Influence of Graphene, Carbon Nanotubes, and Carbon Black Incorporated into Polyamide Yarn on Fabric Properties

Abstract

Carbon nanomaterials are increasingly being integrated into modern research, particularly within the textile industry, to significantly boost performance and broaden application possibilities. This study investigates the impact of incorporating three distinct carbon-based nanofillers—carbon nanotubes (CNTs), carbon black (CB), and graphene (Gn)—into polyamide 6 (PA6) multifilament yarns. It explores how these nanofillers affect the physical, mechanical, and thermal properties of PA6 yarns and fabrics. By utilizing melt extrusion, the nanomaterials were uniformly distributed in the yarns, and knitted fabrics were subsequently produced for detailed analysis. The research offers critical insights into how each nanofiller improves the thermal behavior of PA6-based textiles, enabling the customization of their applications. FTIR spectroscopy revealed significant chemical interactions between polyamide and carbon additives, while DSC analysis showed enhanced thermal stability, particularly with the inclusion of graphene. The introduction of these nanomaterials led to increased absorbance and decreased transmittance in the UV-Vis-NIR spectrum. Additionally, Far-Infrared (FIR) emissivity and thermal effusivity varied with different concentrations, with optimal improvements observed at specific levels. Although thermal conductivity decreased with the addition of these nanomaterials, heat management experiments demonstrated varied effects on heat accumulation and cooling times, underscoring potential applications in insulation and cooling technologies. These findings enrich the existing knowledge on nanomaterial-enhanced textiles, providing valuable guidance for optimizing PA6 yarns and fabrics for use in protective clothing, sportswear, and technical textiles. The comparative analysis offers a thorough understanding of the relationship between carbon nanomaterials and thermal properties, paving the way for innovative advancements in functional textile materials.

1. Introduction

In recent years, the integration of nanomaterials into traditional textiles has garnered significant interest and attention within both academic research and industrial applications. This trend marks a transformative evolution in the textile industry, introducing a wide array of innovative functionalities that were previously unattainable with conventional textiles alone [1,2]. Functionalized textiles, enhanced through the incorporation of nanomaterials, offer a multitude of benefits across diverse sectors, including enhanced heat resistance for protective clothing, improved thermal conductivity for comfort in various climates, and advanced functionalities such as odor absorption, moisture management, and biomedical applications. Furthermore, nanomaterial-treated textiles exhibit properties such as UV protection, electromagnetic interference shielding, and conductivity, enabling applications in smart textiles and specialized protective gear [3,4]. Among the various types of nanomaterials, carbon-based nanomaterials have emerged as leading candidates for textile functionalization due to their exceptional mechanical strength, chemical stability, high surface-to-volume ratio, electrical conductivity, and biocompatibility. Carbon nanomaterials encompass a range of structures including CNTs, Gn, and CB, each offering unique properties that can be tailored for specific textile applications [5,6,7].

The functionalization of textiles using nanoparticles has expanded to encompass diverse types such as carbon-based, inorganic, polymeric, composite, core–shell, hybrid, and engineered nanoparticles [8]. Carbon-based nanomaterials, in particular, have gained prominence due to their versatile properties and compatibility with textile substrates. Carbon, with its ability to form diverse structures like graphite, diamond, CNTs, graphene, and CB, offers unique advantages in enhancing textile functionalities. CNTs are characterized by their tubular structure and high aspect ratio, serve as multifunctional fillers in polymer matrices, and provide exceptional mechanical, electrical, and thermal properties even at low concentrations [9]. Graphene, known for its 2D honeycomb lattice structure and high surface area, exhibits properties such as high electrical conductivity, mechanical strength, chemical stability, and thermal conductivity (with a Young’s modulus of approximately 1.0 TPa) [10]. Carbon black, derived from thermal decomposition of hydrocarbons, is widely used in textile dyeing due to its cost-effectiveness and abundance [11,12].

The integration of carbon-based nanomaterials into textiles, however, poses several technical challenges [13]. Achieving uniform dispersion of these nanomaterials within the polymer matrix or on textile fibers is critical to ensure consistent properties throughout the textile. Nanomaterial agglomeration, driven by van der Waals forces, presents a major hurdle in achieving homogeneous dispersion. Furthermore, controlling the orientation of nanomaterials within the textile structure remains a challenge, despite its potential to enhance specific properties such as mechanical strength and electrical conductivity. To mitigate issues such as nanomaterial migration and separation within textiles, strong interactions between carbon-based nanomaterials and the polymer matrix are essential. Weak interactions can compromise textile material durability and performance under mechanical stresses such as stretching, bending, and abrasion, as well as during repeated washing cycles. Ensuring secure anchoring of nanomaterials within the textile structure is crucial in maintaining functionality over extended use, preventing a loss of nanomaterials and preserving textile integrity [14,15,16].

