Mechanical and Tribological Behavior of LM26/SiC/Ni-Gr Hybrid Composites

Abstract

The study evaluates the mechanical and wear properties of LM26 alloy and its hybrid composites with silicon carbide (SiC) and nickel-coated graphite (Ni-Gr). LM26 aluminum alloy is generally known for its high strength, wear, and corrosion resistance compared to similar materials such as zinc and magnesium. The effect of Ni-Gr was studied, with 2 wt.% was found to provide the best mechanical properties. LM26 composites reinforced with varying percentages of SiC (0 to 30 wt.%) showed the best properties at 20 wt.% reinforcement after fabrication using a bottom pouring type stir casting setup (Two step feeding method). Evaluation of five hybrid LM26 composites through tensile strength, elongation, hardness, impact, porosity, and thermal studies showed that the LM26/2 wt.% Ni-Gr/20 wt.% SiC configuration showed the best filler composition for improved strength. Sliding wear evaluation using experimental and Taguchi analysis was performed at different configurations to identify the best wear resistance. Microstructure studies showed the presence of Ni-Gr particles forming coatings and temperature playing a significant role in the progression of the wear rate. Furthermore, the hybrid composite with 20% SiC and 2% Ni-Gr reinforcement showed the best wear resistance.

1. Introduction

Composite materials, known as metal matrix composites (MMCs), are created by combining a matrix material, such as aluminum, titanium, magnesium, or copper, with reinforcement materials, such as carbides, metallic oxides, borides, nitrides, or non-metallic materials such as red mud or fly ash [1,2,3,4]. The reinforcement materials are dispersed throughout the matrix and provide improved properties over the matrix alone, and slower degradation than the reinforcement materials alone. Reinforcing aluminum with metallic materials is a common practice in industrial applications and has been the subject of much research in recent years to improve stiffness and strength [5]. However, using reinforcement materials such as nitrides, carbides, and borides oxides can present machining challenges and lead to abrasion, cracking, and premature failure. Choosing the best reinforcement material for an aluminum matrix is an ongoing focus for scientists and engineers [6,7,8].

MMCs combine metal matrix and reinforcing phases using liquid-state processing routes such as stir casting, powder metallurgy, and spray deposition, and solid-state fabrication routes such as mechanical alloying, friction stir, and sintering [9,10]. The stir-casting route is advantageous due to its simplicity, flexibility, and high production rate. However, it has drawbacks, such as gas entrapment, reinforcement particle fracture, and agglomeration. A well-dispersed reinforcement in the matrix material, wettable characteristics between the matrix and reinforcements, and adequate porosity levels are all essential elements for obtaining optimal properties in MMCs [11,12,13,14].

Researchers worldwide demonstrated that nano fillers greatly influence the properties of AMCs (aluminum matrix composites). Jia et al. [15] used nanofillers (NFs) to develop AMCs through the ultrasonic-assisted process and reported better dispersion of fillers into the matrix. Similarly, Choi and Awaji [16] developed a novel AMC containing various proportions of nanoparticle sizes (10⁻⁹ m) and investigated its properties. The authors asserted that NFs support molecular bonding of matrix and elaborate dispersion reasonably. Nano-sized particles evenly distributed in the matrix show very low dislocations during fabrication. This phenomenon effectively contributes towards strength enhancement and limits pores drastically [17].

Silicon carbide considerably has predominant properties such as high modulus and thermal and electrical performance and economical with similar grade reinforcements. Bhushan et al. [18] reported after conducting experiments on AMCs that SiC inclusion increased mechanical properties by up to 200% and significant improvement in internal molecular arrangements of fillers into the matrix. Silicon carbide particles are also well known for their wear properties. Kumar et al. [19] developed AA7075/SiC composites and reported that SiC greatly enhances wear properties and hardness more than the virgin alloys. It mixes with the matrix very well due to the density variation. Kumar et al. [20] also compared the strengths of micro and nano SiC-reinforced AA7075 composites. They reported that nano-size fillers using composites show better tensile, wear behavior, and uniform dispersion than micro-size particles.

