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Effect of e-waste nanofillers on the mechanical, thermal, and wear properties of epoxy-blend sisal woven fiber-reinforced composites

  • Jebasingh Immanuel Durai Raj EMAIL logo , Ramamoorthy Iyer Balasubramaniyan Durairaj , Amaladas John Rajan and Praveen Barmavatu
Published/Copyright: December 31, 2023
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Abstract

Lignocellulosic biomass extracted from plants that contain rich amounts of cellulose, hemicellulose, and lignin content can replace synthetic fibers in many engineering applications and is biodegradable. However, e-waste is rapidly evolving into one of the most serious environmental issues in the world owing to the presence of several toxic compounds that can contaminate the environment and pose a threat to human health. Printed circuit boards (PCBs) are one of the major components available in e-waste. In this research work, waste PCB (WPCB) powder is mixed in suitable proportions of 5%, 10%, 15%, and 20% with a lignocellulosic sisal woven fabric fiber mat, and blended with epoxy resin using the vacuum-assisted hand lay-up method. To determine the effect of particle size on the fabricated composites, mechanical, thermal, water absorption, surface roughness, and wear tests were conducted. It was found that the composition that contains 15% nanofiller composites gave better results in mechanical testing than the composition that contains 10% microfiller composites. Pin-on disc wear test and differential scanning calorimetric thermal test results show that 10% microfiller composites show better outcome results than 15% nanofiller composites. Testing values indicate that lignocellulosic sisal fiber composites with WPCB nano- and microfillers can be substituted for many engineering applications instead of being disposed of in landfills.

1 Introduction

Discarded electronics are the fastest-growing waste source because of increased industrialization and product obsolescence. The use of e-waste, or electronic garbage, has resulted in major environmental problems due to the release of toxic substances during disposal processes [1]. For instance, common hazardous compounds that exist in television and computer screens include lead, mercury, and cadmium, whereas common hazardous materials present in circuit boards include nickel, beryllium, and zinc. E-waste materials, use, and disposal have become major problems around the world. About 2 million metric tonnes of electronic garbage are produced each year, with an additional, as-yet-undisclosed quantity imported from elsewhere [2]. Management of e-waste requires the creation of environmentally friendly tools for efficient collection, material recovery and recycling, and final disposal. Landfilling, acid baths, incineration, recycling, and reusing are the different e-waste disposal techniques presently adopted. It creates huge environmental hazards during the dismantling processes to reuse and recycling processes. In the overall composition of e-waste, waste printed circuit boards (WPCBs) amount to 2% (as shown in Figure 1a). Metals such as copper, aluminum, lead, silver, tin, iron, cadmium, and nickel are present, along with silicon dioxide and epoxy resins (Figure 1b). In addition to the electronic components, the circuit board also contains insulators, capacitors, resistors, etc. Various metal oxides (MgO, Al2O3, and CaO) are used as fillers to fabricate printed circuit boards (PCBs). Metal accounts for 40%, ceramics for 30%, and plastic for 30% of the components on a typical PCB [3].

Figure 1 
               (a) Overall composition of e-waste [3] and (b) composition of WPCB [14].
Figure 1

(a) Overall composition of e-waste [3] and (b) composition of WPCB [14].

PCBs that have been used and then thrown away generate a risk to both human and environmental health if they are not disposed of properly [4]. PCB consists of a group of toxic substances that can cause genetic disorders in those who are exposed to them because they promote the creation of micronuclei and chromosomal aberrations when released into the environment via air, soil, water, or landfills [5]. Before disposal of PCBs, the metals present in them can be recovered by different processes, such as pyrometallurgical processing like (i) incineration and pyrolysis, (ii) hydrometallurgical processes, and (iii) chemical leaching and bioleaching processes [6]. All the above-mentioned methods are costlier and time-consuming procedures; moreover, only a few informal sectors are doing this to recover precious metals from PCBs. One of the most pressing problems that humanity and the planet face today is global warming. Therefore, researchers and engineers have moved their focus towards synthetic components to biodegradable and environmentally friendly materials in an effort to reduce this issue. Plant fibers, also called lignocellulosic fibers, are the fibers that come from plants. As a natural plant fiber structure, this is made up of lignin and cellulose. A construction like this could have a tensile strength close to that of glass fibers. As natural fibers are biodegradable, readily available, less expensive, and nontoxic to the environment, researchers have begun designing polymer composites utilizing natural fibers as reinforcement to replace synthetic fiber-based composites [7]. In order to reduce fuel consumption, the automotive industry must find alternatives to nonrenewable resources like petroleum-based polymers and replace them with natural materials that have minimal environmental impact [8]. Ropes, carpets, rugs, textiles, and other handmade goods are only a few of the many uses for sisal fibers. Reinforcement of polymer composites with sisal fibers is another application. Parts for automobiles have been made with the help of sisal fiber-reinforced polymer composites [9]. Sisal fiber, harvested using the leaves of the Agave sisalana plant, is among the toughest natural fibers available. The plantations can be found all across India, Brazil, East Africa, and Indonesia. It is one of the most widely grown hard fibers; therefore, it is readily available in addition to having excellent durability and strength. The main components of sisal fibers are cellulose (65%), lignin (9.9%), hemicellulose (12%), and wax (2.5%) [10].

The mechanical properties of sisal fibers show comparatively higher strength than most of the natural fibers that can be used for engineering applications, with a density of 1.2 g·cm−3, a tensile strength range of 460–855 MPa, a Young’s modulus of 15.5 GPa, and an elongation at break of 8% [11]. Irregularly shaped threads may be present in composites made from nonwoven fibers. At lower stresses, these could get debonded and begin to separate from one another, leading to irregular contraction. It has been found that the mechanical characteristics are also affected by the varying diameters of the fibers [12]. For a variety of applications involving fiber-reinforced polymer composites, woven polymer composites exhibit superior mechanical strengths compared to unidirectional fiber composites. These strengths include increased stiffness, strength, dimensional stability, lighter weight, no delamination, low crack danger, quicker production, and low cost are some of the main advantages. Sisal fibers along with epoxy resin, give good bonding strength.

Also, the shrinkage of epoxy resins is significantly lower than that of unsaturated resins made from polyester. Epoxies are commonly used to make exceptionally good composites containing a wide range of desirable properties, including outstanding mechanical capabilities, resistance to harmful chemicals as well as conditions of use, improved electrical features, enhanced performance at higher temperatures, and good substrate adhesion [13].

Many studies have proven that it is difficult to obtain high-quality products with a minimal amount of structural imperfections and a significant amount of fillers when using the hand lay-up technique, which is among the most widely employed techniques of laminate forming. In order to maximize fiber supersaturation and reduce the likelihood of cavities and pores, numerous low-cost manufacturing techniques are widely used in actual industrial practice. Vacuum bagging (VB) is one technology that could be used to strengthen thin-walled items with continuous fibers, vast surfaces, and complex geometries [15] (Figure 2b). Adding reinforcing fillers to plastics is a tried and true means of improving the material’s mechanical, thermal, and electrical qualities. The mechanical behavior of the resultant composites is of particular interest, as it is one of the physical properties that may be altered by the addition of fillers to plastics. It is well known that the tensile strength, impact strength, and elasticity modulus of polymers may be greatly increased with the right formulation and compounding, enabling the extension of plastics’ application into previously unimagined technical sectors [16,17,18,19,20,21].

Figure 2 
               (a) Bi-directional sisal fiber mat and (b) VB hand lay-up technique [15].
Figure 2

(a) Bi-directional sisal fiber mat and (b) VB hand lay-up technique [15].

