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Abstract

The aim of present paper is to fabricate the Polyamide 6/Carbon nanotubes/Clay (PA6/CNT/Clay) nanocomposites by using 3D printing and investigate the electrical conductivity, thermal stability, tensile strength and elongation of printed samples. Taguchi method and grey relational grade analysis are applied to find the optimum values of CNT content, clay content, feed rate and nozzle temperature. Analysis of the printed samples was performed by SEM, TGA, DSC and four-probe tests. Investigation of results declared that by adding the CNT and clay into the PA6, the thermal stability of PA6/CNT/Clay nanocomposites enhanced. The electrical conductivity of the PA6/CNT/Clay nanocomposite exhibited significant improvement by incorporating 1 wt% CNTs and 2 wt% clay nanoparticles. Taguchi method results also showed that the impact of CNT and clay contents on the tensile strength and elongation is greater than the other parameters. The results of optimization by grey relational grade indicated that the tensile strength and elongation of PA6/CNT/Clay nanocomposite can be improved by CNT content of 1 wt%, clay content of 2 wt%, feed rate of 30 mm/s, and nozzle temperature of 270°C.

Keywords

3D printing PA6/CNT/clay composite thermal stability electrical conductivity tensile strength

Introduction

Polyamide 6 (PA6), also known as Nylon 6, has different applications across many industries due to its good mechanical properties, chemical resistance, and wear resistance.^1,2 PA6 is widely used in automotive parts, electrical components, industrial machinery, consumer goods, and textiles.^3,4 It is a semi-crystalline polymer composed of an amorphous phase and three crystalline phases: α, γ, and β, with the β-phase acting as an intermediate between the α and γ forms.⁵ The formation of either the α or γ structure is primarily influenced by the arrangement of alkyl chains during crystallization and the hydrogen bond length.⁶ The different structures of PA6 significantly affect its strength and stiffness. As a result, the production process can be optimized to achieve an optimal combination of stiffness and flexibility in the final material.² Recent developments have highlighted the use of strengthening additives like carbon nanotubes, graphene, glass fibers, clay, etc..^7–10 These additives greatly improve PA6’s properties, providing higher stiffness and strength, better thermal stability, and greater electrical conductivity.^11,12 Among nanofillers, carbon nanotubes (CNTs) is widely used in polymer nanocomposites due to its extraordinary properties.^11–13 Carbon nanotubes has attracted great attention in different technological fields like electronics, energy storage, conversion, sensors, biomedicine, and composite materials^15–18. Thermal, mechanical and electrical properties of polymer composites can be also enhanced by adding carbon nanotubes. Mei et al.¹⁸ reported that incorporation of CNTs into PA6 improved the Young’s modulus, tensile strength and electrical conductivity. Chen et al.¹⁹ stated that the thermal conductivity and wear resistance of PA6 improved by addition of only 0.2 wt% CNTs. Luna et al.²⁰ observed that the tensile strength, impact strength, electrical conductivity, and crystallization temperature of PA6/ABS/CNT nanocomposite enhanced with addition of 1 wt% CNTs. Yu et al.²¹ reported that the PA6/CNT nanocomposites exhibited higher tensile strength, Young’s modulus and thermal conductivity compared to the neat PA6. Despite the many benefits of CNTs, the cost of these nanoparticles is high and they have environmental and health concerns due to their toxicity. Therefore, excessive use of CNTs cannot be economically justified. In addition, there are some reports that the addition of CNTs has reduced some mechanical properties of PA6.^10,22 Thus, although carbon nanotubes (CNTs) offer many benefits, incorporating these nanoparticles does not enhance every mechanical property of polymer nanocomposites. Another excellent additive used as a nucleating agent in polymers is clay nanoparticles. Clay nanoparticles have great potential for industrial applications due to their low price, wide availability, easy processability, and good performance.^23,24 Shen et al.²⁵ found that addition of 2 wt% clay nanoparticles into PA6 increased flexural modulus and strength of pA6/Clay nanocomposites. AbdulAmeer et al.²⁶ reported that by adding 3 wt% CNT into polypropylene (PP), the tensile and impact strength increased without sacrificing thermal stability. AbdulAmeer et al.²⁷ also observed a substantial improvement in the elastic modulus and flexural strength of the PP/Clay nanocomposite by adding 4 wt% nanoclay. Shanmugam et al.²⁸ stated that the composite containing 5 wt% amino clay demonstrated a significant improvement in tensile strength when compared with the composite containing 3 wt% amino clay. Campos et al.²⁹ reported that the clay nanoparticles increased thermal stability of PA6 but decreased its tensile strength. Hosseini et al.³⁰ also found that the toughness and elongation of PA6/Clay nanocomposite reduced by addition of clay nanoparticles.