Various methods facilitate the incorporation of carbon-based nanomaterials into textiles, including deposition on fibers, yarns, or fabrics during finishing processes, coating, and embedding during melt spinning, which is a particularly effective method for polymeric filament yarns like polyester, polyolefins, and polyamide 6 (PA6) [17,18]. PA6 stands out among textile polymers due to its excellent melt processing, high resistance to elongation and abrasion, durability, mechanical strength, and chemical resistance [19]. Moreover, PA6′s chemical recyclability supports sustainability goals by reducing greenhouse gas emissions and conserving petroleum resources. While existing research has explored the functionalization of melt-spun polyamide fibers using various nanoparticle fillers, including TiO₂, ZnO, nano-silver, nano-clay, nano-silicates, graphene, CNTs, boron phosphate (BPO₄), and silver [20,21,22,23,24,25], there is limited research on the incorporation of carbon-based nanofillers during melt compounding and spinning of PA6 multifilament yarns and their specific impacts on mechanical and thermal properties.

Hence, this study aims to address this research gap by investigating the integration of three distinct carbon-based nanofillers, CNTs, CB, and Gn, into polyamide 6 during the melt spinning process to create multifilament yarns. These yarns will subsequently be knitted into fabrics to evaluate and enhance their functional properties. The research will vary the concentration of nanofillers (0.1%, 0.5%, and 1%) to systematically study and compare their effects on the mechanical and thermal properties of the composite textile materials. By advancing our understanding in this area, this study is pivotal for the development of advanced fabrics with improved properties, thereby contributing significantly to materials science and fostering innovation across various industries.

2. Materials and Methods

Polyamide 6 (PA6)-BASF ULTRAMID 8202C chips with a relative viscosity of 2.6 cP, a density of 1.13 g/cm³, and a melting point of 220 °C were used as the polymeric matrix. The carbon-based nanofillers used were multi-walled carbon nanotubes (MWCNTs) with an outer diameter of 10–30 μm and metal impurities less than 0.24%, provided by Nanomatics, carbon black with a particle size of 50–100 nm, and graphene with a particle size of 1–2 µm, supplied by 2DM Pte Ltd., Singapore. These nanofillers were mixed with the PA6 chips to prepare the masterbatches.

2.1. Preparation of Masterbatch

The PA6 polymer and carbon-based nanofillers (CNTs, CB, and Gn) were dried in an oven at 100 °C for 24 h to remove moisture completely. They were then mixed using twin-screw compounding to achieve a homogeneous distribution of the nanofillers at 2 wt% within the polymer matrix. A co-rotating twin-screw extruder (manufacturer: Xinda Compounding, Jiangyin City, China, model PSHJ-20) with a screw diameter of 21.7 mm and an L/D ratio of 28 was used for this process, utilizing a die with a hole diameter of 5 mm to prepare the masterbatch.

2.2. Fabrication of Melt-Spun Multifilament Yarn

PA6 granules containing 2 wt% of nanofillers were dried in an oven at 85 °C for 4 h before processing. Melt spinning was conducted with mixtures of virgin PA6 chips and various blending amounts of the 2 wt% PA6 batches at a final stage spinning temperature of 265 °C and a take-up speed of 1500 m/min. This process was carried out on a pilot plant (Fiber Extrusion Technology (FET), Leeds, UK) equipped with a single-screw extruder and spinnerets for solid circular fiber cross-sections, a quench cabin, and a high-speed winder. The 2 wt% batches were diluted with pure PA6 to achieve weight percentages of 0.1%, 0.5%, and 1% for melt spinning three different carbon-based nanofillers to produce multifilament partially oriented yarns (POYs) with a linear density of 130 denier and 48 filaments. These POYs were then drawn using a customized drawing roller unit with a draw ratio of 1.7 at a temperature of 70 °C to obtain 75D drawn multifilament yarns; the developed yarns with different carbon-based nanofillers at different concentrations are presented in Figure 1.

2.3. Development of Knitted Fabrics

The drawn yarns were used to produce fabrics through various knitting techniques. Ten different plain jersey fabrics, each approximately 3 m in length, were produced. This was achieved with the help of a customized 24-gauge, 6-feeder, 16-inch (cylinder diameter) circular knitting machine supplied by Anytester Co., Ltd. (Hefei, China). All fabrics were prepared using consistent knitting parameters, including loop length, knitting speed, and take-off speed. The developed knitted fabrics are presented in Figure 2.