The use of filler can have a major impact on the friction coefficient, molding shrinkage, and weatherability, among many other physical attributes [21]. Nano- and microreinforcement composites are taking center stage in the modern materials industry as a result of their superior mechanical capabilities and lightweight construction compared to the primary group of materials. It has been shown that filler compatibility in the matrix can be increased with the use of suitable surface-modified inorganic fillers, leading to enhanced stability and void-free composites. It must have a strong adhesion with the fillers and the polymer matrix, an increased aspect ratio of the filler, even spreading of the filler, and an effective dispersion in order to develop multifunctional particle-reinforced polymeric nanocomposites with remarkable mechanical properties. This can be accomplished by providing the fillers with a good dispersion. Even at minimal filler addition (3–6 wt%), mechanical characteristics improved more with nanoparticle filling [21]. Bearings, gears, cams, and other tribologically active elements of industrial machinery and automobiles have begun to utilize polymer fiber-reinforced composites. While the mechanical and electrical qualities of composites are preferable to those of traditional materials, the tribological characteristics of composites are viewed as a drawback [22]. However, hybridization has been shown to be an effective way to boost the mechanical properties of composites. Fiber-reinforced polymeric-based composites can also benefit from hybridization to enhance their tribological properties [23]. Hybrid composites’ wear can be affected by their material qualities, operation conditions, and the order in which the laminating layers are stacked. By adjusting factors like sliding distance and applied load, wear characteristics can be enhanced [24]. In this research work, the effects of adding micro- and nano-sized filler obtained from WPCB to the sisal fiber blended with epoxy resin on the mechanical, thermal, water absorption, and wear properties have been examined.

2 Materials and methods

2.1 Preparation of the WPCB powder

In this study, WPCB was collected from the waste material collection centers. It consists of waste PCB from all electronic devices such as desktop computers, mobiles, laptops, and televisions. Printed electronic boards are disassembled through de-soldering, as shown in Figure 3a. All the capacitors, relays, resistors, and transistor-like components on the motherboards are desoldered and removed. When disassembling, hot air is used as a disordering tool. A gas mask is required for this procedure since it could release toxic gases. These chemicals pose serious health risks. After the removal of components, approximately 20% of the overall weight of WPCB was reduced [25]. Then, it was pulverized, ground as shown in Figure 3b, and sieved to 75 μm. To prepare nanoparticles, WPCB powder in micro size is fed into a high-energy ball milling machine (Emax model) for 3 h. A nanoparticle size of less than 100 nm (as shown in Figure 3d) was obtained. The size of the particle was verified using field emission scanning electron microscopy (FESEM) (ZEISS SIGMA 300; shown in Figure 4). ImageJ software was used [26,27,28] to perform the measurements, and the results showed that the average size of the particles is around 90 nm (as shown in Figure 5b).

Figure 3 
                  (a) WPCB, (b) sieve shaker (75 μm), (c) micro WPCB powder, and (d) nano-WPCB powder (<100 nm).
Figure 3

(a) WPCB, (b) sieve shaker (75 μm), (c) micro WPCB powder, and (d) nano-WPCB powder (<100 nm).

Figure 4 
                  FESEM machine – ZEISS SIGMA 300.
Figure 4

FESEM machine – ZEISS SIGMA 300.

Figure 5 
                  (a) SEM image of WPCB microfiller powder and (b) nanosize WPCB filler measurement from the SEM image.
Figure 5

(a) SEM image of WPCB microfiller powder and (b) nanosize WPCB filler measurement from the SEM image.

2.2 SEM with EDX analysis of the composite laminate

The elemental chemistry of the material being examined can be quickly and nondestructively determined using scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDX), which can quickly identify all the metals and nonmetals in the samples [29]. SEMs are extremely useful in many fields of science and industry because the high-resolution, three-dimensional images they produce reveal topographical, morphological, and compositional details. It provides information on the topography of solid samples. It concentrates incident electrons onto a sample and the electrons that scatter off on its surface after the contact can be examined by various detectors to reveal the surface’s topography, morphology, and composition [30]. The results that are produced as a result of an EDX examination are spectra-bearing peaks, which correspond to the compounds that make up the actual composition of the substance that is being investigated (as shown in Figure 6b). The selected sample portion of composite boards, as shown in Figure 6a, gives the elemental mapping as shown in Table 1.

Figure 6 
                  Selected portion of the fabricated sisal laminate composite board: (a) SEM image and (b) SEM-EDX analysis.
Figure 6

Selected portion of the fabricated sisal laminate composite board: (a) SEM image and (b) SEM-EDX analysis.

Table 1

Elemental mapping of the selected portion of sisal composite laminates impregnated with WPCB fillers

Element C O Na Mg Si Cl K Ca Fe Cu Zn Br Ag Sn Au Pb
Weight % 65.45 21.25 0.24 0.2 4.71 0.36 0.23 1.04 1.86 1.23 0.82 1.52 0.12 0.06 0.56 0.35
Atomic % 76.82 19.18 0.15 0.11 0.85 0.14 0.08 0.36 0.47 0.81 0.23 0.27 0.12 0.01 0.25 0.15

2.3 X-ray fluorescence (XRF) analysis of WPCB powder

XRF analysis is performed to determine the heavy metals that cause environmental hazards. By analyzing the fluorescence (or secondary) X-ray that a sample emits after being excited by a primary X-ray source, the chemical elemental composition of a sample can be determined. XRF spectrometry has the potential to identify virtually all of the elements included in the periodic table. XRF analysis is quick, precise, and inexpensive [26]. The percentage of each element is obtained from the XRF report as oxides of metals, as shown in Table 2. Figure 7 shows the peak values of each element that is present in oxide form. It is evident from Table 2 and Figure 7 that hazardous heavy metal elements, such as Cr, Zn, Br, Sn, Pb, Ba, Sb, Mn, and Ni, are present in the WPCB powder.

Table 2

XRF elemental composition of the WPCB powder

Compound SiO2 CaO Al2O3 SnO2 Br CuO Fe2O3 PbO BaO
Wt (%) 32.52 16.65 9.55 9.90 8.69 8.0 3.95 3.92 1.76
Compound Cl TiO2 ZnO NiO SO3 Cr2O3 Sb2O3 MnO SrO ZrO2
Wt (%) 1.71 1.22 0.56 0.40 0.334 0.18 0.17 0.13 0.127 0.124
Figure 7 
                  XRF pattern of the WPCB powder sample.
Figure 7

XRF pattern of the WPCB powder sample.

2.4 Fabrication of composite boards

Both micro- and nano-WPCB powders are mixed with epoxy resin LY 554 along with the hardener amino hydrocarbon in a ratio of 10:1. Epoxies with high elasticity and strength are often used as the main component, both as adhesives and matrix [31]. Ultrasonic processing was used to combine nano- and micron-sized WPCB particles with the epoxy resin. Micro- and nanoparticles were dispersed in epoxy resin using ultrasonic waves produced by an ultrasonic instrument. Particle loadings 5, 10, 15, and 20% by weight [911,21,31,32,33] were applied to the woven sisal fabric with a 30 cm ×  30 cm sized woven fiber mat (the fabric’s thickness is 0.7 mm and the amount of weight per area of fabric is 310 g·m−2).

VB is a technique that employs air pressure to clamp adhesive or resin-coated lamination components until the adhesive cures. Release fabric, a smooth woven cloth that does not adhere to epoxy, separates the breather and laminate. Perforated film (which keeps the resin within laminates when prolonged vacuum pressure is used with resin systems that cure slowly or thin laminates) and breather material (which provides a little air space among the bag and laminates to pull air from al regions of the envelope to a port or manifold) are arranged one over the other before beginning of VB process began with VB. Mastic sealant is used to seal the bag and mold perimeters airtight. The epoxy resin paste was applied between each layer of the fiber, and the layers were rubbed together with a heavy roller. To achieve a thickness of 4–5 mm appropriate for ASTM testing, a total of five layers of the fiber were layered on. Each layer is arranged in the same orientation. The vacuum was maintained at a pressure of 0.1 bar for 3 h using a vacuum pump, as shown in Figure 8c. A constant force of 50 N was applied for 24 h to ensure drying (Figure 8c). The board was then released from its mold. To conduct the tensile test, compressive test, Izod impact test, Shore D hardness test, flexure test, water absorption test, and wear test, the samples were cut using a water jet machine (Figure 8d), in accordance with ASTM standards. For each combination, three samples were made and evaluated to determine the mean. It was decided to make three different combinational boards based on the literature reviews [9,10,11], which show that optimum mechanical properties were obtained with the addition of 5–15% of fillers. Laminate boards, each measuring 30 cm × 30 cm, and adding a constant 5, 10, 15, and 20% of micro and nanofillers to the weight of bi-directional woven sisal fiber (Figure 2a) were fabricated. The fabricated Sisal composite boards are named as S1 (sisal – epoxy laminate without fillers), SM2, SM3, SM4, and SM5 (composites of sisal fibers with microfillers), as shown in Figure 8a, and SN2, SN3, SN4, and SN5 (composites of sisal fibers with nanofillers), as shown in Figure 8b (Table 3).