Modi et al. [21] compared the wear behavior of stir-casted zinc aluminum alloys with cast iron. They asserted that ZA shows better wear resistance and reasonable friction heating than the cast iron. Results also exhibit that load and velocity influence these properties significantly. Gencaga and Temel [22] investigated the wear behavior of the Zn/Al40/Cu2/Silicon hybrid configuration. They reported that the proposed hybrid samples exhibit the least coefficient of friction and improved wear resistance than bronze composites. Savaskan and Aydiner [23] investigated the effect of Cu on tribological behavior in zinc–aluminum alloys. They concluded that Cu inclusion improves microhardness by up to 40% more than the unreinforced alloy, whereas tensile and wear resistance was enhanced by up to 5%. Unlu [24] conducted a series of tests to analyze materials such as bronze, brass, white metal, copper, zinc, aluminum, and zinc–aluminum alloys to utilize for journal bearings. It was reported that zinc–aluminum alloys have superior mechanical properties. Khonsari and Lin [25] investigated Al40Zn with Cu-filled alloys for its wear and hardness properties and compared it with bronze alloys. They asserted that Cu inclusion in Al40 significantly impacts hardness and wear resistance. Moreover, it enhances tensile properties by up to 3% more than neat and bronze composites.

Numerous researchers worked on the mechanical and tribology behavior study of the hybrid metal matrix composites. Bekir et al. [26] conducted series of tests to analyze various materials such as bronze, brass, white metal, copper, zinc, aluminum, and zinc aluminum alloys to utilize it for journal bearings. They reported that zinc aluminum alloys are greatly admirable in achieving superior mechanical properties. The Taguchi method helps to determine optimal conditions for multiple outcomes, but it has limitations when it comes to optimizing multiple outputs with numerous factors [27,28]. The use of LM26 alloy as a metallic matrix for composites is a recent development and an area that has not been extensively explored for high-temperature wear environments. By incorporating SiC as a reinforcing material in varying amounts, it is possible to investigate the effects of reinforcement on the mechanical and tribological properties of the composites. The addition of Ni-Gr as a secondary reinforcement is a novel approach for enhancing the tribological properties of the composites.

The current study evaluates mechanical and wear behavior of single (LM26/SiC) and hybrid LM26 composites prepared through stir-casting method. Advanced optimization techniques, such as the Taguchi approach, were employed to achieve optimal composite material suitable for high-temperature applications. The microstructures of the composites were evaluated, and the results were verified through the examination of wear resistance with the optimized conditions obtained through the optimization approach. LM26 has almost all the required properties to utilize in the new era of high-temperature applications. No or very few researchers have attempted to study all the mechanical and wear behavior of AMCs combined. Therefore, this research presents a significant novel contribution to the field of composite materials and provides critical knowledge in investigating their wear and mechanical properties for high-temperature applications.

2. Experimental Methods

2.1. Materials

The LM26 aluminum alloy was reinforced with SiC particles (approximate size: 49 µm) and nickel-coated graphite (approximate size: 24 µm) to improve its composite strength. The nickel coating significantly improves the mechanical properties of graphite, making it more durable, wear-resistant, and robust under high load conditions. Additionally, the nickel coating enhances the adhesion and compatibility between graphite and the underlying substrate, preventing delamination and improving overall performance [29,30]. The composition of the LM26 alloy is detailed in

Table 1. Chemical composition of aluminum LM26 alloy.

Elements	Cu	Si	Fe	Mg	Mn	Zn	Ti	Ni	Other	Bal.
wt.%	2.3–4.7	8.4–10.6	1.3	0.6–1.4	0.2	1	0.2	1	0.3	Al.

.