2.4. Methods

To comprehensively evaluate the properties of the developed fabric samples, a series of standardized and specialized testing methods were employed across various domains. The methodology adhered to established ASTM standards and utilized state-of-the-art instrumentation to ensure accuracy and reliability in the characterization process.

2.4.1. Linear Density and Tensile Properties of Yarns

The linear density of the produced yarns was measured according to DIN EN ISO 2060 [26] using an electronic yarn wrap reel machine from GESTER. The tensile properties of the yarns were evaluated using a Gester universal testing machine, conforming to the ASTM D2256 standard. Prior to testing, the yarn samples were conditioned according to ASTM D1776 to minimize the environmental influence on the results.

2.4.2. Physical Properties of Fabrics

All fabric samples underwent conditioning to stabilize their properties before testing. Fabric thickness measurements followed ASTM D1777-96 (2019) [27] using a D2000 thickness tester. The areal density (grams per square meter, gsm) was measured according to ASTM D3776 [28], with five specimens per sample to ensure representative results.

2.4.3. UV-Vis-NIR

The fabric samples were analyzed for transmittance, reflection, and absorption across the UV-Vis-NIR spectrum using a Lambda 950 UV-Vis-NIR spectrophotometer from PerkinElmer. The FTIR spectra were obtained using a Nicolet iS-50 spectrometer equipped with a gold integrating sphere from PIKE Technologies, covering the range from 4000 to 500 cm⁻¹ with a resolution of 2 cm⁻¹ [29].

2.4.4. Fourier Transform Infrared (FTIR) Spectroscopy

FTIR spectroscopy was used to investigate the interactions between PA6 and the nanofillers. The spectra were recorded on a PerkinElmer 400 FT(N)IR device (Waltham, MA, USA) in transmission mode, completing 64 scans between 4000 and 500 cm⁻¹ with a resolution of 2 cm⁻¹.

2.4.5. Differential Scanning Calorimetry (DSC)

Thermal behavior was investigated using a TA Instruments DSC Q10 instrument under nitrogen atmosphere, heating the samples at 10 °C per minute up to 270 °C, and analyzed using Universal Analysis 2000 software.

2.4.6. Far-Infrared (FIR) Emissivity

Emissivity was measured using the EMS302M analysis system from HOTECH, covering the wavelength range from 5 to 14 µm [30].

2.4.7. Thermal Effusivity

Transient Plane Source effusivity (TPS-EFF) was measured with a Thermtest TPS-EFF meter, following ASTM D7984-16 [31].

2.4.8. Thermal Conductivity and Resistance

A Heat Flow Meter (HFM-25) from Thermtest Instruments was utilized to determine thermal conductivity and resistance by monitoring heat flux and achieving steady-state conditions.

2.4.9. Dynamic Heat Accumulation and Release

The thermal dynamics of the developed fabric samples were evaluated using an infrared (IR) lamp exposure method. Each fabric sample was placed on a Styrofoam board, serving as a thermal insulator to prevent heat absorption and maintain stable temperatures between tests. This set-up ensured a consistent testing environment, reducing external variables that could influence the outcomes. An IR lamp equipped with a 150 W bulb was positioned 30 cm above the fabric samples. The distance and intensity of the lamp were carefully controlled to ensure uniform exposure to infrared radiation across all samples. The IR lamp operated in cycles of 30 s activation followed by deactivation. During the activation phase, the lamp emitted infrared radiation, simulating heat input similar to sunlight or body heat. This cyclic exposure allowed for the observation of how each fabric sample accumulated and released heat dynamically, providing insights into their thermal performance characteristics [32].

The rate of cooling was measured by placing the fabric on a hot plate set to 45 °C to heat the fabric sample to 45 °C. Once the fabric reached this temperature, the hot plate was turned off, and the change in temperature was recorded using an FLIR camera. The time taken for the fabric samples to cool down to 26 °C was calculated and reported [33].

3. Results and Discussion

3.1. Linear Density and Tensile Properties of Yarns

The average linear density of the produced multifilament yarns is around 75D (denier), with each filament denier being 1.56D for both pure polyamide yarns and polyamide yarns containing additives. However, the linear density of the yarns with carbon nanoparticles is slightly varied compared to that of the yarns without additives but not significant based on statistical evaluation. This difference obviously occurs from the additive material input.