Previous studies indicate that single-filler systems typically fail to enhance all mechanical properties of polymer nanocomposites. Consequently, researchers have suggested combining two or more distinct fillers to achieve comprehensive improvements. Pisani et al.³¹ found that by incorporation of graphene and carbon nanotubes into PA6, the Young’s modulus of PA6 polymer improved. Farhadpour et al.³² reported that the electrical conductivity of PA6 improved by addition of both carbon nanotubes (CNTs) and conductive carbon black (CCB). Mousavi et al.³³ incorporated thermoplastic polyurethane (TPU) and carbon nanotubes (CNTs) into PA6 to improve impact resistance and damping performance. Batakliev et al.³⁴ observed that incorporation of both carbon nanotubes (CNT) and graphene (GPN) in the PLA/GPN/CNT composite, indicated better hardness and elastic modulus compared to the PLA/CNT composites loaded with a single carbon nanofiller. Kumar et al.³⁵ reported that by addition of 1.5 wt% carbon nanotubes and 0.5 wt% graphene into PLA, the tensile strength, elastic modulus, yield strength and impact strength were greatly enhanced. Previous findings confirm that combining multiple fillers yields superior mechanical performance in polymer composites. Accordingly, this investigation employs two common reinforcing agents - carbon nanotubes and clay nanoparticles.

The adoption of 3D printing technology for polymer nanocomposite fabrication has grown significantly in recent years. However, identifying optimal printing conditions is crucial for obtaining superior mechanical characteristics. Taher et al.³⁶ determined the optimal parameters for TiO₂ content, nozzle temperature, and printing speed to enhance both the impact strength and elastic modulus of the PP/EPDM/TiO₂ nanocomposite fabricatd by fused deposition modeling (FDM). Arigbabowo et al.³⁷ observed that addition of graphene into PA6 resulted in an improvement in tensile modulus, flexural modulus, thermal stability and volume conductivity for 3D printed samples. Afshari et al.³⁸ stated that the best conditions for increasing the hardness and tensile strength of PP/GPN nanocomposite was obtained at graphene content of 1.5 wt%. Hardani et al.³⁹ found that a rise of print speed declined the impact and tensile strength, but a rise of nozzle temperature enhanced the impact and tensile strength. It was also reported by Hardani et al.⁴⁰ that the elastic modulus and bending strength of PLA/CNT nanocomposite were enhanced by nozzle temperature of 210°C, printing speed of 20 mm/s, and CNT content of 2.9 wt%. Xu et al.⁴¹ observed that the elongation and strength of PP/EPDM/TiO₂ nanocomposite have increased with a 28 mm/s print speed, 2.5 wt% TiO₂ and 227°C nozzle temperature. Benfriha et al.⁴² reported that the parameters of 3D printing have an important effect on the cooling time of printed parts and consequently affects the adhesive strength of adjacent filaments. Vanaei et al.⁴³ found that the impact of extruder temperature on thermal and mechanical properties of PLA printed by FDM process is higher than other process parameters. The impact of FDM parameters on the mechanical behavior of polymer nanocomposite was also investigated by other researchers.^44–48

Recent literature reviews reveal growing interest in ternary nanocomposites for enhanced mechanical performance. However, PA6/CNT/Clay nanocomposites remain unexplored, with no prior investigation of their thermal, electrical, and mechanical characteristics. This study addresses this gap by developing such nanocomposites via an innovative 3D printing approach. The research employs the Taguchi method to efficiently examine the influence of clay content, CNT concentration, feed rate, and nozzle temperature on the tensile strength, elongation, melting temperature, crystallization temperature and electrical conductivity of the nanocomposite with a smaller number of experiments. Furthermore, this work introduces gray relational analysis to optimize processing parameters for concurrent improvement of tensile strength and elongation.