Figure 8 
                  (a) Micro-PCB powder sisal composite, (b) VB, (c) vacuum machine, (d) nano-PCB powder sisal composite, and (e) water jet machining process.
Figure 8

(a) Micro-PCB powder sisal composite, (b) VB, (c) vacuum machine, (d) nano-PCB powder sisal composite, and (e) water jet machining process.

Table 3

Fiber layer weight and filler %

S. no. Laminates Amount of filler used (%) Woven sisal fabric weight per layer (g) Amount of WPCB filler (g) Density (g·cm−3)
1 S1 0 31 + 33 + 32 + 32 + 31 = 159 0 1.143
2 SM2 5 33 + 32 + 31 + 32 + 32 = 160 8 1.154
3 SM3 10 32 + 32 + 33 + 31 + 33 = 161 16.1 1.162
4 SM4 15 33 + 31 + 32 + 33 + 32 = 161 24.15 1.187
5 SM5 20 33 + 32 + 32 + 31 + 33 = 161 32.2 1.206
6 SN2 5 32 + 31 + 31 + 33 + 32 = 159 8.1 1.144
7 SN3 10 32 + 33 + 32 + 33 + 32 = 162 16.2 1.167
8 SN4 15 33 + 31 + 31 + 32 + 33 = 160 24 1.169
9 SN5 20 31 + 33 + 32 + 31 + 32 = 159 31.8 1.175

2.5 Experimental details

2.5.1 Tensile test

The tensile strength of the composites was determined using a Universal Testing Instrument (UTM, INSTRON 3382) (Figure 9a). The procedure followed was according to the guidelines laid out by ASTM D3039 [34]. A gauge length of 50 mm and a crosshead speed of 1.27 mm·min−1 were set on the UTM machine. The average results for each stacking sequence were determined by testing three similar (Figure 9b) specimens with dimensions of 120 mm × 20 mm × 3 mm. Figure 9c shows the specimen samples once the tensile test was conducted.

Figure: 9 
                     (a) Tensile testing machine, (b and c) microfiller test specimens before and after the tensile test, and (d and e) nanofiller test specimens before and after the tensile test.
Figure: 9

(a) Tensile testing machine, (b and c) microfiller test specimens before and after the tensile test, and (d and e) nanofiller test specimens before and after the tensile test.

2.5.2 Compression test

Three samples of each composition of micro- and nanofiller composites were compressed according to the ASTM standard (ASTM D3410) [35]. Using a compression testing machine (Dak System Inc. U.T.M.) and a 100 kN load cell, the tests were run at a testing speed of 2 mm·min−1 (Figure 10a). Each specimens were cut into 100 mm length, 25 mm width, and 4 mm thickness (Figure 10b), and then clamped in hydraulic cylinders having the long axis aligned to the direction of the application of force, with a 5 kN gripping load applied to the first 40 mm of each end. Before the failure (or buckling) occurred, the ultimate strength and strain were recorded.

Figure 10 
                     (a) Compression testing machine, (b) and (c), microfiller test specimens before and after the compression test, and (d) and (e) nanofiller test specimens before and after the compression test.
Figure 10

(a) Compression testing machine, (b) and (c), microfiller test specimens before and after the compression test, and (d) and (e) nanofiller test specimens before and after the compression test.

2.5.3 Flexure test

The resistance to bending or stiffness of a material was measured by conducting flexural testing on the FRP laminate material. The ASTM D-790 [36] standard dictated the exact sizes of the specimens that were cut. The flexural strength of the specimens was measured using a three-point bending test. The Instron3 UTM machine (Figure 11a) was used for the evaluation. The specimen dimensions were 125 mm in length, 12.7 mm in width, and 3.2 mm in thickness (Figure 11b).

Figure 11 
                     (a) Flexure testing machine, (b) and (c) microfiller test specimens before and after the flexure test, and (d) and (e) nanofiller test specimens before and after the flexure test.
Figure 11

(a) Flexure testing machine, (b) and (c) microfiller test specimens before and after the flexure test, and (d) and (e) nanofiller test specimens before and after the flexure test.

2.5.4 Impact test

To gauge the impact of the load-carrying ability of woven sisal fabric composite specimens along with the addition of micro- and nanofillers, an Izod notched impact test was carried out using an impact testing machine. The composite samples are evaluated in accordance with the requirements of ASTM D256 [37]. The specimen was broken with a single swing (Figure 12a) at room temperature when held as a vertical cantilever beam using the appropriate pendulum hammers mounted at a speed of 10 kJ. After each set of testing, the equipment was calibrated such that the impact energy (in J·m−1) could be determined with precision.

Figure: 12 
                     (a) Impact testing machine. Impact test specimens before and after the test. (b) and (c) microfiller specimens, and (d) and (e) nanofiller specimens.
Figure: 12

(a) Impact testing machine. Impact test specimens before and after the test. (b) and (c) microfiller specimens, and (d) and (e) nanofiller specimens.

2.5.5 Shore D hardness test

One of the most commonly used tools for characterizing the hardness of FRP composite materials is the Shore hardness tester. A shore durometer is a tool used to evaluate the hardness of various substances, most frequently polymers. The degree of hardness is quantified along a scale from 0 (very soft) to 100 (very hard) by measuring the extent of indentation made by a rigid ball when subjected to a spring force or dead load. The rubber with a modulus of elasticity of zero is represented by a hardness of zero on a scale from 0 to 100, and the rubber with an elasticity modulus of infinite is represented by a hardness of 100 [38]. The hardness tests were carried out in accordance with the standards outlined in ASTM D2240 [39].

2.5.6 Water absorption test

The expansion of the fiber caused by water absorption can lead to microcracks at the fiber–matrix region, which can decrease the strength and dimensional characteristics of the composites [40,41,42]. Since hydrophobic thermosetting resins are incompatible with hydrophilic natural fibers, chemical treatments are required to increase adhesion between the two [29,34]. The test for water absorption under ASTM D570 [43] requires the specimens of size 2″ in diameter by 0.25″ in thickness to be dried in the oven at a predetermined temperature and duration, after which they are transferred to a desiccator for cooling. The samples are weighed as soon as they are cooled. After that, they are submerged in water over a predetermined period of time (at 23°C for 24 h) until equilibrium is reached. The samples are dried with a lint-free cloth and then weighed after removal. The percentage of water absorption is calculated using the following equation [35]:

% W ab = [ ( W a W b ) / W b × 100 ]

where W ab is the % of water absorption, W a is the weight after absorption, and W b is the weight before absorption.

2.5.7 Surface roughness measurement

It is very difficult to machine the composite material because of its anisotropic and nonhomogeneous properties. Composite materials are far more challenging to machine than metals because of their unique machining mechanisms [44]. The typical cutting tool must repeatedly encounter the cohesive zone, such as the reinforcement of hard fiber in the soft matrix while machining fiber composites. For instance, surface damage during machining accounts for 60% of rejected composite products in the aerospace industry. Therefore, a good surface finish is also a considerable criterion in natural fiber composite (NFC) laminate fabrication. Fabrication methods will also have a greater influence on the surface finish [45]. Mitutoyo Surface Roughness Tester (Figure 13a) Surftest SJ-210 Series 178-Portable is used to measure the surface roughness. All micro-WPCB filler laminates and nano-WPCB filler laminates are tested. The roughness average (R a), the average maximum height of the profile (R z), the root mean square average of the profile heights (R q), and the maximum roughness depth (R max) readings are taken, and the average value is tabulated, as shown in Table 4.

