites

An effective hybrid particle swarm—artificial neural network optimization for predicting green bio-fiber mechanical characteristics and optimizing biomaterial performance

Investigating and Predicting the Effects of Fiber Chemical Composition and Treatment on the Mechanical Properties of Natural Fiber Composites by Response Surface Method

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