2.2. Fabrication of Composites

The stir casting method, which includes subsystems such as a magnetic stirrer unit, temperature limiting unit, and mold setups, was employed for the composite fabrication. The fillers were preheated to a temperature of 400 °C to enhance their wettability with the matrix material and to eliminate moisture content. First, SiC particles were added to the molten alloy and then the Ni-Gr particles were added. A crucial aspect of the stir casting process that must be considered during fabrication is the formation of an aluminum oxide layer on the surface of the molten metal, as the aluminum core inside the crucible reacts with atmospheric oxide. This aluminum oxide layer protects the metal and prevents further reaction with the atmosphere. Once the matrix reached its maximum temperature of 700 °C, the preheated fillers were added to the molten metal. The stirrer unit was activated, and the ceramic and molten metal mixture was agitated at 500 rpm for 5–8 min using three-pin impeller blades to mix the matrix and filler thoroughly. Care was taken to ensure that the metal was thoroughly agitated during the mixing process and that the vortex entirely absorbed the filled ceramic particles. After mixing, any excess slurry on the metal surface was removed using a scraper, and the molten metal was poured directly into a preheated mold (at 100 °C) after removing the slag floating on the molten metal surface. The composite material was allowed to cool to room temperature for ten hours before being removed from the die.

Abrasive cutters and automatic CNC lathe machines were used to prepare specimens. The abrasive processed metal cast samples were thoroughly prepared for testing, including mounting, polishing, and gold coating. Single LM26/SiC composite samples were prepared by varying SiC (5, 10, 15, 20, and 30 wt.%). The optimum Ni-coated graphite amount was determined by adding different percentages of 1.0, 2.0, and 3.0 wt.% in LM26 alloy. Finally, hybrid LM26/SiC/Ni-Gr composites were prepared with the optimum amount of Ni-Gr and varying SiC amounts. Various filler compositions were selected for the fabrication of MMCs, and the composite configurations and their constitutions are listed in

Table 2. Hybrid configurations of AMCs.

Designation	Sample Code	Composition (Weight Percentage)
Matrix alloy	NEAT Sample	Aluminum LM26
Hybrid Composition	HAMC1	Aluminum LM26 + Ni-Gr (02 wt.%) + SiC (05 wt.%)
	HAMC2	Aluminum LM26 + Ni-Gr (02 wt.%) + SiC (10 wt.%)
	HAMC3	Aluminum LM26 + Ni-Gr (02 wt.%) + SiC (15 wt.%)
	HAMC4	Aluminum LM26 + Ni-Gr (02 wt.%) + SiC (20 wt.%)
	HAMC5	Aluminum LM26 + Ni-Gr (02 wt.%) + SiC (30 wt.%)

with their respective sample codes. Neat LM26 was also prepared as a reference material for comparison with other composites.

2.3. Composite Characterization

2.3.1. Tensile Test

Tensile tests of the hybrid samples were carried out using a computerized Unitech—Instron 4001 series ISO 7500-1 standard UTM machine equipped with HIGH TOWN LBG, Italy. Initially, the specimens were prepared as per ASTM E8/E8M standard (12.5 mm diameter × 50 mm gauge length) for the testing with a loading rate of 1 mm/ min. The surfaces of the samples were polished using emery sheets (900 grit) to remove debris and dust. The core objective of the testing is to identify the difference in yield, elongation, and ultimate strengths of the materials. For each configuration, three samples were prepared, and average results were reported.

2.3.2. Impact Test

A Charpy V notch impact test was performed to evaluate the maximum energy absorption capacity of the prepared samples. Tests were conducted using a ball-type pendulum impact tester of ISO 1757: 1988 standard with the sample dimensions of 55 mm × 10 mm × 10 mm (V notch angle of 45 degrees).

2.3.3. Hardness Test

B 3000 model Brinell hardness tester was utilized to evaluate the samples’ hardness. Indentations were performed at different locations of samples, and average results correspond to a series of 5 measurements.

2.3.4. Porosity/Void Measurement

It was essential to measure the density and porosity level of the material to use it for diversified weight-cantered applications. The theoretical and experimental densities were calculated separately and compared for obtaining accurate results. The amount of porosity of the fabricated samples was calculated using the following equations.

Porosity% = (Theoretical Density − Experimental density)/(Theoretical Density) × 100

(1)

Theoretical Density of composite (ρ_c) = (ρ_m × V_m) + (ρ_r × V_r)

(2)

where ρ_m and ρ_r are the density of the matrix and reinforcement, respectively. V_m and V_r are the volume fraction of the matrix and reinforcement, respectively.

Experimental density = (W_air)/((W_air) − (W_medium)) × Density of medium

(3)

where, Density of medium = Density of Ethanol = 0.791 (g/cm³), W_air = Specimen Weight in the air (g), and W_medium = Specimen weight in ethanol (g).