Figure 13 
                     (a) Surface roughness tester and (b) R
                        a, R
                        z, R
                        max, and R
                        q values of sisal micro and nanofiller laminates.
Figure 13

(a) Surface roughness tester and (b) R a, R z, R max, and R q values of sisal micro and nanofiller laminates.

Table 4

Surface roughness test results

Laminates Average roughness (R a), µm Average max. height of profile (R z), µm Maximum roughness depth (R max), µm Root mean square roughness (R q), µm
S1 9.431 48.13 54.67 11.38
SM2 12.19 60.38 71.48 14.56
SM3 11.79 55.61 68.49 13.06
SM4 5.09 26.78 64.35 6.36
SM5 3.26 17.34 48.53 4.25
SN2 10.07 47.35 57.24 12.10
SN3 10.27 48.64 55.91 12.39
SN4 5.90 28.70 47.64 7.06
SN5 4.29 25.23 43.83 6.56

2.5.8 Wear test

All-natural fiber-reinforced composites are quickly becoming a viable alternative to metals and ceramics in various fields, including the automotive, aerospace, marine, sporting goods, and electronics sectors [46]. Many studies have been reported on the abrasive wear mechanism of polymers and polymer composites. Many movable and immovable parts are made of composites. In recent developments, gears are manufactured using plastics, and for a sustainable environment, gears can be made using NFCs [47]. Sisal fiber composites are utilized in brake liners, door boards, trim parts, lodge linings, seat pads, backs, etc. [48]. Using sisal fiber hybrid composites, automotive components that include rearview mirrors, screens in two-wheelers, billion seat covers, indicator covers, cover L-sides, and nameplates were manufactured [49]. Surface roughness and wear due to regular usage may vary with different parameters like load and friction. To find the wear rate and surface roughness, a pin-on-disc wear test (Figure 14a) is conducted. Micro- and nano-sisal fiber specimens of 10 mm diameter and 5 mm thickness (Figure 15a,b) are tested for all combinations. An ASTM G-99 [50] compliant pin-on-disc apparatus is used for two-body abrasive wear testing. One side of the composite specimen (diameter of 10 mm and thickness of 5 mm) is in contact with water-proof silicon carbide abrasive paper (Figure 14b) that is placed on a revolving disc, while the other side is attached to an epoxy rod pin (Figure 14c) of 30 mm length and diameter of 10 mm [32]. Specimens were positioned so that the plain fabric was perpendicular to the sliding plane, whereas the warp was perpendicular to the abrading orientation.

Figure 14 
                     (a) Wear test setup, (b) pin on disc, and (c) sample specimen.
Figure 14

(a) Wear test setup, (b) pin on disc, and (c) sample specimen.

Figure 15 
                     Wear samples: (a) microfiller composite and (b) nanofiller composite.
Figure 15

Wear samples: (a) microfiller composite and (b) nanofiller composite.

The pin-on-disc is equipped with a sticker-type sandpaper (Figure 14b) of the 800 grit variety, and its diameter is 150 mm to ensure a firm grip. The test samples were damaged by the implanted SiC particles. A piece of soft paper soaked in acetone was used to clean both the sample and the disc before the test, and then both were allowed to dry fully [51]. At first, an electronic balance was used to determine the pin assembly’s weight with an accuracy of 0.01 mg. Weight reduction is quantified by comparing the starting and ending weights [52]. Sliding distances (L) of 900, 1,800, and 2,700  m at velocities of 1, 2, and 3 m·s−1 under loads (F) of 5, 10, and 15 N were used to conduct the dry wear testing on each material. A 125 mm track radius is designed to be the pin’s rubbing surface [43]. A new 800-grit sandpaper was used to conduct each test to determine the wear rate W S (mm3/N m), weight loss Δm, (g), and coefficient of friction. The specific wear rate of the material with the calculated density (ρ), sliding distance (L), and normal load (F) is calculated using the following equation:

Specific wear rate ( W S ) = ( Δ m ) ( L × ρ × F )

To find the optimum conditions for control factors, the Taguchi optimization technique is used at a mixed-level design, and an L 18 orthogonal array (21 × 33) is used. The Taguchi optimization technique was used to analyze the various levels of experimentation with a smaller number of trials [53]. The aim of the wear test is to find the optimum parameters of load, speed, and distance that result in a minimum wear rate (W S), a lower coefficient of friction (µ), and a minimum loss in weight (W L). The “smaller the better” (as in the footnote of Table 9) characteristic is chosen to analyze the rate of wear (WR), coefficient of friction (µ), and weight reduction (WL) that occur due to various loads (L), velocities (m·s−1), and sliding distances (km). Minitab software was used to find the optimized parameter values. To normalize the results, all responses have been converted into a signal-to-noise (SN) ratio. The objective of conducting the experiment is to reduce the SWR (specific wear rate), CoF (coefficient of friction), and W L (weight loss) of hybrid composites.

2.5.9 Differential scanning calorimetric (DSC) test

The thermal endurance of hybrid epoxy-NFCs is a crucial aspect that should be taken into consideration, as the temperature at which they are processed plays an essential role in the manufacturing process of the composites [54]. This method is excellent for determining the glass transition temperature and other characteristics of the material. The DSC test can detect chemical changes in the fiber’s components as a result of heating. When the fiber is heated, chemical variations among the constituents can be measured by DSC [55]. At temperatures below their transition temperature, polymers remain hard and brittle, like glass, whereas at higher temperatures, they become more rubbery. The thermal study of the micro- and nano-sisal specimens was carried out using DSC thermal measurements, which were carried out using a Netzsch STA409C (Selb, Germany). In preparation for the DSC study, a sample weighing approximately 10 mg was measured and then vacuum-sealed. Temperatures between 20 and 200°C were used in each of the tests, which were conducted in an environment containing nitrogen. The rate of heating was kept at 10°C·min−1. The glass transition temperature was noted from the graph results as ASTM D3418 [56].

3 Results and discussion

The experimental values obtained using mechanical, thermal, and water absorption tests were analyzed. Values obtained by adding microsized WPCB fillers to test specimens are compared with those obtained by adding nanosized WPCB fillers, and the results are interpreted through graphs.

3.1 XRF and SEM-EDX analysis

SEM-EDX analysis of the WPCB powder sample indicates the presence of toxic metals like copper, lead, tin, nickel, zinc, titanium, and chromium. In XRF analysis, the result indicates the elements are present in the form of oxides. Since heavy metals are harmful to the environment, they should not be dumped into landfills. Tables 1 and 2 confirm the presence of heavy metal in the fabricated laminates as well as in the microsized e-waste filler. XRF analysis of WPCB filler shows that (Table 2) around 8.0% Cu, 9.9% Sn, 3.92% Pb, 0.40% Ni, 1.22% Ti, and 0.56% Zn are present in the filler sample as heavy metal oxides. FESEM image (Figure 16a) and mapping spectrum (Table 1) for the sisal laminates for a selected portion are shown in Figures 6b and 7.

Figure 16 
                  FESEM analysis of the sisal fiber laminate (a) with WPCB filler, (b) micro-WPCB filler view at 1 µm, and (c) WPCB filler at 100 nm view.
Figure 16

FESEM analysis of the sisal fiber laminate (a) with WPCB filler, (b) micro-WPCB filler view at 1 µm, and (c) WPCB filler at 100 nm view.

3.2 Mechanical test results

Table 4 summarizes several mechanical testing findings on sisal fabrics with micro- and nano-PCB powder. Average values are calculated, and error bars are drawn based on the data scatter. Table 5 depicts the diversity of sample tensile characteristics. The pores as well as voids in the composites affect mechanical characteristics and performance. However, voids are inevitable in composites manufactured using wet hand lay-up techniques, and the formation of voids was reduced using vacuum-assisted technique. The tensile strength of composites increases steadily as the WPCB filler concentration increases (Figure 17c). It increases up to 10% for micro-WPCB fillers and 15% for nano-WPCB fillers before decreasing both their tensile values. It has been found that the addition of WPCB fillers increases the tensile strength. When compared with pure polymers, these types of composites need more stress to produce comparable levels of deformation. Because the PCB waste includes high-modulus glass fibers and epoxy particles, they operate as reinforcing fillers, reducing matrix mobility and increasing the composite stiffness [27]. The graphic value shows that the tensile strength value of composites levelled out after 10 wt% with the microfiller and 15% with the nanofiller on loading of PCB waste since sisal fibers might tear out (Figure 17a) from the matrix under elevated loadings, diminishing the reinforcing action of fillers, as shown in Figure 17b. Because the nanofiller powder penetrates more deeply into the sisal fabric laminates, a 15% nanoPCB powder sample (82.83 MPa) outperforms a 10% microfiller sample (78.2 MPa) [21,57].