Materials and methods

Materials

The study utilized multi-walled carbon nanotubes (≥90% purity) from INP Corporation, featuring average dimensions of 1.5 μm in length and 9.5 nm in diameter, along with a specific surface area ranging from 250 to 300 m²/g. The matrix material consisted of commercial PA6 powder (SINTERLINE XP 1537/A, Solvay SA Group), characterized by near-spherical particles averaging 50 µm in diameter. The organically-modified montmorillonite (OMMT) nanoclay used in this study was obtained from Southern Clay Products Inc., characterized by an interlayer spacing (d-spacing) of 15 Å and a specific gravity of 1.66 g/cm³.

Fused Deposition Modeling (FDM)

This study employed fused deposition modeling (FDM) to fabricate PA6/CNT/Clay ternary nanocomposites. The PA6/CNT/Clay powder nanocompositions were first dried in an oven at 80°C. Then, a mechanical mixer was employed to blend PA6 powders with Clay and CNT nanoparticles at different loadings. Composite filaments (0.75 mm radius) were produced using a Filabot EX2 extruder (USA) operating at 210°C with a screw rotation speed of 3 rpm. The quality of the produced filaments was visually inspected to ensure the presence of holes or porosity. The FDM process was executed using a Wanhao D12-230 3D printer, with systematic variation of nozzle temperature and feed rate parameters. Constant process parameters are detailed in Table 1.

Table 1.

Values of constant parameters of FDM.

Parameters	Air gap	Bed temperature	Nozzle diameter	Layer thickness	Built orientation
Values	0.04 mm	100°C	0.4 mm	0.2 mm	0°

Taguchi Design

To optimize the experimental process, this study employed the Taguchi design approach, which significantly reduces the required number of tests. The experimental layout was generated using Minitab® 17 software, with four input parameters of clay content, CNT content, nozzle temperature, and feed rate. The complete design matrix is provided in Table 2.

Table 2.

Design matrix based on L9 orthogonal array.

Run	1	2	3	4	5	6	7	8	9
Clay (wt%)	0	0	0	2	2	2	4	4	4
CNT (wt%)	0	1	2	0	1	2	0	1	2
Feed rate (mm/s)	20	30	40	30	40	20	40	20	30
Nozzle temperature (°C)	250	260	270	270	250	260	260	270	250
Elongation (%)	27	46.8	37.8	34.2	30.6	32.4	23.4	36	25.2
Tensile strength (MPa)	53.8	66.9	61.2	75.1	69.4	66	57.7	72.9	63.3

The parameter ranges listed in Table 2 were determined through a review of prior research^12–50 and initial experimental trials. Each parameter is considered at three levels. The output responses focused on tensile strength and elongation. Following Taguchi’s orthogonal array principles, an L9 array was selected for the experimental design. To ensure reliability, each experimental condition was tested with two replicates.

Thermal Tests

The thermal properties of the fabricated samples were evaluated using differential scanning calorimetry (DSC; Netzsch 200 F3 Maia). The analysis was performed under nitrogen atmosphere with a constant heating/cooling rate of 10°C/min, following a three-stage temperature protocol (20°C–220°C) comprising heating, cooling, and reheating cycles. This procedure enabled determination of the melting (T_m) and crystallization (T_c) temperatures. Sample crystallinity (X_c) was subsequently calculated using equation (1).

X_{c} = (\frac{{∆ H}_{m}}{{∆ H}_{L}}) \times 100 %

where,

{∆ H}_{m}

and

{∆ H}_{L}

are the measured melting enthalpy and the enthalpy for a perfect crystal of PA6 (230 J/g), respectively.

Mechanical Tests

Fused deposition modeling (FDM) was employed to manufacture specimens for tensile testing. Tensile specimens were fabricated in compliance with ASTM D-638 standard and evaluated using a Zwick/Roell-Z100 universal testing machine at a constant crosshead speed of 50 mm/min.

