Synthesis and tribological investigation of Al-SiC based nano hybrid composite

Alexandria Engineering Journal (2017) xxx, xxx–xxx

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Alexandria University

Alexandria Engineering Journal www.elsevier.com/locate/aej www.sciencedirect.com

ORIGINAL ARTICLE

Synthesis and tribological investigation of Al-SiC based nano hybrid composite Navdeep Singh a, Mir Irfan Ul Haq a,*, Ankush Raina a, Ankush Anand a, Vinay Kumar b, Sanjay Mohan Sharma a a b

Department of Mechanical Engineering, Shri Mata Vaishno Devi University, Katra, Jammu, India Department of Physics, Shri Mata Vaishno Devi University, Katra, Jammu, India

Received 30 December 2016; revised 29 April 2017; accepted 7 May 2017

KEYWORDS Aluminum; Tribology; Combustion synthesis

Abstract In this study, a novel self lubricating nano-composite Al-SiC-nAl2O3-WS2 has been synthesized via powder metallurgy method. Nano-Al2O3 has been prepared via combustion synthesis. Three different compositions by varying the amount of solid lubricant, WS2 (0, 5, 9) wt.% were synthesized and analyzed. The density measurements of composites were carried out by using Archimedes Principle. The micro hardness value of every composition was obtained by using micro hardness tester. The tribological properties were investigated under dry and unidirectional sliding conditions on a pin on disk tribometer. Taguchi L9 orthogonal array was used to study the effects of various parameters like load, content, speed and sliding distance on wear and frictional behavior of the composites. Analysis of variance (ANOVA) was used to investigate the percentage contribution of various parameters on the wear and friction behavior. It was observed that composite with 5 wt.% of WS2 exhibited lower friction and wear. SEM images obtained therein revealed that ploughing and abrasion are the two dominant mechanisms of wear. Ó 2017 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction Aluminum based composites have continued to be important materials for aerospace and automotive applications due to their low strength to weight ratio, good corrosion resistance and high thermal and electrical conductivity. However, most recently the nano-composite materials have emerged as suitable alternatives to overcome limitations of micro-composites and monolithics, while posing preparation challenges related * Corresponding author. E-mail address: [email protected] (I.U.H. Mir). Peer review under responsibility of Faculty of Engineering, Alexandria University.

to the control of elemental composition and stoichiometry in the nanocluster phase. Nanocomposites offer better mechanical, thermal and tribological properties over the microcomposites. Recent researches have also found that nanosized reinforcement particles increase strength, ductility and toughness [1–4]. Casting methods often lead to segregation and non uniform distribution of reinforcements [1,5]. The main challenge faced by the researchers in this technique is to obtain a homogeneous distribution of the reinforcement in the metal matrix [6,7]. The use of powder metallurgy can obviate this trouble which can produce metal matrix composites in the whole range of matrix reinforcement compositions without the segregation phenomena typical of the casting pro-

http://dx.doi.org/10.1016/j.aej.2017.05.008 1110-0168 Ó 2017 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Please cite this article in press as: N. Singh et al., Synthesis and tribological investigation of Al-SiC based nano hybrid composite, Alexandria Eng. J. (2017), http://dx. doi.org/10.1016/j.aej.2017.05.008

2

N. Singh et al. Table 1

The composition variation of the composites.

Aluminum (wt.%)

SiC (wt.%)

n-Al2O3 (wt.%)

WS2 (wt.%)

