Ehsan Zarinabadi | Ramin Abghari* | Ali Nazari | Mohammad Mirjalili
© 2025 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
In this study, silica/Kaolinite/silver nanocomposites were synthesized according to experimental design results, using the central composite design (CCD) method. Samples were synthesized by impregnation on the polyester fabric, to get an in-situ approach to make a new performance of the polyester fabric to protect the human body from dangerous magnetic waves. Initially, magnetic saturation of the designed specimens was tested and its optimum values were measured with a Vibrating Sample Magnetometer (VSM) device. Mechanical properties including tensile strength, friction, abrasion, hydrophobicity (drop absorption), bending, thickness, and Crease Recovery Angle (CRA) of polyester fabrics impregnated with different amounts of nano-composite components were investigated using Response Surface Methodology (RSM) and PLS statistical methods which can help to show the effect of variables on each other. FESEM, EDX, and FTIR analyses were conducted for raw polyester-impregnated nanocomposites using an in-situ method under optimum conditions. The results confirm that the polyester fabric impregnated with three- component nanocomposite by varying concentrations of silica, Kaolinite, and silver, can significantly enhance the properties of saturation magnetic, strength, abrasion, friction, hydrophobicity, bending, thickness, air permeability, and CRA.
VSM, mechanical properties, saturation magnetic, structural equation, in-situ
Textile industry is one of the research areas where nanotechnology can make possible great advances [1-3]. Nanotechnology is based on the fact that properties of the materials will significantly improve when the particle size is reduced to nanometer dimensions [4-6]. A wide range of beneficial properties is obtained in various fields of textile industry [7, 8] when nanotechnology and its techniques were used, because it can change the properties of too many materials [9]. Nanomaterials in the range of 100 nm are widely used for industrial applications [10-13]. In this regard, nanotechnology is used effectively to enhance such desirable properties as fabric softness [14, 15], durability [16], strength [17], moisture absorption [18], anti-fire [19], and anti-bacterial [20], in fibers, yarns and fabrics [21-23].
Magnetic forces are generated by the motion of charged electrical particles [24-27]. Magnetic field is not a central filed, in other words, there is no one magnetic pole [28-30]. Electrical current in a circular loop of wire creates a magnetic field at the center [31-33]. Therefore, electrons mainly affect magnetic properties of solids [34]. The electrons have a magnetic moment of about 10× 3.9 e.m.u to 21 × 3.9 e.m.u. One of them is magnetic properties of composite materials such as nanocomposites [35], polymers [36], and man-made fibers [37], which a non-conductive particle is added to a metal or polymer matrix in order to modify the magnetic properties [38]. Materials exhibit a variety of magnetic behaviors [39] when they exposed to a magnetic field. According to this, they are classified into some categorizes like diamagnetic [40-44], paramagnetic [45-47], and ferromagnetic [48-51]. However, in some of research papers antiferromagnetic [52-53] and free magnetics are considered as subgroups of ferromagnetic materials [54-58].
Data processing analysis is a multi-step procedure which can obtain data from statistical population, where they (sample) are summarized [59, 60], coded [61], categorized and finally processed for applying in various analytical systems to reach a hypothesis testing [62, 63]. Data analysis is a process based on science which can apply for any scientific research [64]. Therefore, all research activities are controlled and managed until the results to be achieved [65-67]. For this purpose, proposed and designed model is validated using structural equation modeling method [68-71], in order to validate the contained value of each indicator at the measuring desire properties. A comprehensive structural equation model is consisting of path diagram and confirmatory factor analysis. This method widely used in research studies aimed to test a particular model or design a model to get relationship between variables [72-74].
Least squares method does not require a default distribution type for measurement variables [75-77]. If measurement variables are perceptual, as defined on Likert scale [78], they have an undetermined distribution [79]; therefore, they are abnormal and the least squares method is superior to covariance-oriented methods [80-82]. Covariance- oriented methods are susceptible to sample size [83]. Smaller sample sizes may reduce statistical power of the method [84]. Moreover, with reducing sample size, data normalization assumption will not be displayed greatly [85]. The least squares method can estimate parameters of proposed model using the original sample [86]. However, to achieve a correct statistical estimation of the model [86], it can use re-sampling method to compute confidence intervals for model parameters [87]. Resampling method (e.g. Bootstrapping) validate models using random subsets of the data [88-91]. When parametric clauses (e.g. normality) are not satisfied [92], resampling is another powerful method for statistical inference [93]. Accordingly, least squares method is a powerful and suitable tool when we have some abnormal data and small sample sizes.
Harmful levels of electromagnetic radiation along with new technologies can affect the life quality of people around the world. There is some research about fabricating special goods to protect the human bodies from harmful electromagnetic waves and checking the mechanical and comfortable of the fabrics [113, 114] but there has been no comprehensive research on partial least squares statistical analysis on them. This software is not commonly used at textile industries. In this research, a new kind of fabric were synthesized using in situ method to protect people from all harmful electromagnetic waves. Some of experiments such as comfort and mechanical test has been done to confirm as- prepared fabric can consume in the apparel. DX software help us to design the experiments, also Smart PLS software were used to produce as-prepared fabric in industrial size and its real effect on the variables.