Table 5

Mechanical testing and water absorption test results

Laminates Amount of filler added (%) Tensile strength (MPa) Elongation break (%) Compression strength (MPa) Flexural strength (MPa) Impact strength (J·m−1) Shore D hardness value Water absorption (%)
S1 0 64.29 1.521 37.26 84.68 26.1 83 4.16
SM2 5 27.13 0.93 36.32 31.33 35.2 84 3.01
SM3 10 78.02 1.372 50.77 60.27 77.1 83 3.04
SM4 15 70.72 1.353 48.57 51.16 35.2 84 4.54
SM5 20 23.86 0.825 40.01 29.26 11.7 85 5.61
SN2 5 17.33 0.776 30.51 31.29 32.1 83 2.04
SN3 10 40.27 1.201 34.31 33.96 50.5 85 4.81
SN4 15 82.83 1.398 54.42 79.49 88.1 86 4.71
SN5 20 26.16 0.823 34.09 27.94 32.1 82 4.62
Figure 17 
                  SEM image of tensile fracture: (a) microfiller laminate, (b) nanofiller laminate, and (c) the tensile graph.
Figure 17

SEM image of tensile fracture: (a) microfiller laminate, (b) nanofiller laminate, and (c) the tensile graph.

Since tensile loading is often studied, NFCs are not regarded as materials that can bear compression [58]. Since nanofiller evenly distributes in all pores of sisal fibers, the compression test result also shows the nanofiller composite compressive strength as 54.2 MPa, while the microfiller shows 50.7 MPa, as in Figure 18a [9,21]. Figure 18b depicts the flexural strength fluctuation of micro and nanofiller waste composites. Both showed similar patterns, with the introduction of 10% PCB microfiller waste (71.16 MPa) and 15% nanofiller (79.49 MPa) in the sisal epoxy matrix resulting in a considerable improvement in the flexural strength. Composites made of sisal that includes 0% filler perform better in bending strength tests. There is a minor decrease in the flexural strength because the homogenous contact between the fiber and the filler is not carried out to its maximum extent [28]. The inclusion of 5% additional nanofiller results in a significant increase in the flexural strength of the composites when compared to microfillers.

Figure 18 
                  Effect of micro- and nanoparticle of WPCB fillers on the (a) compression test, (b) flexure test, and (c) izod impact test.
Figure 18

Effect of micro- and nanoparticle of WPCB fillers on the (a) compression test, (b) flexure test, and (c) izod impact test.

Figure 18c shows the impact test results. The poor intraluminal strength of NFC laminates makes them susceptible to delamination, which can occur under certain impacts throughout the composite [59]. Nanofiber composites at 15% show a higher impact strength of 88.1 J·m−1 than the microfiller with 10% filler, which gives 77.1 J·m−1. Further addition of PCB fillers makes the laminates brittle, and the energy-absorbing capacity reduces drastically at 20% filler addition. Figure 19(a) shows the effect on hardness values of the addition of micro- and nanofillers in varying percentages [60]. Nanocomposite laminates show a slightly higher hardness value of 86 at 15% filler addition [38]. The addition of fillers makes the surface of the laminate harder, and the values are maintained constant for both microfiller and nanofiller laminates.

Figure 19 
                  Effect of micro- and nanoparticle WPCB fillers on the (a) shore D hardness value test and (b) water absorption test results.
Figure 19

Effect of micro- and nanoparticle WPCB fillers on the (a) shore D hardness value test and (b) water absorption test results.

3.3 Water absorption results

The use of natural fibers as reinforcements has been hampered by the fact that these fibers are susceptible to the absorption of water. Because of their cellulose-rich, hydrophilic chemical composition, natural fibers tend to absorb moisture. As the cellulose concentration of a natural fiber increases, the total amount of independent hydroxyl groups in the fiber increases, and the fiber’s ability to absorb water increases with it [61]. Microcracks are caused when there is a gap between the fiber and the matrix. Figure 19(b) shows that the water absorption rate of microfiller increases quickly to 5.61% when 20% of microfiller is added. This is because there will be a small void between the fibers and the matrix [24]. All metal powders are found in oxide forms (Table 2), which also enables absorption.

3.4 Thermal test results

The temperature history of a polymer composite is a highly essential factor that influences the organization of the amorphous and crystalline phases and, as a result, the physio-mechanical characteristics of the composite [58]. When a fiber is heated in a fiber-reinforced composite, either thermal energy is released or absorbed by the fiber. A DSC study is performed in order to investigate this phenomenon. A number of endothermic and exothermic processes are brought about as a result of the decomposition of fibers that occurs at different temperatures. It is possible to detect the thermal phase shift of the fiber with the maxima of the endothermic and exothermic processes. The difference between endothermic and exothermic reactions is that endothermic reactions absorb heat, whereas exothermic reactions give out heat. In endothermic reactions, one can find evidence of laminate melting, change in phase, evaporation, dehydration, and pyrolysis. Crystallization, oxidation, combustion, and breakdown can all be studied by exothermic reactions. The results obtained from mechanical testing, as shown in Table 5, prove that 10% of the microfiller laminate and 15% of the nanofiller laminate gave better results. For these two composite laminates, a DSC test was carried out, and the values are presented in Table 6. When the composition of the crystalline state determined from the first heating cycle and the second heating cycle are compared, it can be observed that sisal micro- and nanofiller samples during the second heating cycle have an amorphous character, despite the initial crystalline character determined from the first heating scan. This can be seen by comparing the content of the crystalline phase estimated from the first heating cycle and the second heating cycle. From Table 6, the SM2 sample glass transition temperature (T g) is 62.05°C, while SN3 is 59.06°C. Microfiller samples withstand a slightly higher glass transition temperature than nanofiller composites due to the high melting point of the heavy metallic microfiller powder present in the filler [54] (Figure 20).

Table 6

DSC test results

Samples T g, °C (first heating) T g, °C (second heating)
SM2 62.05 67.98
SN3 59.06 76.47
Figure 20 
                  DSC test results: (a) microfiller composites (MFC) first heating; (b) MFC second heating, (c) nanofiller composite (NFC) first heating, and (d) nanofiller composite (NFC) second heating.
Figure 20

DSC test results: (a) microfiller composites (MFC) first heating; (b) MFC second heating, (c) nanofiller composite (NFC) first heating, and (d) nanofiller composite (NFC) second heating.

3.5 Surface wear test results

A pin-on-disc wear test was conducted for the samples, which gave higher mechanical strength (indicated with boldface in Table 5) and thermal behavior. SM2 (a sample with 10% micro-WPCB filler) and SN3 (a sample with 15% nanofiller composite) were tested under varying load conditions of 5, 10, and 20 N, velocities of 1, 2, and 3 m·s−1, and sliding distances of 900, 1,800, and 2,700 m. The wear rate (Ws) mm3/Nm, coefficient of friction (µ), and weight reduction (g) values are tabulated in Table 7. To find the optimum input parameter conditions to reduce the wear rate, low coefficient of friction, and minimum mass reduction, the L18 Taguchi orthogonal array L18 (2^1 3^3), 4 factors, and 18 runs are used in Minitab software [57]. For each possible combination of factor levels, the signal-to-noise (S/N) ratio is determined using the formula in Table 8 [62,63,64]. The theoretical formula for the lower-is-better [62] S/N ratio using base 10 log is as follows:

S/N = 10 × log ( Σ( Y 2 )/ n )

where Y is the response for the specified combination of factors and levels and n is the number of responses in each possible combination of factors and levels.