Balance Balance Balance

10 10 10

2 2 2

0 5 9

cess [5,6]. Ramachandra et al. [7] studied the hardness and wear resistance of zirconium dioxide nano particle reinforced aluminum nano composites wherein zirconium dioxide (nZrO2) nano particles were produced by solution combustion method. Mahboob et al. [8] synthesized Al-Al2O3 NanoComposite by mechanical alloying and evaluated the effect of ball milling time on the microstructure and mechanical properties. Kanthavel et al. [9] studied the tribological properties on Al/Al2O3/MoS2 hybrid composite processed by powder metallurgy. Dass et al. studied the influence of nano particulates of SiC, Al2O3, and ZnO on the mechanical and tribological performance of epoxy-based nanocomposites [10]. Prasad et al. have opined that the solid lubricating properties of WS2 are far superior than graphite [11]. Riyadh et al. studied the tribological properties of WS2 nanoparticles lubricants on aluminum-silicon alloy and carbon steels wherein the authors have concluded that an optimal content of WS2 nanoparticles can be used as an anti wear additive for reducing wear and the addition of nanoparticles on metal surfaces prevents the direct contact between the surfaces during mating [12]. A significant increase in the wear resistance and micro hardness has been reported by Zarghani et al. in the nano Al2O3 reinforced aluminum composite produced via casting stir process [13]. The present study deals with the tribological investigation of AlSiC based nano hybrid composite produced via powder metallurgy technique. Al2O3 nanoparticles synthesized via combustion synthesis were added as a reinforcement. In order to form a self lubricating composite, WS2 was added as a solid lubricant. 2. Experimental details 2.1. Material selection In this study, the Al-SiC-nAl2O3 is considered as the base material. Pure aluminum (supplied by HIMEDIA) having an average particle size of 250 lm, Tungsten disulfide (WS2) and

Figure 1

silicon carbide (SiC) of size 50 lm were used in composite preparation. The average size of tungsten disulfide was 15 lm and was procured from Lotus Enterprises, Pune, India. Nano alumina was prepared by solution combustion synthesis process. Calculated amount of pure aluminum, silicon carbide, nano alumina and tungsten disulfide were put into the mortar pestle to carry out the mixing process. The quantity of nano alumina and Silicon carbide were kept constant (2 wt.%) and (10 wt.%) respectively. Tungsten disulfide which was used as a solid lubricant was varied (0, 5, 9) % by weight. Zinc stearate was also added (0.8% by weight) as a binder. Table 1 gives the detailed compositions of the various constituent elements. 2.2. Combustion synthesis Combustion synthesis method was used for the synthesis of nano-Al2O3. The method is used because it provides a more efficient way to produce refractory and hard materials [14]. Chemicals used for the preparation were High-purity aluminum nitrate nanohydrate [Al(NO3)3
9H2O], and urea (H2NCONH2) which were procured from HIMEDIA. The chemical reaction is represented in Eq. (1). The reagents were weighed in the molar ratio of 2:5. The oxidizer to fuel ratio was kept unity for complete combustion because maximum heat is produced at this ratio [15]. 2AlðNO3 Þ3
9H2 O þ 5CH4 N2 O ! Al2 O3 þ 28H2 O þ 5CO2 þ NO2

ð1Þ

After thorough mixing, the gel formed was kept in a preheated muffle furnace kept at a temperature of 500 °C (Fig. 1a) which resulted in a rapid dehydration with the evolution of the large amount of gas yielding voluminous white product. The powder thus produced was nano alumina (n-Al2O3) (Fig. 1b).

Table 2

L9 orthogonal array factors and levels.

Factors

Level 1

Level 2

Level 3

Composition (wt.%) Load (N) Speed (rpm) Sliding distance (m)

0 5 150 1000

5 10 300 2000

9 15 450 3000

(a) Combustion process in a muffle furnace (b) nano-alumina powder produced.

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Synthesis and tribological investigation of Al-SiC

3

Experimental layout of L9 orthogonal array.

Table 3

Experiment number

1 2 3 4 5 6 7 8 9

Input parameters Content WS2 (%)

Load (N)

Speed (rpm)

Sliding distance (m)

0 0 0 5 5 5 9 9 9

5 10 15 5 10 15 5 10 15

150 300 450 300 450 150 450 150 300

1000 2000 3000 3000 1000 2000 2000 3000 1000

34

2.9

33 2.8 2.7

31

Density (g/cm3)

Vicker's Hardness (H.V)

32

30 29 28

2.6 2.5 2.4

27 2.3

26 2.2

25 20

40

20

60

Solid Lubricant Content (wt. %)

Figure 3 Figure 2

40

60

Solid Lubricant Content (wt. %)

Variation of density with solid lubricant content.