Figure 3 illustrates the relationship between tenacity (g/d) and breaking elongation of pure PA6 and PA6 modified with varying concentrations of three types of carbon-based nanofillers: CNTs, CB, and Gn. When CNTs are introduced into PA6, there is typically a reduction in tenacity, notably observed at a 0.5% concentration where a decrease of 17.37% is noted, despite an increase in breaking elongation. This decrease in tenacity may be attributed to the agglomeration of CNTs at higher concentrations, which disrupts the integrity of the polymer matrix. In contrast, carbon black enhances the tenacity of PA6, particularly at higher concentrations (e.g., 1%), showing a significant improvement. This enhancement is likely due to effective dispersion and strong interaction within the polymer matrix [34]. Notably, at a 0.1% concentration of carbon black, there is a notable increase in breaking elongation, indicating the enhanced ductility and stretch ability of the material.

The inclusion of graphene consistently decreases the tenacity of PA6 across all concentrations, likely due to challenges in achieving uniform dispersion within the matrix. However, breaking elongation shows a significant increase, suggesting improved ductility and stretch ability with graphene incorporation.

The mechanical properties of melt-spun yarns containing nanofillers are influenced by several factors, with the quality of nanofiller dispersion within the PA6 matrix being paramount. Poor dispersion can lead to agglomeration, creating vulnerabilities in the material. The interaction between nanofillers and the polymer matrix also plays a crucial role in distributing stress efficiently [35]. Strong interactions typically enhance mechanical properties, whereas weaker interactions may compromise them. Each type of nanofiller possesses distinct surface areas, aspect ratios, and mechanical characteristics: CNTs are prone to entanglement and alignment issues due to their high aspect ratio, while carbon black offers potential reinforcement owing to its expansive surface area. Graphene, with its planar structure, requires proper orientation for effective stress distribution. Processing conditions during melt spinning, such as temperature and shear forces, significantly influence the dispersion and alignment of nanofillers within the PA6 matrix, thereby impacting the final mechanical properties of the composite material [36].

3.2. Physical Properties of Fabrics

The areal density and thickness of all fabric samples were measured to ensure consistency across the experimental conditions. The measured average GSM (grams per square meter) of each fabric was found to be in the range of 120–125 GSM, and the thickness ranged between 0.35 and0.37 mm. Statistical analysis was performed to determine if there were any significant differences between the fabric samples with and without carbon-based additives. The analysis confirmed that there were no significant differences in areal density and thickness between the various fabric samples. This indicates that the physical characteristics of the fabrics, such as GSM and thickness, are consistent across all samples regardless of the presence of carbon-based additives. By maintaining uniformity in these physical properties, this study ensures that any observed differences in thermal properties can be attributed to the different additives and their concentrations rather than variations in the fabric’s physical characteristics. This approach isolates the effect of the additives, allowing for a more accurate assessment of how each additive and its concentration influence heat accumulation and dissipation.

3.3. Analysis of FTIR Spectra

As shown in Figure 4, the FTIR absorbance spectra of polyamide yarns with different additives, namely CNTs, CB, and Gn, at various concentrations reveal significant chemical interactions and structural modifications in the fabric. The FTIR spectrum of pure polyamide yarn shows characteristic peaks corresponding to the functional groups in its structure, including the amide I and II bands. The amide I band (1650–1700 cm⁻¹) is primarily due to the C=O stretching vibration, while the amide II band (1550–1600 cm⁻¹) arises from N-H bending and C-N stretching vibrations. The CH₂ stretching peaks (2850–2950 cm⁻¹) result from the symmetric and asymmetric stretching vibrations of CH₂ groups, and the broad N-H stretching peak (3200–3500 cm⁻¹) corresponds to N-H bond vibrations [37]. When CNTs are added, characteristic peaks appear at 1350 and 1580 cm⁻¹, known as the D and G bands, indicating disorder and graphitic nature. Shifts in the amide I and II bands compared to pure polyamide suggest interactions between CNTs and the polyamide matrix. Carbon black shows similar D and G bands at 1350 and 1600 cm⁻¹, with increased absorbance in the fingerprint region (500–1500 cm⁻¹) due to various bending and stretching vibrations of C-H and C-C bonds, indicating its presence [38,39]. Graphene also exhibits peaks at 1350 and 1580 cm⁻¹, corresponding to the sp² carbon framework, with increased absorbance in the 2800–3000 cm⁻¹ region, indicating interactions affecting C-H stretching vibrations. The additives increase absorbance in this region, indicating their presence in the polyamide matrix.

3.4. Differential Scanning Calorimetry

Figure 5 presents the differential scanning calorimetry (DSC) results illustrating heat flow (W/g) versus temperature (°C) for various polyamide yarn samples. These include pure polyamide yarn and polyamide yarns modified with three types of nanomaterials, CNTs, CB, and Gn, at concentrations of 0.1%, 0.5%, and 1%.