Electrical Tests

The electrical resistance of the printed samples was measured using a four-probe electrical conductivity meter (Suragus, Germany). The electrical resistivity of the samples was calculated using the equation ρ = RA/L, where L is the thickness of the sample, A is the area, and R is the resistance measured.⁴⁹ The electrical tests of printed samples were performed at room temperature and 55% relative humidity.

Microstructure Observation

Microstructural characterization was performed using a VEGA-TESCAN-XMU scanning electron microscope. Sample preparation involved cryogenic fracture in liquid nitrogen to expose pristine fracture surfaces, followed by gold coating using an Agar Scientific B7340 sputter coater (UK) to ensure adequate conductivity for SEM imaging.

Results and discussion

Analysis of thermal Properties

The thermal characteristics of the PA6/Clay/CNT nanocomposite were investigated through differential scanning calorimetry (DSC). The results of DSC analysis for PA6/Clay/CNT composite were shown in Figure 1. The values of melting temperature, crystallization temperature and percentage crystallinity of PA6/Clay/CNT composite were obtained from DSC test, as given in Table 3.

Figure 1.

Results of DSC test for PA6/Clay/CNT.

Table 3.

Thermal properties of PA6/Clay/CNT nanocomposite obtained by DSC test.

Thermal properties	PA6 + 0 wt% clay +0 wt% CNT	PA6 + 2 wt% clay +1 wt% CNT	PA6 + 4 wt% clay +2 wt% CNT
Crystallization temperature (°C)	196.4	199.6	202.1
Crystallinity (%)	21.3	24.7	28.7
Melting temperature (°C)	216.5	219.4	223.9

From Table 3, it can be seen that a rise of clay and CNT in the PA6 improved the crystallization and melting temperatures of PA6/Clay/CNT nanocomposite. It should be noted that some of heat is absorbed by clay and CNT nanoparticles, thus the crystallization and melting temperatures of the composite increased by addition of clay and CNT. Therefore, the thermal stability and heat transfer of the PA6/Clay/CNT nanocomposite improved by addition of clay and CNT in PA6. Furthermore, the results of DSC in Table 3 show that the increase of the amount of clay and CNT nanoparticles improved the crystallinity percentage of the composite, because these nanoparticles act as nucleation agents in PA6.

For investigating the thermal properties of PA6/Clay/CNT nanocomposite, the thermogravimetric analysis was conducted in the range of 0 to 600°C, as shown in Figure 2. Figure 2 shows that the thermal stability of PA6 increased by addition of clay and CNT. When the amount of nanoparticles is 0 wt%, the thermal degradation of PA6 starts at 304°C and its mass decreases continuously until 542°C. However, by adding nanoparticles, the decomposition temperature of PA6/Clay/CNT nanocomposite increases to 351°C.

Figure 2.

Thermogravimetric analysis of PA6/Clay/CNT nanocomposite.

The incorporation of nanoparticles in the PA6/Clay/CNT nanocomposite significantly constrains polymer chain mobility, thereby elevating its thermal decomposition temperature.^4–10 Thermal stability was quantitatively assessed through characteristic degradation temperatures (T10%, T50%, T90%) as presented in Table 4. Based on Table 4, the thermal stability of PA6 enhanced by increasing the Clay and CNT contents.

Table 4.

Weight loss temperature at 10, 50 and 90%.

Temperature	PA6 + 0 wt% clay +0 wt% CNT	PA6 + 2 wt% clay +1 wt% CNT	PA6 + 4 wt% clay +2 wt% CNT
T₁₀ (°C)	348	367	386
T₅₀ (°C)	417	440	452
T₉₀ (°C)	469	484	497

Analysis of electrical Properties

Figure 3 displays the volume conductivity of printed nanocomposite samples containing different nanoparticle concentrations. The results indicate that incorporating clay and CNT nanoparticles into PA6 enhances the samples’ conductivity. Specifically, a mixture of 1 wt% CNT and 2 wt% clay increased conductivity to 53 s/cm. However, further increasing the CNT to 2 wt% and clay to 4 wt% led to a decline in conductivity. This initial improvement is attributed to the high conductivity of CNTs, whereas the subsequent reduction occurs due to the insulating nature of clay particles at higher concentrations (4 wt%). Additionally, raising the CNT and clay content to 2 wt% and 4 wt%, respectively, promotes nanoparticle agglomeration, resulting in an uneven surface and microstructural voids, as detailed later. These voids act as insulating regions, further diminishing the volume conductivity of the nanocomposite.