Table 7

Levels of each parameter

Parameters Level 1 Level 2 Level 3
Samples S SM SN
Load L A 5 10 15
Velocity (m·s−1) B 1 2 3
Sliding distance (m) C 900 1,800 2,700
Table 8

Surface wear experiment (L18- Taguchi) results and S/N values

Exp. no. Control factors Wear rate, W s (mm3/N m) S/N ratio for W s Coefficient of friction (µ) S/N ratio for CoF Weight loss, W L (g) S/N ratio for W L
Sample S Load (N) A Velocity (m·s−1) B Sliding distance (m) C
1 SM 5 1 900 0.0045667 46.8080 0.811302 1.8163 0.6825 3.3181
2 SM 5 2 1,800 0.0050579 45.9206 0.805246 1.8814 1.3039 −2.3047
3 SM 5 3 2,700 0.0061528 44.2185 0.777511 2.1858 1.9993 −6.0177
4 SM 10 1 900 0.0046938 46.5695 0.761760 2.3636 0.8262 1.6583
5 SM 10 2 1,800 0.0038598 48.2687 0.702739 3.0641 1.4164 −3.0240
6 SM 10 3 2,700 0.0049930 46.0328 0.702572 3.0661 3.3308 −10.4510
7 SM 15 1 1,800 0.0031739 49.9681 0.680457 3.3439 2.2088 −6.8830
8 SM 15 2 2,700 0.0057098 44.8676 0.726997 2.7693 3.8563 −11.7235
9 SM 15 3 900 0.0032561 49.7460 0.638316 3.8992 0.9613 0.3424
10 SN 5 1 2,700 0.0085368 41.3741 0.857495 1.3353 2.7179 −8.6845
11 SN 5 2 900 0.0103406 39.7091 0.841576 1.4981 0.4801 6.3743
12 SN 5 3 1,800 0.0067454 43.4198 0.965782 0.3024 1.2695 −2.0726
13 SN 10 1 1,800 0.0054381 45.2911 0.625273 4.0786 2.0113 −6.0694
14 SN 10 2 2,700 0.0046298 46.6888 0.695604 3.1527 2.5951 −8.2832
15 SN 10 3 900 0.0053271 45.4702 0.694123 3.1712 0.9453 0.4888
16 SN 15 1 2,700 0.0029754 50.5291 0.658025 3.6351 2.8118 −8.9796
17 SN 15 2 900 0.0037179 48.5940 0.642715 3.8396 0.9314 0.6176
18 SN 15 3 1,800 0.0044561 47.0209 0.697052 3.1347 2.6406 −8.4341

3.5.1 Analysis of signal-to-noise ratio values

An analysis of the effect of each control factor (L, V, and D) on the wear rate, coefficient of friction, and weight reduction was carried out through a “S/N response” [65]. The obtained values through response tables of S/N for W S, CoF, and W L are shown in Table 9. The level values of the control factor are shown in Table 7. From these figures, optimal machining values for the control variables can be easily calculated, to reduce the wear rate (W s), coefficient of friction (µ), and weight reduction (g) as much as possible [63,64]. The curve that is linear in Figure 21 has less significant parameters, and the steep curve has more significant parameters to influence the outcome result. The level that had the highest signal-to-noise ratio among the several control factor levels was determined to be the optimal one for each control factor. As shown in the table, the S/N ratios, the levels, and the factors giving the lowest wear rate (W s) values were specified as the SM sample (Level 1, S/N = 46.93), load (Level 3, S/N = 48.45), velocity (Level 1, S/N = 46.76), and sliding distance (Level 2, S/N = 46.65). In other words, an optimum W s value to obtain a minimum wear rate was obtained with a micro-WPCB filler composite (S1), at a load (A3) of 15 N, velocity (B1) of 1 m·s−1, and a sliding distance (C2) of 1,800 m (Figure 21a). Correspondingly, S/N ratios and the levels for the factors that give the minimum coefficient of friction (µ) were specified as the SM sample (Level 1, S/N = 2.710), load (Level 3, S/N = 3.437), velocity (Level 1, S/N = 2.762) and sliding distance (Level 1, S/N = 2.765). To be specific, an optimum CoF value was obtained for a micro WPCB filler composite (S1), at a load (A3) of 15 N, velocity (B1) of 1 m·s−1, and a sliding distance (C1) of 900 m (Figure 21b).

Table 9

S/N ratio response table for W s, CoF, and W L

Levels Control factors
Wear rate (Ws) mm3/N m Coefficient of friction (µ) Wt. reduction (g)
Sample S Load L (N) A Velocity V (m·s−1) B Sliding distance D, (m) C Sample S Load, L (N) Velocity V (m·s−1) Sliding distance D (m) Sample S Load L (N) Velocity V (m·s−1) Sliding distance D (m)
1 46.93 43.58 46.76 46.15 2.710 1.503 2.762 2.765 −3.719 −1.543 −4.259 2.133
2 45.34 46.39 45.67 46.65 2.683 3.149 2.701 2.634 −4.001 −4.245 −3.074 −4.785
3 48.45 45.98 45.62 3.437 2.627 2.691 −5.792 −4.247 8.928
Delta 1.59 4.88 1.08 1.03 0.027 1.934 0.136 0.131 0.282 4.249 1.185 11.061
Rank 2 1 3 4 4 1 2 3 4 2 3 1

*Smaller is better. The optimum level control factors are shown in boldface.

Figure 21 
                     SN ratios of (a) W
                        s versus L, V, and D (b) µ versus L, V, and D, and (c) W
                        L versus L, V, and D.
Figure 21

SN ratios of (a) W s versus L, V, and D (b) µ versus L, V, and D, and (c) W L versus L, V, and D.

Similarly, S/N ratios and the levels for the factors giving a lesser weight reduction (g) were specified as the SN sample (Level 1, S/N = −3.719), load (Level 1, S/N = −1.543), velocity (Level 2, S/N = −3.074), and sliding distance (Level 1, S/N = −2.133). Therefore, an optimum weight reduction value was obtained with a micro-WPCB filler composite (S1), at a load (A1) of 5 N, velocity (B2) of 2 m·s−1, and at a sliding distance (C1) of 900 m (Figure 21c). A negative value indicates that more noise occurs (external parameters) than the signal.

From the SN ratio graph in Figure 21, it is observed that for SM (sisal with 10% microfiller) samples, to obtain a minimum wear rate (W s), the noise ratio in the load increases as the load is increased to 15 N, the noise in velocity reduces and slightly increases at 3 m·s−1, and the noise level in the sliding distance reduces at 2,700 m. Similarly, to obtain a minimum coefficient of friction (µ) for the SM sample, the SN ratio graph 7(b) shows the noise level increases in load (N), reduces in velocity (m·s−1), and shows a slight increase in the sliding distance (m). To obtain a minimum weight reduction (g), from Figure 21(c), it was observed that the noise level increases as the load sliding distance increases, and in the velocity factor, the noise level increases at 2 m·s−1 and reduces at 3 m·s−1.

The sliding distance creates a significant impact on the mass loss of sisal fiber composites. Throughout the dry sliding wear testing, the temperature along the contact surface across the specimen with the counterface increased when the sliding speed increased. This was evident for both the specimen as well as the counterface. This temperature increase was not uniform, resulting in thermal gradients. These thermal gradients led to the formation of thermal strains, which in turn led to weak fiber matrix adhesion at the interfaces [66]. As shown in Figure 21, WPCB microfiller sisal composites have a lower wear rate, a lower coefficient of friction, and a smaller mass reduction compared to WPCB nanofiller composites [67]. The microfiller of WPCB sisal still contains heavy metal powders such as copper, nickel, Sn, and Zn, as fine particles, which resist surface wear better than the nanofiller of WPCB sisal composites since the metal powders are very fine (<100 nm) and easily wear out from the surface [68]. The SEM image (Figures 2224) shows the fiber pullout and laminate disintegration at optimum SN ratios from Figure 21.

Figure 22 
                     Normal probability plot for the (a) wear rate, (b) coefficient of friction, and (c) weight reduction.
Figure 22

Normal probability plot for the (a) wear rate, (b) coefficient of friction, and (c) weight reduction.