The reference pure polyamide yarn exhibits a glass transition temperature (T_g) of approximately 60–80 °C and a distinct endothermic peak around 230 °C, corresponding to its melting temperature (T_m). The addition of CNTs (0.1%, 0.5%, 1%) to the polyamide yarn results in a slight increase in T_g compared to pure polyamide, indicating improved thermal stability. Tm shows noticeable shifts and broadening, with higher concentrations having a more significant impact, suggesting better interaction and dispersion of CNTs within the polyamide matrix and enhancing crystallinity and thermal stability. The inclusion of carbon black (0.1%, 0.5%, 1%) results in moderate increases in T_g with higher concentrations, reflecting enhanced thermal stability. T_m shifts to higher temperatures and broadens, indicating good dispersion and interaction of carbon black with the polyamide matrix. Carbon black significantly increases T_g compared to CNTs, suggesting better reinforcement and interaction with the polyamide matrix. The shift in Tm is more significant with carbon black, enhancing crystallinity and thermal stability effectively. The inclusion of graphene (0.5% and 1%) shows a significant increase in T_g, especially at higher concentrations, suggesting a strong interaction between graphene and the polyamide matrix. Tm shifts to higher temperatures with increasing graphene content, indicating enhanced crystallinity and thermal stability. At these low concentrations, graphene may not significantly alter the polymer matrix of polyamide, and hence, T_g might remain relatively stable or could slightly decrease due to minor changes in polymer chain mobility. Graphene has the most substantial impact on T_g, particularly at 1%, demonstrating its strong interaction with the polyamide matrix. It also has the most significant impact on T_m, markedly improving thermal properties, crystallinity, and stability. Overall, the tubular structure and high aspect ratio of CNTs allow for their interaction with the polyamide matrix, but their dispersion and interaction are less effective compared to carbon black and graphene. The fine, spherical particles of carbon black offer a large surface area for interaction, leading to better reinforcement and thermal stability. Graphene’s planar structure and high surface area allow for excellent interaction and dispersion within the polyamide matrix, resulting in significant improvements in thermal properties [23]. Higher concentrations of each additive result in more pronounced effects on T_g and T_m due to the increased interaction and reinforcement within the polyamide matrix.

3.5. Effect of Additives on UV-Vis-NIR of Fabrics

Figure 6 illustrates the absorbance and transmittance spectra in the UV-Vis-NIR range of the polyamide fabric (PA6) samples with various additives, including carbon nanotubes (CNTs), carbon black (CB), and graphene (Gn), at different concentrations. In Figure 6a, the addition of these additives generally increases the absorbance of PA6 fabrics to varying extents. For pure polyamide fabric (PA6), the absorbance ranges approximately from 0.65 to 0.75 across the wavelength range of 200–1600 nm, with a noticeable increase after 800 nm. When CNTs are added, the absorbance varies with concentration. The areas under the absorption spectra in the UV range (200–400 nm), visible range (400–700 nm), and NIR range (700–1600 nm) for each sample, along with the percentage change from the reference, are provided in

Table 1. Analysis of area under curve of UV-Vis-NIR spectra.

Samples	Absorption			Transmittance
	AUC (200 nm–400 nm)	AUC (400 nm–700 nm)	AUC (700 nm–1600 nm)	AUC (200 nm–400 nm)	AUC (400 nm–700 nm)	AUC (700 nm–1600 nm)
Reference—Pure PA	129.4	191.6	578.0	4914.4	7430.5	16,802.6
PA with CNTs 0.1%	124.0	184.1	549.2	4804.0	7253.3	16,588.8
PA with CNTs 0.5%	128.8	192.0	574.1	4535.5	6808.7	15,348.5
PA with CNTs 1%	156.1	233.2	707.5	3780.1	5588.6	12,890.6
PA with CB 0.1%	127.4	188.4	586.2	4611.1	7000.0	14,824.2
PA with CB 0.5%	140.0	209.2	616.2	3991.7	5973.9	13,622.8
PA with CB 1%	126.8	188.5	564.8	4702.9	7085.0	15,792.3
PA with Gn 0.1%	156.6	230.9	681.4	3288.4	5036.2	11,265.8
PA with Gn 0.5%	133.0	199.3	600.9	4329.3	6451.9	14,281.3
PA with Gn 1%	120.5	179.9	555.3	4264.0	6384.9	14,282.9