Figure 3.

Volume conductivity of printed samples containing different nanoparticle concentrations.

Microstructure analysis

The microstructure of the printed samples is analyzed to assess the distribution of nanoparticles in the PA6/Clay/CNT nanocomposite and examine the bonding quality between filament layers. Figure 4 displays the fracture surface of tensile specimens with different amounts of clay and CNTs. As seen in Figure 4(a), pure PA6 exhibits a smooth and homogeneous fracture surface. In Figure 4(b), with 2 wt% clay and 1 wt% CNT, the nanoparticles are well-dispersed within the nanocomposite. The interfacial interaction between the nanoparticles and PA6 matrix increased at this condition, leading to an enhancement in the mechanical properties of the PA6/Clay/CNT nanocomposite. The very small size of clay and CNT nanoparticles creates a large interfacial surface area with the polymer, enabling efficient stress transfer from the PA6 matrix to the high-strength nanoparticles, thereby improving the composite’s performance.^25–27 However, when the clay and CNT contents increase to 4 wt% and 2 wt%, nanoparticle agglomeration becomes evident (Figure 4(c)). This uneven dispersion negatively impacts the mechanical performance of the nanocomposite.

Figure 4.

Fracture surface of nanocomposite for (a) Clay = 0 wt%, CNT = 0 wt%, (b) Clay = 2 wt%, CNT = 1 wt%, (c) Clay = 4 wt%, CNT = 2 wt%.

Figure 5 illustrates the influence of feed rate on the microstructure of the PA6/Clay/CNT nanocomposite. As shown in Figure 5(a), at a print speed of 20 mm/s, the bonding between layers is weak due to the formation of voids and cracks in the fracture surface, leading to diminished mechanical properties. However, when the feed rate increases to 30 mm/s (Figure 5(b)), the number of voids and cracks decreases, indicating stronger interlayer adhesion. Conversely, further increasing the feed rate to 40 mm/s (Figure 5(c)) reintroduces voids and cracks, as the slower cooling rate weakens the bond between the printed layers.

Figure 5.

Fracture surface of nanocomposite for feed rate of (a) 20, (b) 30, (c) 40 mm/s.

Figure 6 demonstrates the effect of different nozzle temperatures on the microstructure of printed samples. As evident in Figure 6(a), (a) nozzle temperature of 250°C results in poor interlayer adhesion due to the high concentration of voids and cracks in the fracture surface. This weak bonding is attributed to the higher viscosity of PA6 at this temperature, which hinders effective deposition by reducing filament fluidity and limiting the interpenetration of polymer chains.^10,17–23 When the nozzle temperature is raised to 260°C (Figure 6(b)), the number of voids and cracks diminishes, giving rise to an enhancement of interlayer bonding as the polymer’s viscosity becomes more favorable for deposition. Further increasing the temperature to 270°C (Figure 6(c)) nearly eliminates cracks and voids, significantly improving layer adhesion due to optimal polymer flow and chain inter-diffusion.

Figure 6.

Fracture surface of nanocomposite for nozzle temperature of (a) 250, (b) 260, (c) 270°C.

Taguchi Design analysis

To evaluate how process parameters affect the tensile strength and elongation of fabricated samples, a signal-to-noise ratio (S/N) analysis was employed. The Taguchi experimental design accounts for both disturbing factors (noise variables that affect the process but are impractical to control) and controllable factors (adjustable process parameters). Rather than analyzing raw output responses directly, the Taguchi method utilizes S/N ratios as performance metrics. These ratios are categorized based on optimization objectives: “smaller is better,” “larger is better,” or “nominal is best.” The corresponding S/N ratios for the first two scenarios are computed using Equations (1) and (2), respectively.

\frac{S}{N} = - 10 \log 10 (\frac{1}{n} \sum_{i = 0}^{n} ({y_{i}}^{2}))

(1)

\frac{S}{N} = - 10 \log 10 (\frac{1}{n} \sum_{i = 0}^{n} (\frac{1}{{y_{i}}^{2}}))

(2)

In these equations, n represents the repetition of experimental tests (n = (2) and y_i represents the recorded response for the i^th time. Since the maximum values of tensile strength and elongation are expected, equation (2) is used to obtain the S/N ratio.