Variation of hardness versus wt.% WS2 content. 0.07 0.06

2.3. Preparation of hybrid composite

0.05

2.4. Density measurement The density of the hybrid composite was measured by the Archimedes principle. A sample of each composition of the composite was used in the process. The mass of each sample was measured in the air and then using a setup mass was measured in water. Then density of the composite was calculated by the formula:

Mean

In order to prepare the composite, the reinforcements were firstly mixed in a rotary double cone mixer. The process was carried out for 40 min at 100 rpm in order to ensure the proper mixing. After the mixing process, the green compacts of the different compositions were prepared by uni-axial compaction of the weighed powder samples on a Universal Testing Machine. A die of high speed steel having an internal diameter of 17 mm was used in the compaction process. The compaction pressure of 320 MPa was applied and the samples were compacted in the form of tablets having 17 mm diameter. The green compacts produced therein were sintered in a muffle furnace at 600 °C for 1 h.

0.04 0.03 0.02 0.01 0.00 0

5

9

Concentration

Figure 4

q¼

Mean plot of wear (g) versus content.

ma ma  mw

where q = Density ma = mass of sample in air, mw = mass of sample in water.

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4

N. Singh et al. for the hardness value at five different locations to obtain an average value of hardness.

0.06 0.05

2.6. Wear and friction testing

Mean

0.04 0.03 0.02 0.01 0.00 5

10

15

Load

Figure 5

Mean plot of wear (g) versus load.

0.10

To investigate the coefficient of friction of the hybrid composite, wear and friction test was performed. IEICOS wear and friction testing machine with unidirectional sliding having a pin on disk configuration was used to perform the tests. 58HRC EN31 steel disk was used as the counterface disk. Three samples of each composition were tested at different speed (rpm), load and sliding distance in order to ensure repeatability. The samples were machined and polished by using the emery papers of different grades in order to ensure the surface roughness of 0.06 ± 0.001 lm. The value of the shear force was noted after every 100 revolutions. The value of coefficient of friction was calculated from the shear force value.

Mean

0.08 0.06

3. Optimization technique

0.04

3.1. Taguchi design

0.02 0.00 150

300

450

Speed

Figure 6

Mean plot of wear (g) versus speed.

0.07 0.06

Mean

0.05 0.04 0.03 0.02 0.01

Taguchi method, an efficient and systematic tool in parameter design was used to carry out the experimentation. The methodology is of great help in cases when the design parameters are qualitative and discrete [16]. Taguchi designs try to identify controllable factors (control factors) that minimize the effect of the noise factors. Apart from finding out the significant factors, the tool helps a great deal in reducing the time and cost associated with the experiment when fractionated designs are used. The most commonly used types of performance characteristics for the analysis of the S/N ratio include, the lower the better, the nominal the better, and the higher the better [17]. In our work, Taguchi lower the better type was used to calculate the process parameters. The four process parameters which affect the wear rate of a composite include load, content, sliding speed and sliding distance. L9 orthogonal array was used to design the experiments. Table 2 shows different L9 orthogonal array factors and its levels. The sequence of the experiments to be carried out is presented in Table 3.

0.00 1000

2000

3000

3.2. ANOVA method

Sliding Distance

Figure 7

Mean plot of wear (g) versus sliding distance.

2.5. Hardness measurement The Vickers Hardness value for each composition was measured as per ASTM E-384 which gives an allowable range of loads for testing with a diamond indenter; the resulting indentation is measured and converted to a hardness value. The actual indenters used were Vickers (a square base diamond pyramid with an apical angle of 136°) or Knoop (a narrow rhombus shaped indenter). Prior to the test the surfaces of the test samples were polished by smooth emery paper. The indent formed on the surface was measured and the value of the hardness was calculated. Each specimen was investigated

In order to optimize the process parameters, the numerical optimization technique has been used. Analysis of variance (ANOVA) was used to find out the significance of input parameters. MINI TAB 15.0 statistical software was used to develop the design matrix. In order to determine the optimal values of wear rate and relative importance of parameters affecting wear rate of all the compositions, ANOVA was performed using the mean values. 4. Results and discussion 4.1. Mechanical properties In this study the micro hardness and the density measurements of the synthesized composites has been measured. The strength of the sintered composites has been gauged by means of hard-

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Synthesis and tribological investigation of Al-SiC

5

Concentration

70

Load

60

Mean of SN ratios

50 40 30 0

5

9

5

10

Speed

70

15

Sliding Distance

60 50 40 30 150

300

450

1000

2000

3000

Signal-to-noise: Smaller is better Figure 8

Mean plot for SN ratio for wear.