. With 0.1% CNTs, the absorbance is around 4 to 5% lower than that of pure PA6 in all three ranges. With 0.5% CNTs, there are no significant differences in absorbance compared to the reference. With 1% CNTs, the absorbance starts at 0.8 at 200 nm and gradually increases, reaching 0.95 at 1600 nm, with the area under the curve being 21.97% higher in the UV range and 23% higher in both the visible and NIR ranges compared to the reference, indicating the highest absorption capacity. Carbon black additives also influence the absorbance spectra. With 0.1% CB, the absorbance shows no significant change and is slightly lower in the UV and visible ranges but higher in the NIR range compared to pure PA6. With 0.5% CB, the absorbance is around 5–10% higher than at 0.1%, maintaining a stable trend. Interestingly, with 1% CB, the absorbance is lower than the reference despite the higher concentration. Graphene additives display a different pattern. With 0.1% Gn, the absorbance increases significantly, by around 18–20% in all three regions compared to pure PA6. With 0.5% Gn, the absorbance decreases slightly compared to 0.1%. With 1% Gn, the absorbance further decreases compared to 0.5%.

The variations in absorbance with different concentrations of additives can be attributed to several reasons. For CNT additives, the absorbance increases with higher concentrations due to the enhanced interaction of CNTs with the fabric matrix, improving the light absorption properties. For CB additives, the initial increase in absorbance is attributed to CB’s high intrinsic absorbance. However, at higher concentrations (1%), the absorbance decreases, possibly due to the agglomeration of CB particles, which reduces the effective surface area for light absorption. In the case of graphene additives, the significant increase in absorbance at low concentrations (0.1%) is likely due to graphene’s excellent light absorption capabilities. As the concentration increases, the absorbance decreases, potentially due to agglomeration effects and increased light scattering.

Figure 6b shows that the transmittance of pure polyamide yarn is relatively stable between the 200 and 800 nm wavelength range, with a noticeable decrease toward higher wavelengths. At a 0.1% concentration, CNTs do not significantly alter the transmittance, with the area under the curve showing less than a 3% difference compared to pure PA fabric. At a 0.5% concentration, CNTs reduce the transmittance more noticeably (7–9%) across the entire wavelength range, indicating that higher concentrations of CNTs lead to lower transmittance. As shown in Table 1, the addition of 1% CNTs in the fabric results in around 23% lower transmittance across the UV-Vis-NIR regions compared to the fabric without additives. Both 0.1% and 0.5% concentrations of carbon black result in a noticeable reduction in transmittance compared to pure polyamide yarn. With 0.1% CB, there is a 6% reduction in the UV and visible spectral range and an 11.8% reduction in the NIR range. The reduction is more pronounced at higher concentrations (0.5%), demonstrating that carbon black is effective in decreasing transmittance, with a 19% reduction compared to the reference. However, a 1% addition of CB has a diminishing effect. Graphene at a 0.1% concentration results in a significant reduction in transmittance, around 33%, when compared to pure polyamide yarn. Higher concentrations of graphene (0.5% and 1%) lead to increased transmittance compared to the 0.1% concentration but still show an 11–15% lower transmittance than pure PA fabric, similar to the effect observed with carbon black. The differences in transmittance between the polyamide fabric samples can be primarily attributed to the intrinsic optical properties of the additives, their concentration, particle size and distribution, interfacial interactions with the polyamide matrix, and their specific absorption characteristics across the UV-Vis-NIR range [40]. Carbon black and graphene with lower concentrations (0.5% and 0.1%) are more effective in reducing transmittance due to their strong light absorption properties, while CNTs have a more moderate effect with lower concentrations but are effective with 1%. Among the additives, carbon black and graphene have a more substantial impact on reducing transmittance compared to CNTs at the same concentration.

3.6. FIR Emissivity

Emissivity is a material property that describes its ability to emit or radiate thermal infrared energy. Lower emissivity values indicate low emission, while higher values show high emission. The provided data in Figure 7 include the FIR (Far-Infrared) emissivity results for various polyamide fabric samples with different additives and concentrations. Incorporating CNTs at concentrations of 0.1% and 0.5% boosts FIR emissivity in comparison to pure polyamide fabric, likely due to the increased surface area and better interaction with infrared radiation. However, when the CNT concentration reaches 1%, the emissivity drops, probably because the CNTs start to agglomerate, diminishing their effectiveness. Similarly, carbon black enhances FIR emissivity at lower concentrations but sees a decrease at the 1% concentration, indicating that excessive carbon black might cause particle aggregation, thereby reducing its overall effectiveness. Graphene, on the other hand, behaves differently from CNTs and carbon black. At concentrations of 0.1% and 0.5%, graphene slightly decreases FIR emissivity, but at 1%, the emissivity returns to the baseline level. This behavior could be attributed to the unique structural and thermal properties of graphene, which may not enhance emissivity as effectively as CNTs or carbon black at these particular concentrations. Both CNTs and carbon black exhibit an initial rise in FIR emissivity at lower concentrations, followed by a decrease at the highest concentration (1%), implying that there is an optimal concentration range for these additives to effectively enhance FIR emissivity. In contrast, graphene does not show a notable increase in FIR emissivity at any concentration, instead exhibiting a slight reduction at lower concentrations and a neutral effect at higher concentrations.