The Minitab software was used to determine the S/N ratios and identify the optimal parameter levels for each response, as presented in Table 5. This table also includes the corresponding tensile strength and elongation values. Tables 6 and 7 detail the S/N ratios for various parameter levels affecting tensile strength and elongation, respectively.

Table 5.

S/N ratios for tensile strength and elongation.

Run	1	2	3	4	5	6	7	8	9
Tensile strength (MPa)	53.8	66.9	61.2	75.1	69.4	66	57.7	72.9	63.3
S/N for tensile strength	34.62	36.50	35.74	37.51	36.83	36.39	35.22	37.25	36.03
Elongation (%)	27	46.8	37.8	34.2	30.6	32.4	23.4	36	25.2
S/N for elongation	28.63	33.40	31.55	30.68	29.71	30.21	27.38	31.13	28.03

Table 6.

Results of S/N analysis for tensile strength.

Level	Clay	CNT	Feed rate	Nozzle temperature
1	35.62	35.78	36.09	35.82
2	36.91	36.86	36.68	36.04
3	36.17	36.05	35.93	36.83
Delta	1.29	1.08	0.75	1.01
Rank	1	2	4	3

Table 7.

Results of S/N analysis for elongation.

Level	Clay	CNT	Feed rate	Nozzle temperature
1	31.19	28.90	29.99	28.79
2	30.20	31.42	30.70	30.33
3	28.85	29.93	29.55	31.12
Delta	2.35	2.52	1.15	2.33
Rank	3	1	4	2

The delta values, calculated as the difference between the minimum and maximum S/N ratios, indicate the relative influence of each parameter on the responses. The parameters with higher delta values demonstrate greater impact on a response. The relationship between process parameters and responses is further illustrated in Figure 7, which plots the S/N ratios for both tensile strength and elongation.

Figure 7.

Effect of parameters on (a) tensile strength, (b) elongation.

Analysis of Tables 6 and 7 reveals that clay content exerts the most significant influence on tensile strength, while CNT content predominantly affects elongation in the printed parts. As shown in Figure 7(a), optimal tensile strength occurs at 2 wt% clay and 1 wt% CNT. This enhancement correlates with the SEM observations in Figure 4(b), which demonstrate excellent nanoparticle dispersion within the PA6 matrix at these concentrations. Conversely, higher clay and CNT loading (4 wt% and 2 wt%, respectively) leads to nanoparticle agglomeration, impairing their distribution and consequently reducing tensile strength. This strength reduction may also stem from increased PA6 crystallinity at these higher filler concentrations. While crystallinity improves matrix stiffness, it can occasionally diminish overall specimen strength, as documented in prior studies.^{17–21,25–28}

Figure 7(b) demonstrates that the maximum elongation is achieved with a 0 wt% clay and 1 wt% CNT. The detrimental effect of clay on elongation likely arises from its larger particle size, which creates stress concentration sites within the PA6/Clay/CNT nanocomposite structure. Figure 7(a) and (b) demonstrate that increasing the feed rate to 30 mm/s enhances both tensile strength and elongation in the PA6/Clay/CNT nanocomposite, while further elevation to 40 mm/s leads to deterioration of these mechanical properties. As evidenced by Figure 5(b), the observed improvement at 30 mm/s correlates with enhanced interlayer adhesion and reduced void formation between deposited filaments. These structural imperfections act as stress concentration points, significantly compromising the mechanical performance of material. These findings align with previous studies reported in references [^9,36,50–54], which similarly established the critical relationship between processing parameters, structural integrity, and mechanical properties in polymer nanocomposites.