2.3.5. Sliding Wear Test

A pin-on-disc tribometer with a standard disc and rig arrangement was utilized for sliding wear tests. EN-24 (shaft steel) with surface roughness (Ra) of 0.3 µm and hardness of 50 HRC was used as a tribopair.

In this research, EN 24 shaft was effectively used against the proposed hybrid aluminum composites for advanced wear performance study. Pin diameter ranges from Φ3 mm to 12 mm, pin temperature is about Min: ambient to Max: 400 °C, load and disc rotation speed varies from 5 N to 200 N and 200–2000 RPM respectively. At the same time, the various wear process parameters such as sliding distance (50–400 m), speed (100–600 rpm), applied load (10–60 N), and temperatures (50–250 °C) are varied while testing the wear resistance of the samples.

2.3.6. Microscopical Observation

The microscopic image of the unfractured and fractured samples was captured using an FEI Quanta 400F Field Emission microscope with an accelerating voltage of 10 kV. Similarly, samples are mirrored polished and thoroughly polished using emery sheets, then mounted in the mold for examination.

3. Results and Discussions

3.1. Selection of Matrix Alloy and Ni-Gr Content

LM26 is an aluminum-based alloy from the aluminum-silicon-magnesium alloy family. It is a high-strength alloy that is primarily used for its excellent casting properties, high-temperature strength, and corrosion resistance. LM26 is a highly adaptable alloy that finds widespread use across several industries such as aerospace, marine, automotive, and industrial applications. In the proposed research, the LM26 alloy was examined and compared to similar materials such as zinc, magnesium, and pure aluminum. Analysis was performed, and results were documented, including elongation, impact energy absorption, hardness, and tensile strength measurements for various materials, as shown in Figure 1. The microstructure and elemental analysis of the matrix material are depicted in Figure 2. The results indicated that the LM26 alloy had better wettability between all types of ceramics reinforced within it [3]. By optimizing the distribution and dispersion of ceramic particles in the matrix, the mechanical properties of the composite are improved. The LM26 alloy, an aluminum-based alloy, contains copper, magnesium, and manganese, in addition to aluminum. Copper enhances the alloy’s strength and hardness, while magnesium improves its ductility and toughness. Furthermore, the addition of magnesium enhances the alloy’s ductility, allowing it to deform without fracturing. The mechanical properties are also enhanced by the refined grain structure, which lowers the probability of flaws and improves the material’s strength and toughness. Manganese is also beneficial in refining the alloy’s grain structure, improving its mechanical properties. The LM26 alloy exhibited the highest elongation, impact energy absorption, and reasonable hardness improvement. Based on these findings, the LM26 alloy was preferred for its superior properties as a matrix material. EDS analysis confirmed the elemental composition of the LM26 alloy. The mechanical behavior of the LM26 alloy looks excellent when compared to the other materials [9,14,23].

Although graphite improves wear resistance through its inherent solid lubrication effect, but its load bearing capacity is still poor. By coating Ni on the graphite can improve its mechanical properties and resists the agglomeration of graphite in the LM26 alloy matrix [31,32].

3.2. Mechanical Characterization of LM26/Ni-Gr Composites

The physical and mechanical properties of LM26 alloy filled with various weight percentages of nickel-coated graphite (Ni-Gr) were investigated to find the optimum amount of Ni-Gr filler for the best mechanical and tribological properties. Initial experiments were conducted with 1, 2, and 3 wt.% Ni-Gr-filled composites and compared to LM26 alloy or unfilled composites. The difference between theoretical and experimental densities, and the porosity levels, was reported along with mechanical characterization. Figure 3 illustrates the observed results from the experiments. Theoretical and experimental densities revealed that porosity gradually increased with the filler percentages. Microscopic images of LM26/Ni-Gr composites revealed the presence of small pores and voids on the surface of the samples (Figure 4).