3.7. Thermal Effusivity

Thermal effusivity is a property that characterizes how quickly a material can exchange thermal energy with its surroundings. It is a combination of thermal conductivity and volumetric heat capacity and describes a material’s ability to conduct and store heat. High-effusivity materials respond quickly to changes in temperature, while low-effusivity materials exhibit slower responses [41]. As shown in Figure 8, with the incorporation of CNT 0.1% in polyamide, there is a significant decrease in thermal effusivity around 30% when compared with the reference. There is a slight increase at the middle concentration (0.5%) and a slight decrease at the highest concentration (1%). This suggests that the addition of CNTs at 0.1% significantly reduces thermal effusivity, which could be due to inadequate dispersion or interaction within the fabric matrix. At 0.5%, the thermal effusivity increases but not significantly, likely because the CNTs are well dispersed and enhance heat transfer. However, at 1%, the slight decrease could be due to the aggregation of CNTs, which hinders their effectiveness. Regarding CB, at a 0.1% concentration, there is an increase in thermal effusivity, with the highest increase at 0.5%. However, at a 1% concentration, the thermal effusivity decreases, likely due to particle aggregation, which reduces the material’s ability to conduct heat efficiently. Graphene increases thermal effusivity at the lowest concentration, but at higher concentrations, it decreases, suggesting that higher amounts of graphene may lead to aggregation, reducing its thermal effectiveness.

3.8. Thermal Conductivity

Figure 9 shows the thermal conductivity of fabric samples made from pure polyamide and polyamide mixed with additives like CNTs, CB, and Gn at various concentrations. Adding CNTs to polyamide reduces the thermal conductivity, with the most significant decrease of 6% occurring at a 0.5% concentration. This reduction happens because the total interfacial area between the CNTs and the polymer matrix increases, which amplifies interfacial thermal resistance and lowers the composite’s thermal conductivity. Additionally, incomplete contact at the interface leads to more phonon scattering, increasing thermal resistance and further decreasing thermal conductivity. The growing number of CNT–polymer interfaces creates additional barriers to heat flow. At this stage, the CNTs do not yet form a continuous thermal network, so their potential as thermally conductive fillers is not fully realized. Instead, the disruptions in the polymer matrix caused by the CNTs continue to reduce the effective thermal conductivity. When the CNT concentration reaches around 1%, the CNTs start forming a percolated network within the polyamide matrix, creating more efficient thermal transport paths across the composite, which helps overcome the interfacial resistance. Carbon black (CB) slightly increases thermal conductivity at low concentrations but decreases it at higher levels. At low concentrations, CB does not significantly disrupt heat flow, but higher concentrations lead to agglomeration, forming clusters that reduce the effective surface area and disrupt thermal pathways, thus lowering conductivity. The increased interfacial resistance and disruption of the polymer microstructure at higher CB concentrations further decrease thermal conductivity by hindering phonon transport and altering the polymer’s crystalline structure. Graphene effectively reduces thermal conductivity at low concentrations (0.1% and 0.5%), with decreases of about 6% and 8% compared to pure polyamide. However, at 1%, thermal conductivity slightly increases from the 0.5% level. The reduction with lower concentrations is attributed to interface effects between the polymer to graphene and graphene to graphene, which can give rise to barriers to heat flow due to phonon scattering, and both can lower the overall effective thermal conductivity. Despite graphene’s inherent high thermal conductivity, its planar structure in the polymer matrix disrupts phonon transport, increasing thermal resistance. Strong interfacial interactions between graphene and polyamide further enhance phonon scattering, while layered graphene introduces additional heat dissipation paths, further reducing thermal conductivity. Graphene, known for its exceptional thermal conductivity, can form continuous networks in a polymer matrix when densely distributed, maintaining high thermal conductivity throughout the composite. The percolation threshold, the critical point where particles form a network, is crucial; below this threshold, isolated graphene particles limit thermal conductivity due to high interfacial resistance. Beyond this threshold, interconnected networks significantly enhance thermal conductivity by creating efficient heat transfer paths. Insufficient graphene concentration can lead to a discontinuous network, hindering heat transfer and potentially causing localized hotspots. This behavior is well documented in the literature [42,43]. Moreover, graphene’s alignment within a polymer matrix is a dynamic process that begins with its dispersion and continues through various stages of material processing. The drawing process plays a pivotal role in orienting graphene sheets along the polymer chains, which can significantly enhance the composite’s properties. However, achieving and maintaining this alignment requires careful control of processing conditions to avoid issues like aggregation, which could otherwise diminish the material’s overall performance.