It can be observed from Figure 7(a) and (b) that an elevation of nozzle temperature to 270°C enhanced the tensile strength and elongation of PA6/Clay/CNT nanocomposite, so that the highest tensile strength and elongation were obtained at nozzle temperature of 270°C. As can be seen from Figure 6(c), the greater adhesion between the printed layers caused by the lower viscosity of the PA6 is responsible for the increased tensile strength and elongation at nozzle temperature of 270°C. The robust bonding between printed layers at this temperature minimizes the formation of cavities and cracks (Figure 6(c)), leading to improved mechanical properties in terms of both tensile strength and elongation. Additionally, as shown in the SEM image in Figure 6(a), defects in the microstructure caused by poor filament layer adhesion significantly degrade these properties at a nozzle temperature of 250°C. It is important to note that insufficient temperature during filament deposition results in weak interlayer bonds, primarily due to inadequate molecular chain fusion between the layers. These findings align well with the observations reported in other studies.^{33–38,50–52}

Grey Relational analysis

To simultaneously improve tensile strength and elongation, determining the ideal processing parameters is crucial. The Taguchi method results were subsequently optimized through grey relational analysis to establish these optimal parameter settings. This approach involves the normalization of S/N values, ensuring they fall within the range of 0 to 1.⁵⁴ The normalization process was carried out using equation (3).⁵⁴

Z_{i j} = \frac{Y_{i j} - \min (Y_{i j})}{\max (Y_{i j}) - \min (Y_{i j})}

(3)

In equation (3), Z_ij denotes the normalized values, which fall within the range of 0 to 1, while Y_ij denotes the outcome of the i_th test for the j_th response.⁵⁴ Table 8 summarizes the normalized signal-to-noise (S/N) values corresponding to each response.

Table 8.

Normalized S/N ratios for tensile strength and elongation.

Run	Tensile strength	Elongation
1	0.0000	0.1538
2	0.6103	1.0000
3	0.3474	0.6154
4	1.0000	0.4615
5	0.7324	0.3077
6	0.5728	0.3846
7	0.1831	0.0000
8	0.8967	0.5385
9	0.4460	0.0769

The gray relational coefficient is calculated using equation (4). This involves converting the normalized values into a deviation sequence (Δ_ij), which is obtained by calculating the difference between the normalized values and the ideal target value (i.e., 1).⁵⁴

∆_{i j} = 1 - Z_{i j}

(4)

Equation (5) is used to compute the gray relational coefficient (GC_ij), which measures the correlation between the ideal and actual test results.⁵⁴

{G C}_{i j} = \frac{∆_{\min} + λ ∆_{\max}}{∆_{i j} + λ ∆_{\max}}

(5)

In equation (5), Δ_min and Δ_max are equal to 0 and 1, respectively. The discrimination coefficient (λ), which varies from 0 to 1, is chosen according to the analysis requirements. In this study, λ was assigned a value of 0.5.⁵⁴ The gray relational coefficient (GC) for each response was then computed using equation (5), as the results were listed in Table 9.

Table 9.

Gray relational and G_i coefficients for each response.

Run	Tensile strength	Elongation	G_i coefficient
1	0.3333	0.3714	0.352381
2	0.5620	1.0000	0.781003
3	0.4338	0.5652	0.499513
4	1.0000	0.4815	0.740741
5	0.6514	0.4194	0.535365
6	0.5392	0.4483	0.493758
7	0.3797	0.3333	0.356506
8	0.8288	0.5200	0.674397
9	0.4744	0.3514	0.412869

Once the gray relational coefficients were calculated for all experiments, the final coefficient (G_i) was computed using equation (6). The experiment yielding the highest Gi value demonstrates the optimal parameter levels.⁵⁴

G_{i} = \frac{1}{m} \sum (α_{j} \times G C_{i j})

(6)

Equation (6) incorporates two key parameters: m represents the combined effect coefficient across all responses, while α_j indicates the weighting coefficient for each individual response. In this investigation, equal weighting coefficients were applied to all responses. The calculated G_i coefficients for each experimental run are presented in Table 9.

Analysis of these results reveals that experiment 4 yielded the maximum G_i coefficient for tensile strength, whereas experiment 2 produced the highest value for elongation. This indicates that sample 4 demonstrated optimal tensile performance, while sample 2 exhibited superior elongation characteristics. Significantly, experiment 2 emerged as the optimal condition for concurrently enhancing both tensile strength and elongation. The corresponding parameters for this optimal condition were: 1 wt% CNT content, 0 wt% clay content, a feed rate of 30 mm/s, and a nozzle temperature of 260°C.