Tensile strength increased with the filler percentages up to 2.0 wt.%, but slightly decreased with a further increase in the Ni-Gr amount [33]. A similar trend was also noticed for the impact strength. On the other hand, Brinell hardness values gradually reduced due to the softness of the graphite particles [34]. Both density and ductility or elongation percentages increased with the increasing concentration of Ni-Gr, again for the same reason of softer graphite particle introduction. Mendoza [35] reported that Ni-Gr addition in the aluminum matrix possess lower porosity and improved mechanical performance along with the significant wear resistance. Therefore, it was concluded that 2.0 wt.%, Ni-Gr reinforced particles could provide a better combination of strength, hardness, density, and ductility.

3.3. Mechanical and Microstructural Characterization of SiC/LM26 Composites

As shown in the LM26 + Ni-Gr single composite, the hardness decreased due to the addition of softer graphite, a hybrid composite with the introduction of harder SiC has been proposed. Tensile strength, hardness, and energy absorption properties of the LM26/SiC composites gradually increased up to 20 wt.% of SiC reinforcements and decreased after that (Figure 5). The ductility of the composites drastically reduced with the SiC reinforcement, while the porosity was found to increase. The results indicated that up to 20 wt.% SiC reinforcement resulted in superior properties, and this configuration is proposed for further examination. The morphology of 30 wt.% SiC reinforced composites at different magnifications were captured using an Olympus microscope and presented for discussion in Figure 6. It was evident that pores and small voids were present in the contour, and clusters of SiC were also found in the samples, which may contribute to a reduction in strength [36,37].

3.4. Mechanical Characterization of Hybrid Aluminum Composites

Tensile, elongation, hardness, impact, and porosity values of the hybrid LM26/SiC/Ni-Gr composites are presented in Figure 7. The results of the tensile studies indicate that the HAMC4 configuration exhibited superior elongation and strength compared to other compositions. Hardness also increased gradually with increasing filler percentages but reached a limit with further additions of SiC particles [38]. In summary, the general trend in single and hybrid composites was similar. However, higher ductility and impact energy (except HAMC5) were found in the hybrid composites compared to the single composites and neat alloys. On the other hand, the hybrid composites at the optimum concentration of SiC (20 wt.%) showed lower strength and hardness than their single counterparts.

The microstructure of the hybrid samples was thoroughly examined using a microscope at magnifications ranging from ×150–200, and the results are presented in Figure 8. It is evident from the images that there is a smooth distribution of micro-constituents on the matrix. The characterization studies revealed that the HAMC4 composite is reinforced with 20 wt.% SiC and 2 wt.% Ni-Gr exhibits superior results. SEM and EDS analyses were performed on the HAMC4 composite to validate the study further and the results are presented in Figure 9.

3.5. Hybrid Composites Wear Behavior Analysis

The combination of 2 wt.% Ni-Gr reinforcement and varying weight percentages of SiC (5, 10, 15, and 20%) on the sliding wear behavior of the fabricated hybrid composites were investigated using a standard EN24 disc and various process factors, including temperature, applied load, filler weight percentage, and sliding velocity, according to L16 orthogonal array. Wear tests were conducted to determine the deviation and accuracy level of the developed models. It was observed from the statistical analysis that the most dominating parameter of wear is temperature, followed by the applied load and filler percentage, and the least dominating parameter was sliding velocity. It was observed that 2 wt.% of Ni-Gr reinforcement exhibits superior wear resistance compared to the other configurations, and 20 wt.% of SiC addition exhibited excellent wear behavior [39].

3.5.1. Taguchi Analysis

After analyzing the process parameters of hybrid configurations using L16 orthogonal array for three samples, its average values were reported in

Table 3. Wear results for hybrid configurations as per L16 (4⁵).