Figure 23 
                     (a–c) SEM image of the worn surfaces of the microfiller laminate at L = 15 N, V = 1 m·s−1, and D = 1,800 m.
Figure 23

(a–c) SEM image of the worn surfaces of the microfiller laminate at L = 15 N, V = 1 m·s−1, and D = 1,800 m.

Figure 24 
                     (a–c) SEM image of the worn surfaces of the microfiller laminate at L = 15 N, V = 1 m·s−1, and D = 900 m.
Figure 24

(a–c) SEM image of the worn surfaces of the microfiller laminate at L = 15 N, V = 1 m·s−1, and D = 900 m.

3.5.2 Analysis of variance (ANOVA)

ANOVA is a statistical approach that can be used to assess independent interactions with each of the control variables that are involved in a test design. Within the scope of this investigation, an ANOVA test was carried out to investigate how the variables of the sample, load, velocity, and sliding distance influenced the wear rate, coefficient of friction, and weight loss. Table 10 displays the ANOVA findings on the wear rate, the coefficient of friction, and the amount of weight loss. This investigation was carried out with a level of significance of 5% and a degree of confidence of 95%. When performing an ANOVA, the significance of the control variable is assessed by evaluating the P (probability value) values of all control factors. The proportional percentage of each parameter’s contribution is displayed in the final column of the table. This value represents the level of influence each parameter has on the overall performance of the process. Based on Table 10, the percentage contributions of variables A, B, C, and D to the specific wear rate were found to be 15.79%, 76.32%, 2.63%, and 5.26%, respectively. This information was obtained from the data presented in the table. Therefore, load (N) was the most important component that affected the wear rate, accounting for 76.32% of the total.

Table 10

ANOVA values

Source DF Adj SS Adj MS F-value P-value Contribution %
Wear rate, W S
Sample 1 0.000006 0.000006 2.94 0.117 15.79
Load (N) 2 0.000029 0.000014 6.60 0.015 76.32
Velocity (m·s−1) 2 0.000001 0.000001 0.30 0.746 2.63
Sliding distance (m) 2 0.000002 0.000001 0.38 0.695 5.26
Error 10 0.000022 0.000002
Total 17 0.000060
S R-sq R-sq (adj) R-sq (pred)
0.0014501 74.73% 40.04% 0.00%
Coefficient of friction, µ
Sample 1 0.000278 0.000278 0.08 0.786 0.27
Load (N) 2 0.101054 0.050527 14.12 0.001 98.52
Velocity (m·s−1) 2 0.000592 0.000296 0.08 0.921 0.58
Sliding distance (m) 2 0.000652 0.000326 0.09 0.914 0.64
Error 10 0.035786 0.003579
Total 17 0.138362
S R-sq R-sq (adj) R-sq (pred)
0.0474370 90.74% 72.35% 47.31%
Weight loss, W L
Sample 1 0.0212 0.02116 0.13 0.730 0.15
Load (N) 2 1.9682 0.98411 5.85 0.021 13.48
Velocity (m·s−1) 2 0.0381 0.01903 0.11 0.894 0.26
Sliding distance (m) 2 12.5773 6.28867 37.36 0.000 86.12
Error 10 1.6832 0.16832
Total 17 16.2880
S R-sq R-sq (adj) R-sq (pred)
0.379831 91.14% 84.94% 71.30%

DF, degree of freedom; S, standard deviation; Adj SS, adjusted sum of squares; and Adj MS, adjusted sum of mean squares.

The ANOVA findings revealed that the percentage contributions of variables A, B, C, and D to the coefficient of friction were, in order, 0.27%, 98.52%, 0.58%, and 0.64%, respectively. This demonstrated that the variable that had the maximum influence over the coefficient of friction was the same as load (N), with a percentage of 98.52%. In the same direction, the results in Table 10 show that the percentage contributions of components A, B, C, and D that influence weight loss are 0.15%, 13.48%, 0.26%, and 86.12%, respectively. These figures were derived from the data presented in Table 10. This demonstrated that the element with the greatest impact on the weight loss was the sliding distance (D), which contributed 86.12% of the total. The percentage of inaccuracy was extremely low, 0.000060 for W s, 0.035786 for CoF, and 1.6832 for W L. According to the ANOVA table for the many parameters impacting the specific wear rate of the sisal laminate in Table 10, the value of P is significant to the response if it is less than 0.05, and the regression analysis is carried out at a 95% confidence interval [64].

Therefore, the load factor with a value of 0.015 is the highest significant factor that increases the particular wear rate of the microfiller sisal laminate when it is subjected to the conditions that were evaluated. The type of sample is the next significant component, with a P value of 0.117. The other two parameters, sliding speed, and sliding distance, cannot be considered significant factors in impacting the wear qualities of the sisal microfiller laminate because their P values are higher than 0.05. In addition, the R-square value for the model that was developed is lower than 90%, i.e., the model explained 74.73% of fitted data in the regression model [69]. This is probably because the coarse counterface of abrasive paper (800 grit) that was utilized in this study, which caused a continuous variance within the frictional value in each test that was performed is responsible for it. Any values above 70% can be chosen to be fitted into the model. The value suggests the influence of independent variables (L, V, and D) over dependent variables (W S, µ, and W L) [70].

Again, the load factor, which has a P value of 0.001, tends to be relevant for the microfiller sisal laminates when it comes to the components that affect the coefficient of friction. In addition, it is claimed that the retrieved data are compatible with the model that was created because the R-square value is greater than 90%. It can be seen from Table 10 that the P value for the weight loss that occurs due to the parameters of load, speed, and distance is 0.000. The sliding distance plays a big role in this model; thus, the R-square value that is created is above 90%, which indicates that the model is accurate. As a result, the application of ANOVA to the data also demonstrates and validates the considerable effect that the external parameters of load, speed, and sliding distance have [60]. Figure 22 displays a normal probability plot of the expected values of the Taguchi method. The linear Taguchi models show strong prediction, as the projected values are far less than the mean line [63].

3.6 SEM analysis of worn surface morphology

Surface morphology of the composites that experience an optimum specific wear rate at L = 15 N, V = 1 m·s−1, and D = 1,800 m, coefficient of friction at L = 15 N, V = 1 m·s−1, and D = 900 m and weight loss at L = 5 N, V = 2 m·s−1, and D = 900 m (10% SM sample) is shown in Figures 2325. Images were analyzed to examine the wear mechanisms of the tested specimens through SEM micrographs.

Figure 25 
                  (a–c) SEM image of the worn surfaces of the microfiller laminate at L = 5 N, V = 2 m·s−1, and D = 900 m.
Figure 25

(a–c) SEM image of the worn surfaces of the microfiller laminate at L = 5 N, V = 2 m·s−1, and D = 900 m.

Figures 2325 show the SEM images of microfiller sisal composite specimens that were subjected to wear testing. All of the sisal samples with the aforementioned conditions may exhibit considerable debonding. Matrix fracture, exposed fibers, fiber pull-out, and matrix plastic deformation were also observed in the specimens [48]. Clearly, apparent delamination and debonding occurred at the surface of the laminate. Wear debris, fiber fractures, and matrix rupture are all visible in the SEM images of the deteriorated surfaces of sisal composites.