ANOVA of S/N ratios for wear.

Table 4

Degree of freedom

Sum of square

Mean square

F

% Contribution

Content Load Speed Sliding Distance Error Total (Error)

2 2 2 2 0 8 4

7411 963 11,188 82,399 0 101,961 8374

11,525 1239 15,455 41,199

5.50 0.59 7.38 19.67

7.26 0.94 10.97 80.81

2093.5

0.75

1.0

0.74

0.9

0.73

0.8

Mean

Mean

Source

0.72 0.71

0.7 0.6

0.70

0.5 0

5

9

5

10

Figure 9

Mean plot of COF versus content.

ness values and to rule out porosity in the samples density calculations have been performed. 4.1.1. Hardness test Hardness of the composite was measured by Vickers hardness tester on the polished samples. The indent formed on the surface was measured and the value of the hardness was calculated. The hardness value was measured at 200 g load. Fig. 2 shows the variation of the hardness with the increase in the content of the WS2 solid lubricant. It was found that hardness

15

Load

Concentration

Figure 10

Mean plot of COF versus load.

increased with increase in wt.% content of WS2. The composition with 9 wt.% WS2 exhibited highest hardness 31.93 HV. The increase in the hardness is in conformance to Sidhu et al. [18]. 4.1.2. Density measurement Density of the composite was measured using Archimedes principle and it was found to be increasing with increase in the percentage of solid lubricant WS2. This increase in the density can be attributed to the filling of the pores present in the

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6

N. Singh et al. Table 5

ANOVA of S/N ratios for COF.

Source

Degree of freedom

Sum of square

Mean square

F

% Contribution

Content Load Speed Sliding Distance Error Total (Error)

2 2 2 2 0 8 4

114.406 49.648 20.964 34.174 0 219.192 55.138

24.094 14.920 12.215 17.087

1.74 1.08 0.88 1.23

52.19 22.65 9.56 15.59

13.784

0.90

composite. Three samples from each composition were used to measure the density and their average value was taken as the measured value. Fig. 3 shows the variation of the density with the increase in the percentage of solid lubricant (WS2).

0.85

Mean

0.80 0.75 0.70

4.2. Investigation of tribological properties

0.65 0.60

4.2.1. Influence of input parameters on the wear

0.55 150

300

To analyze the effects of different parameters like content, load, speed, sliding distance, MINITAB 15.0 was used and Taguchi design was applied. The S/N ratios are calculated as given in Eq. (2). Taguchi method is used to analyze the result of response of parameters for smaller is better (SB) criteria. " # n 1X 2 SB : g ¼ 10 log yi ð2Þ n i¼1

450

Speed

Figure 11

Mean plot of COF versus speed (rpm).

0.9

where g denotes the S/N ratios calculated from observed values, yi represents the experimentally observed value of the ith experiment and n = 3 is the repeated number of each experiment in L9 Orthogonal Array. The mean plots indicated in Figs. 4–8 indicates that wear at 5% content of WS2, 10 N load, 300 rpm speed and 1000 m sliding distance respectively gives the best results on input parameters. To know the statistical validity of the developed experimental setup on ANOVA analysis (Table 4) is performed. The significance of the model and percentage contribution of sliding distance is about 80.81% and it is revealed that the impact

Mean

0.8

0.7

0.6

0.5 1000

2000

3000

Sliding Distance

Figure 12

Mean plot of COF versus sliding distance.

Concentration

6.0

Load

Mean of SN ratios

4.5 3.0 1.5 0.0 0

5

9

5

Speed

6.0

10

15

Sliding Distance

4.5 3.0 1.5 0.0 150

300

450

1000

2000

3000

Signal-to-noise: Smaller is better Figure 13

Mean plot for SN ratio for COF.

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Synthesis and tribological investigation of Al-SiC

80.81%

Concentraon

7

Sliding Direcon Shallow Grooves

Load

7.26% 0.94%

Speed Sliding Distance

10.97% Figure 14

Contribution (wt.%) of parameters on wear.