Test	Sliding Speed (A)	Load (B)	Temperature (°C)	Sliding Distance (D)	Filler Content (E)	Wear (Micron)	SN Ratio
	m/s	N	°C	km	wt.%
1	1	20	40	1.5	5	186	−45.3903
2	1	40	60	3	10	273	−48.7233
3	1	60	80	4.5	15	349	−50.8565
4	1	80	100	6	20	436	−52.7897
5	2	20	60	1.5	5	281	−48.9741
6	2	40	40	3	10	243	−47.7121
7	2	60	100	4.5	15	401	−52.0629
8	2	80	80	6	20	439	−52.8493
9	3	20	80	1.5	5	350	−50.8814
10	3	40	100	3	10	448	−53.0256
11	3	60	40	4.5	15	313	−49.9109
12	3	80	60	6	20	414	−52.3400
13	4	20	100	1.5	5	407	−52.1919
14	4	40	80	3	10	391	−51.8435
15	4	60	60	4.5	15	430	−52.6694
16	4	80	40	6	20	372	−51.4109

. A better approach was followed for the optimization, and experimentation was performed using Minitab 18 software. Results in the form of noise-to-signal ratio were reported in

Table 4. Response for SN Ratios.

Level	A	B	C	D	E
1	−49.44	−49.36	−48.61	−50.41	−50.98
2	−50.40	−50.33	−50.68	−50.92	−50.77
3	−51.54	−51.37	−51.61	−51.07	−50.78
4	−52.03	−52.35	−52.52	−51.01	−50.88
Delta	2.59	2.99	3.91	0.66	0.21
Rank	3	2	1	4	5

. The difference between each factor’s highest and lowest average response values can calculate delta values.

Figure 10 represents the standard S/N ratio, means of variance, and contour plot with respect to temperature, applied load and wear rate. According to the results, the temperature was found to have the highest rank, followed by the applied load (rank 2), filler weight percentage (rank 4), sliding velocity (rank 3), and sliding distance (rank 5). The delta values also indicated that the higher the delta values, the greater the influence of the parameter. Furthermore, Figure 11 revealed that the optimal wear rates were observed at (A1, with a speed of 1 m/s), (B1, with a load of 20 N), (C1, with a temperature of 40 °C), (D1, with a sliding distance of 1.5 km), and (E2, with a filler content of 20 wt.% SiC). Temperature and wear resistance were inversely proportional, with an increase in one leading to a decrease in the other. However, a filler content of 20 wt.% was observed to result in significantly lower wear rates compared to the other configurations. Results on the response for means are presented in

Table 5. Wear response for average values of each parameter.

Level	A	B	C	D	E
1	311.0	306.0	278.5	348	375.8
2	341.0	338.8	349.5	358	349
3	381.3	373.3	382.3	362.5	353.3
4	400	415.3	423	364.8	355.5
Delta	89	109.3	144.5	16.8	26.8
Rank	3	2	1	5	4

.

3.5.2. Analysis of Variance (ANOVA)

ANOVA analysis was performed at a confidence level of 95% to calculate the influence of individual parameters on the wear rate. Individual factor significance was calculated using p-values and F-values. Less than 0.05% of p-values represent the better significance of the parameters.

Table 6. ANOVA for wear rate.

Source	DF	SS	MS	F Value	p-Value	% Contribution
A	1	18,880.5	18,880.5	65.72	0.000	30.36
B	1	26,245	26,245	91.35	0.000	26.30
C	1	43,477	43,477	151.33	0.000	36.88
D	1	599.5	599.5	2.09	0.16	2.700
E	1	655.5	655.5	2.28	0.159	1.706
Error	10	2823	287.3			2.054

describes the p-values of all five variables, which are less than 0.05% and significantly contributed to the wear performance of the material. Individual contributions to the specific factors and parameters were also reported. Temperature contributes 36.88%, followed by sliding speed, applied load, sliding distance, and temperature contributing 30.36%, 26.30%, 2.70%, and 1.706%, respectively.

3.5.3. Predictive Equation for Wear Estimation

Input parameters and response relationships were expressed by the regression Equation (4).

Wear Rate = 28.4 + 30.72 A + 1.811 B + 2.331 C + 3.65 D − 1.145 E

(4)

Positive and negative coefficients represent gain and loss in wear rates, respectively. Moreover, the coefficient of determination (R²) values are close, which means the integration of the derived equation, and undergoes the 95% accuracy level.

3.5.4. Confirmation Experiment

Confirming the experimental optimized results is a stage to authenticate the derived results. Data were analyzed using Minitab optimization represents the optimum parameters of A₁B₁C₁D₁E_2, and the results were reported in

Table 7. Confirmation Results.