4 Conclusion

In the current investigation, used PCBs are ground into micro- and nanopowder forms. SEM analyses of the mechanical, thermal, wear, water absorption, and morphology were carried out to investigate the effect of different particle sizes of fillers (micro and nano). The following is a summary of the findings:

  • The results of mechanical testing reveal an increase in values as compared to the 0% filler laminates for compression strength, tensile strength, and impact strength. The results of the laminate with 15% nanofiller added were superior compared to those with 10% microfiller. Flexure strength values reduce slightly with the addition of fillers. Because nanofillers can penetrate even the smallest spaces that are present in the cellulose of sisal fibers, it improves the strength of the material. The results of mechanical tests have shown that nanofiller composites perform better than microfiller composites. Maximum values of the tensile strength of 82.83 MPa, an elongation before the break of 1.39%, a compressive strength of 54.42 MPa, a flexure strength of 79.49 MPa, and an impact strength of 88.1 J·m−1 have been measured for 15% nanofiller composites. These values are nearly equivalent to those of other commercial polymers such as polycarbonate and PMMA

  • The surface has a Shore D hardness of 86, which indicates that it can be scratch-resistant in addition to having good resistance to being penetrated. The DSC test reveals that the microfiller laminate has a slightly higher initial heating value than the nanofiller laminate. This is because the metal powder in the laminates has the ability to resist softening. The fact that the natural fiber laminates were found to absorb up to 5.61% of the micro-WPCB filler during the water absorption test suggests that these laminates are susceptible to moisture absorption. Because of the significant cellulose content, there was an increase in the amount of moisture that was absorbed. In the presence of environmental circumstances, bio-based coatings, and in particular PFA (perfluoroalkoxy), are able to significantly reduce the amount of moisture that fiber-reinforced composites are able to absorb while also retaining the materials’ capacity to function as expected structurally.

  • The XRF pattern reveals the presence of harmful heavy metals in the WPCB filler. These fillers include copper, lead, zinc, manganese, tin, nickel, and boron, all of which are present in the oxide form. In addition, the FESEM-EDX findings point to the incorporation of WPCB fillers into the sisal laminates.

  • Surface wear tests are also performed since natural fiber-reinforced composites are employed for engineering purposes. Taguchi L18 analysis was used to determine the optimum parameter values for the load, speed, and sliding distance in order to lower the specific wear rate, coefficient of friction, and weight loss of SM and SN samples. The S/N ratio reveals that the SM sample possesses more wear-resistant capacity and the control factors L = 15 N, V = 1 m·s−1, and D = 1,800 m are the optimal parameters for obtaining a lower specific wear rate; L = 15 N, V = 1 m·s−1, and D = 900 m are the optimal parameters for obtaining a lower value of the coefficient of friction; and L = 5 N, V = 2 m·s−1, and D = 900 m conditions indicate a smaller amount of weight reduction.

  • The ANOVA table predicted the significant control factor at the percentage level. Load and sliding distance play a significant role in altering the wear properties of the composites. The values indicated that microfiller laminates show less wear rate and weight reduction than nanofiller laminates. The size of the micro-WPCB filling materials affects the change in the wear resistance, coefficient of friction, and weight loss. Since the particle size of heavy metal powders in the microfiller can resist wear more than nano-sized metal powders, the microfiller sisal laminate shows a better outcome in the overall wear characteristics.

  • Experiments showed that with the addition of the e-waste (PCB) filler, samples showed comparable values in all mechanical and thermal tests. Thus, we can suggest that it could be used as a filler in the bio-degradable NFCs for engineering applications rather than being dumped into landfills, where it would cause environmental damage.

  1. Funding information: Authors state no funding involved.

  2. Author contributions: Jebasingh Immanuel Durai Raj: writing – original draft, investigation, and formal analysis; Ramamoorthy Iyer Balasubramaniyan Durairaj: writing – review and editing, and formal analysis; Amaladas John Rajan: writing – review and editing, and investigation; Praveen Barmavatu: conceptualization and methodology.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Data availability statement: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Received: 2023-06-13
Accepted: 2023-12-10
Published Online: 2023-12-31

© 2023 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  88. Study on the preparation of glycerylphosphorylcholine by transesterification under supported sodium methoxide
  89. Wireless network handheld terminal-based green ecological sustainable design evaluation system: Improved data communication and reduced packet loss rate
  90. The optimization of hydrogel strength from cassava starch using oxidized sucrose as a crosslinking agent
  91. Green synthesis of silver nanoparticles using Saccharum officinarum leaf extract for antiviral paint
  92. Study on the reliability of nano-silver-coated tin solder joints for flip chips
  93. Environmentally sustainable analytical quality by design aided RP-HPLC method for the estimation of brilliant blue in commercial food samples employing a green-ultrasound-assisted extraction technique
  94. Anticancer and antimicrobial potential of zinc/sodium alginate/polyethylene glycol/d-pinitol nanocomposites against osteosarcoma MG-63 cells
  95. Nanoporous carbon@CoFe2O4 nanocomposite as a green absorbent for the adsorptive removal of Hg(ii) from aqueous solutions
  96. Characterization of silver sulfide nanoparticles from actinobacterial strain (M10A62) and its toxicity against lepidopteran and dipterans insect species
  97. Phyto-fabrication and characterization of silver nanoparticles using Withania somnifera: Investigating antioxidant potential
  98. Effect of e-waste nanofillers on the mechanical, thermal, and wear properties of epoxy-blend sisal woven fiber-reinforced composites
  99. Magnesium nanohydroxide (2D brucite) as a host matrix for thymol and carvacrol: Synthesis, characterization, and inhibition of foodborne pathogens
  100. Synergistic inhibitive effect of a hybrid zinc oxide-benzalkonium chloride composite on the corrosion of carbon steel in a sulfuric acidic solution
  101. Review Articles
  102. Role and the importance of green approach in biosynthesis of nanopropolis and effectiveness of propolis in the treatment of COVID-19 pandemic
  103. Gum tragacanth-mediated synthesis of metal nanoparticles, characterization, and their applications as a bactericide, catalyst, antioxidant, and peroxidase mimic
  104. Green-processed nano-biocomposite (ZnO–TiO2): Potential candidates for biomedical applications
  105. Reaction mechanisms in microwave-assisted lignin depolymerisation in hydrogen-donating solvents
  106. Recent progress on non-noble metal catalysts for the deoxydehydration of biomass-derived oxygenates
  107. Rapid Communication
  108. Phosphorus removal by iron–carbon microelectrolysis: A new way to achieve phosphorus recovery
  109. Special Issue: Biomolecules-derived synthesis of nanomaterials for environmental and biological applications (Guest Editors: Arpita Roy and Fernanda Maria Policarpo Tonelli)
  110. Biomolecules-derived synthesis of nanomaterials for environmental and biological applications
  111. Nano-encapsulated tanshinone IIA in PLGA-PEG-COOH inhibits apoptosis and inflammation in cerebral ischemia/reperfusion injury
  112. Green fabrication of silver nanoparticles using Melia azedarach ripened fruit extract, their characterization, and biological properties
  113. Green-synthesized nanoparticles and their therapeutic applications: A review
  114. Antioxidant, antibacterial, and cytotoxicity potential of synthesized silver nanoparticles from the Cassia alata leaf aqueous extract
  115. Green synthesis of silver nanoparticles using Callisia fragrans leaf extract and its anticancer activity against MCF-7, HepG2, KB, LU-1, and MKN-7 cell lines
  116. Algae-based green AgNPs, AuNPs, and FeNPs as potential nanoremediators
  117. Green synthesis of Kickxia elatine-induced silver nanoparticles and their role as anti-acetylcholinesterase in the treatment of Alzheimer’s disease
  118. Phytocrystallization of silver nanoparticles using Cassia alata flower extract for effective control of fungal skin pathogens
  119. Antibacterial wound dressing with hydrogel from chitosan and polyvinyl alcohol from the red cabbage extract loaded with silver nanoparticles
  120. Leveraging of mycogenic copper oxide nanostructures for disease management of Alternaria blight of Brassica juncea
  121. Nanoscale molecular reactions in microbiological medicines in modern medical applications
  122. Synthesis and characterization of ZnO/β-cyclodextrin/nicotinic acid nanocomposite and its biological and environmental application
  123. Green synthesis of silver nanoparticles via Taxus wallichiana Zucc. plant-derived Taxol: Novel utilization as anticancer, antioxidation, anti-inflammation, and antiurolithic potential
  124. Recyclability and catalytic characteristics of copper oxide nanoparticles derived from bougainvillea plant flower extract for biomedical application
  125. Phytofabrication, characterization, and evaluation of novel bioinspired selenium–iron (Se–Fe) nanocomposites using Allium sativum extract for bio-potential applications
  126. Erratum
  127. Erratum to “Synthesis, characterization, and evaluation of nanoparticles of clodinofop propargyl and fenoxaprop-P-ethyl on weed control, growth, and yield of wheat (Triticum aestivum L.)”
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