Delaminaon

Micro Cracks

15.59%

(a)

Concentraon

9.56%

Load

Wear Debris

Sliding Direcon

Speed Sliding Distance

22.65% Figure 15

52.19% Contribution (wt.%) of parameters on COF.

Ploughing of sliding distance on wear loss is high. The parameters such as Load, Speed and Content has very little effect on wear loss.

(b)

4.2.2. Influence of input parameters on coefficient of friction To evaluate the effect of the load, speed, content and sliding distance mean plot for coefficient of friction was plotted. Mean plots of Figs. 9–13 indicate that COF at 5% content, 15 N load, 450 rpm speed and 2000 m sliding distance is the optimal condition. The statistical validity of the developed experimental setup on ANOVA analysis (Table 5) is performed. The ANOVA analysis revealed that the% age of WS2 content on the COF is the highest (52.19%). The parameters such as Speed, sliding distance and load has very little effect on COF.

Sliding Direcon


Delaminaon Ploughing

4.2.3. Percentage contribution The percentage contribution of the input parameters on the wear and COF is shown in Figs. 14 and 15 wherein it is evident that sliding distance is the most contributing factor on the wear characteristics and content of the solid lubricant plays the most important role in the COF of the developed composite.

(c) Figure 16 SEM images of worn surface: (a) worn surface of composite containing WS2 (0 wt.%), (b) worn surface of composite containing WS2 (5 wt.%), (c) worn surface of composite containing WS2 (9 wt.%).

4.3. Wear mechanism After performing the wear tests, the worn out surfaces of the samples were investigated using SEM micrographs shown in Fig. 16. Fig. 16a shows shallow grooves on the worn surface, small pits and micro cracks can be seen on the worn surface. Delamination and stick-slip behavior can also be seen clearly. The presence of nano alumina has led to the decreased wear. Fig. 16b shows smooth worn surface and even less grooves. Ploughing seems to be the dominant wear mechanism. This is due to layer formed by the solid lubricant WS2 which reduces the coefficient of friction and wear to a great extent.

The addition of ceramic reinforcement phase SiC and nAl2O3 enhances the overall load bearing capacity of the aluminum composite however the relatively softer WS2 phase improves the friction characteristics. Fig. 16c shows somewhat increased wear as compared to Fig. 16b. A mix of ploughing and delamination mechanisms seem to be the dominant wear mechanisms and an increased wear is evident from the image. Moreover micro crack formation can also be seen. The increased wear may be due to the fact that applying more than specific percentage of solid lubricant deteriorates the fracture toughness thereby becoming easy for the composite to fracture during the wear process [19,20].

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8 5. Conclusion The mechanical characterization of Al-SiC-n-Al2O3-WS2 hybrid composites brought out the following conclusions: 1. As the percentage of WS2 increases, the density of the composite also increased with 9 wt.% WS2 having the maximum density of 2.757 g/cm3. This is due to the fact that WS2 filled the gaps in the composite thereby increasing the density. 2. Similarly, the increase in percentage of WS2 solid lubricant increased the hardness of the composite. The hardness of the composite having 0 wt.% WS2 was 29.07 HV and the hardness of the composite having 9 wt.% WS2 was 31.93 HV. These results are in consistence with Sidhu et al. [18]. 3. Taguchi’s method of experimental design is used to find the optimum conditions for dry sliding wear of WS2 filled AlSiC-n-Al2O3 hybrid composite. Following conclusions are drawn from the study. 4. Using Taguchi approach, it is concluded that the wear at 5% content of WS2, 10 N load, 300 rpm speed and 1000 m sliding distance is the least. 5. By performing ANOVA analysis, it is concluded that the impact of sliding distance on wear loss is high (80.81%) followed by speed, content and load. 6. Similarly, Taguchi approach also showed that coefficient of friction at 5% content, 15 N load, 450 rpm speed, 2000 m sliding distance gives the best results. 7. The impact of input parameters was investigated by ANOVA analysis. It showed that the impact of WS2 content on COF is high (52.19%). The parameters such as speed, sliding distance and load has very little effect on COF. 8. SEM micrographs showed small pits and worn surface on the composite containing 0 wt.% WS2. Composites with optimum content of WS2 (5%) had low wear and abrasion. Also their coefficient of friction was low.

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