Level	Parameters (Initial)	Parameters (Optimal)
		Predicted	Experimental	Error
	A1B1C1D1E1	A1B1C1D1E1	A1B1C1D1E2
Wear	186	178	174	2.24
SN ratio	−44.87	−44.45	−43.95

. It was also observed that the error rate associated with the experiment is 2.24% which denoted the model has better reliability by up to 95% during the development of the hybrid composites.

Further experiments were conducted to investigate the effect of pin temperature on the wear rate of the proposed composites, as represented in Figure 12. Results depict that increasing temperature gradually accelerates the wear rate due to the internal deformation of the fillers resulting in the failure of the proposed composites.

3.5.5. Percentage Errors in Experimental and Taguchi Approach

Table 8. Error percentages in the Taguchi and predicted model.

Test Run	Wear Results (Micron) Experiment and Predicted		Percentage Error in Wear Results
	Experiment	Taguchi	Experiment	Taguchi
1	186	191	10.2921	3.053878
2	273	278	9.6885	2.494022
3	349	354	10.32361	3.384677
4	436	441	9.91254	−1.24437
5	281	286	5.27093	−2.91348
6	243	248	−0.137161	2.576
7	401	406	−9.93195	0.340658
8	439	444	−1.61118	−1.1356
9	350	355	−9.28481	1.101194
10	448	453	−5.14507	0.97358
11	313	318	−11.7797	−0.89692
12	414	419	−3.86821	−0.58034
13	407	412	8.884387	−0.12203
14	391	396	10.48158	3.177678
15	430	435	3.405672	0.02665
16	372	377	−3.5385	−0.42828

illustrates the percentage of wear rate error obtained through both experimental and predicted models. The optimal wear rate for the respective error percentage was analyzed for its reliability calculations. It was observed that the wear rate associated with the wear optimization studies was 2.24%, and it effectively tolerates the wear rates to achieve the highest performance of the proposed samples. The maximum accuracy is contingent upon the error percentage derived from the results and, in this case, the predicted model provides up to 97% accuracy. Additionally, Figure 13 and Figure 14 depict graphical representations of the compared wear rates and respective error percentages.

3.5.6. Worn Surface Morphology

To understand better the tribological behavior, Figure 15 presents the cross-section of the predicted optimum condition (A₁B₁C₁D₁E₂).

A top layer can be identified at the cross-section, which is a mechanically mixed layer (MML). The formation of this layer is a result of the compression of wear debris, which can be composed by the extrusion of second phases, SiC, and graphite. The continuity of contact stresses led to cracks formation [40].

Figure 15a shows the top surface after the wear process for the same material condition. Figure 15b presents the aspect of the worn surface where micro-cracks formed when the composite is subjected to contact stresses. The eggshell effect can happen, i.e., the level of deformation imposed on the original surface was sufficient to weaken the support given to this top layer [41]. A zoom of the worn surface in Figure 15c reveals the wear debris. The compression of them is a result of the plastic deformation imposed by the contact. This Figure presents many aspects and characteristics of severe plastic deformation. Finally, Figure 15d shows the element of the MML. It is clear its distinctive aspect, confirming the observed in Figure 15a.

4. Conclusions

In order to improve mechanical properties of LM26 alloy compared, five hybrid LM26 composites with SiC contents from 0 to 30% wt.% were prepared. LM26 alloy composites reinforced with 20 wt.% Silicon Carbide (SiC) was identified to display the best mechanical properties.

To enhance the tribological behavior of composites, Ni-coated graphite (Ni-Gr) was added from 1 wt.% to 3% wt.%, and an optimum content of 2 wt.% was found to maintain the mechanical properties at the high-level.

Using experimental and Taguchi analysis, the composites were tested for wear resistance. A combination between operational variables and filler content resulted in a best wear resistance with accuracy up to 95% was A₁B₁C₁D₁E₂ (A₁: 1 m/s, B₁: 20 N, C₁: 40 °C, D₁: 1.5 km, and E₂: 20 wt.% SiC).

Analyzing the worn surfaces, a mechanically mixed layer (MML) was formed, from the extrusion of secondary phases. The imposed deformation was enough to promote cracks along with the MML layer.