The non-linear thermal conductivity in polymer matrices filled with graphene, carbon black, or CNTs arises from complex interactions, including thermal boundary resistance and phonon scattering, and the nanofillers’ morphology. These factors, along with temperature-dependent changes and strain effects, contribute to the non-linear relationship between filler concentration and overall thermal resistance. While all additives reduce the thermal conductivity of composite yarns, CNTs and graphene are most effective at lower concentrations with lower thermal conductivity, with graphene showing the greatest reduction at 0.5%. Carbon black’s effectiveness varies with concentration, being more effective at higher levels, particularly in enhancing thermal resistance for winter clothing applications.

3.9. Influence of Additives on Dynamic Heat Accumulation and Release

The experiment aims to evaluate how different fabrics accumulate and release heat when exposed to an IR lamp. This assessment is essential for understanding the thermal properties of fabrics, which are critical for insulation, temperature regulation, and comfort. In Figure 10, the results show the maximum heat accumulation for various polyamide fabric samples with different additives and concentrations when exposed to an IR lamp at 30 cm for 90 s. The reference fabric (pure polyamide) had a maximum temperature of 31.63 °C. CNTs increased heat accumulation significantly, with a 65% increase a at 1% concentration compared to the reference, indicating enhanced heat absorption and retention. Carbon black showed a 115% increase at a 0.1% concentration, suggesting strong heat absorption and retention, but the efficiency diminished at higher concentrations due to particle aggregation. Graphene also increased heat accumulation, with the highest increases observed at 0.5% and 1% concentrations, by 64% and 66%, respectively.

The cooling time data show how long various polyamide fabric samples took to cool from 45 °C to 26 °C as given in Figure 10. CNTs significantly reduced cooling time at a 0.5% concentration by 50% compared to the reference fabric due to their excellent thermal conductivity. However, at 1%, the cooling time was slightly higher, due to CNT agglomeration reducing heat transfer efficiency. At 0.1%, CB increased cooling time by 60%, indicating poor thermal conductivity or dispersion. Higher concentrations (0.5% and 1%) formed a conductive network, reducing cooling time and enhancing heat dissipation. Graphene’s effect was less pronounced, with low concentrations slightly increasing cooling time and higher concentrations providing modest improvements in thermal conductivity. Fabrics with additives that reduce cooling time are suitable for applications requiring rapid heat loss, such as sportswear, cooling garments, and electronics’ heat management. Fabrics with higher heat accumulation and increased cooling time are beneficial for thermal insulation applications, such as winter clothing, thermal blankets, and protective gear [44].

4. Conclusions

This study highlights the transformative impact of incorporating carbon nanotubes (CNT), carbon black (CB), and graphene (Gn) into polyamide (PA6) yarns and fabrics, significantly altering their mechanical, thermal, and optical properties. The results underscore that the type and concentration of nanofillers play a pivotal role in defining these material characteristics, influencing tenacity, elongation, thermal stability, optical behavior, and thermal management. Notably, CNTs enhance elongation but reduce tenacity, CB significantly boosts tenacity, and graphene improves elongation while reducing tenacity. These effects are closely tied to the quality of nanofiller dispersion and their interaction within the polymer matrix, emphasizing the necessity for optimized processing conditions to achieve uniform distribution. FTIR and DSC analyses confirmed the strong interactions between nanomaterials and PA6, revealing significant chemical modifications and improved thermal stability, particularly with graphene. Optical properties were enhanced, with increased absorbance and decreased transmittance due to CB and graphene’s light absorption capabilities. Thermal properties such as effusivity and conductivity were notably affected by nanomaterial concentration, influencing the heat management properties of PA6 fabrics, especially in terms of heat accumulation and cooling performance.

The findings demonstrate that CNTs, CB, and graphene can effectively tailor PA6 yarns for advanced applications, including protective clothing, sportswear, and technical textiles, by enhancing specific performance attributes. Future work should focus on refining nanofiller dispersion techniques and processing parameters to fully harness the potential of these nanomaterials, ensuring optimal performance tailored to specific end-use requirements. This study provides a solid foundation for the continued exploration of nanomaterial-enhanced polyamides in high-performance textile applications.