To confirm the reliability of the obtained results, several verification tests have been performed under optimal parameter conditions (Clay = 0 wt%, CNT = 1 wt%, feed rate = 30 mm/s, Nozzle temperature = 260°C). In addition, several tests were performed in the initial conditions of the parameters (Clay = 0 wt%, CNT = 0 wt%, feed rate = 20 mm/s, Nozzle temperature = 250°C) to compare with the optimal conditions. Results of experiments at initial and optimal conditions were shown in Table 10. As can be seen from Table 10, the tensile strength and elongation values in the optimal conditions have improved by 25% and 74%, respectively, compared to the initial conditions.

Table 10.

Results of experiments at initial and optimal conditions.

Run	Initial conditions	Optimal conditions
Clay (wt%)	0	0
CNT (wt%)	0	1
Feed rate (mm/s)	20	30
Nozzle temperature (°C)	250	260
Tensile strength (MPa)	53.8	67.3
Elongation (%)	27	46.9

Based on preliminary observations showing simultaneous improvement in both tensile strength and elongation at nozzle temperature of 270°C, this parameter was adjusted at 270°C in the optimal conditions for further evaluation. In addition, the tensile strength improved at clay content of 2 wt% and the elongation decreased slightly, so the clay content was also chosen at 2 wt% to examine the values of the responses obtained. Table 11 presents comparative results between the initial and modified optimal conditions. According to Table 11, the tensile strength and elongation values in the new optimal conditions have improved by 46% and 60%, respectively, compared to the initial conditions. Notably, these refined conditions (incorporating 270°C nozzle temperature and 2 wt% clay content) yielded substantially greater tensile strength than previous optimal settings, with only a minimal compromise in elongation performance.

Table 11.

Results of experiments at initial and new optimal conditions.

Run	Initial optimal conditions	New optimal conditions
Clay (wt%)	0	2
CNT (wt%)	1	1
Feed rate (mm/s)	30	30
Nozzle temperature (°C)	260	270
Tensile strength (MPa)	67.3	78.4
Elongation (%)	46.9	43.1

Conclusion

In this research, the thermal, electrical and mechanical properties of the PA6/Clay/CNT nanocomposite enhanced using the Taguchi method and grey relational analysis. Thermal characterization revealed that incorporating clay and CNT nanoparticles elevated both crystallization and melting temperatures while improving thermal stability through enhanced heat absorption. Electrical conductivity measurements demonstrated optimal performance at 1 wt% CNT and 2 wt% clay loading. Microstructural examination showed excellent nanoparticle dispersion at 1 wt% CNT and 2 wt% clay concentrations, corresponding to improved tensile strength and elongation. However, when amounts of clay and CNT increased up to 4 and 2 wt%, the aggregation of the nanoparticles was detected in the microstructure of the nanocomposite. The Taguchi optimization revealed that maximum tensile strength and elongation were achieved at a feed rate of 30 mm/s combined with a nozzle temperature of 270°C. These optimal processing conditions facilitated superior interlayer adhesion in the nanocomposite, which effectively minimized void formation and microstructural defects. The enhanced interfacial bonding between filament layers directly contributed to the improved mechanical performance observed at these parameters. Through grey relational analysis, the ideal processing parameters for concurrently enhancing tensile strength and elongation were identified as: 1 wt% CNT content, 2 wt% clay content, a feed rate of 30 mm/s, and a nozzle temperature of 270°C.

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Raman Kumar

Data Availability Statement

The data supporting the findings of this study are available within the article.*

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Examination of electrical conductivity,thermal stability,tensile strength and elongation of PA6/CNT/Clay nanocomposite fabricated by 3D printing

Abstract

Keywords

Introduction

Materials and methods

Materials

Fused Deposition Modeling (FDM)

Taguchi Design

Thermal Tests

Mechanical Tests

Electrical Tests

Microstructure Observation

Results and discussion

Analysis of thermal Properties

Analysis of electrical Properties

Microstructure analysis

Taguchi Design analysis

Grey Relational analysis

Conclusion

Footnotes

Declaration of conflicting interests

Funding

ORCID iD

Data Availability Statement

References