1.1 Instrumentation
1.1.1 Materials
Kaolinite Nano clay particles (commercially named as Sillitin N85) were purchased from Haffman Co. (Muenchene Strasse 75 • DE-86633 Neuburg (Donau), Germany). Density of particles was about 2.6 g/cm3. AgNO3, citric acid (CA) cetyl-trimethyl-ammonium bromide (CTAB) `and Sodium Hypophosphite (SHP) were purchased from Merck Co (8064293, Darmstadt, Germany). The polyester fabrics (with weft and warp densities of 22.1 and 15 yarn/cm and yarn Numerical 150 denier were purchased from yazdbaf Co (Yazd, Iran).
1.1.2 Instruments
Briefly, an Osram UV 400 lamp (HTC 400-241 400W R7S UV LAMP) was used to cure the fabrics with nanocomposites. Surface morphology of the fibers was examined through field emission scanning electron microscopy Via a MIRA3-TESCAN-XMU FE-SEM equipped with a Pulse or Maxim/Quartz Imaging XOne EDX system. Images and EDX analyses were taken using a 15 kV electron accelerating voltage. The presence of Ag, kaolinite and silica particles in the nanocomposites and polyester fabrics was confirmed by EDX system and mapping (Bruker Xflash6/10) which explained above. Tensor 27 (Bruker Germany) infrared spectroscope was applied to evaluate and check the presence of functional group in the impregnated samples.
1.1.3 Method
Design of experiments (DOE)
A design expert toolbox with engineering design tools (related to the response surface methodology) were applied to optimize preparation conditions of polyester fabrics. In our analysis, three independent variables were considered, including Silitin N85 concentration (3.0-9.0 g), AgNO3 (30- 60 mL) concentration, and UV irradiation time (30-60 min) (see, Table 1). The effects of these variables on saturated magnetic, strength, abrasion, friction, thickness, bending, crease recovery angle, air permeability and hydrophobic features of the polyester fabrics were evaluated, respectively.
Partial least squares (PLS)
The effect of parameters such as Saturate magnetic, strength, abrasion, friction, hydrophobicity (Drop absorption), bending, thickness, air permeability and CRA in polyester fabrics were investigated using Smart PLS-SEM software to achieve structure modeling.
1.1.4 Preparation of silica/kaolinite/silver nanocomposites and in situ impregnation of polyester
Polyester fabric was prepared with different amounts of Silitin, containing SiO2-kaolinite, as shown in Table 1. Next, different values of an AgNO3 (0.4 N) solution and CTAB (2:1, CTAB/nanocomposite) were added to the mixture and then stirred slowly for 60 minutes. In another side, 8.0% On Weight of fiber (O.W.F) CA and 5.0% (O.W.F) SHP were added to the suspended mixture which was placed in an ultrasound bath for 120 minutes at 50ºC. The polyester samples immersed in as prepared suspended mixture for 120 seconds and then padded with 85% wet peak up using heavy duty padding mangle (Rapid, Turkey). The samples were dried for four minutes at 60ºC and then cured at room temperature under a 400-W UV irradiation as shown in Table 1. The irradiated fabrics were rinsed with deionized water for three times until the additional and unfixed nanocomposites, CA and SHP were removed. Finally, the treated fabrics were dried in a vacuum drying oven for 1hr at 40ºC.
Table 1. Design of experiments
|
|
Sil |
Silitin N85 |
UV |
Ms |
Warp Strength (N) |
Weft Strength (N) |
Abrasion |
Fri |
Drop Absorption |
Thickness |
Air Permeability |
Be |
Crease |
|
contr |
0 |
0. 00 |
0 |
0.1 28 |
31 0.8 |
31 0.0 |
98 6 |
0. 22 |
20 |
0. 34 |
60 .5 |
2.1 |
42 |
|
1 |
45 |
6. 00 |
45 |
0.3 89 |
31 8.5 |
31 8.2 |
11 45 |
0. 27 |
15 2 |
0. 35 |
41 .3 |
3.8 5 |
53 |
|
2 |
45 |
6. 00 |
45 |
0.3 76 |
32 2.4 |
32 1.5 |
11 44 |
0. 26 |
15 0 |
0. 36 |
38 .1 |
3.5 6 |
53 |
|
3 |
45 |
6. 00 |
19 .7 |
0.3 05 |
33 4.1 |
33 3.0 |
11 36 |
0. 22 |
14 1 |
0. 4 |
45 .6 |
4.3 |
50 |
|
4 |
60 |
3. 00 |
30 |
0.3 13 |
32 6.4 |
32 5.7 |
11 30 |
0. 26 |
14 5 |
0. 33 |
39 .7 |
3.3 |
50 |
|
- 5 |
30 |
9. 00 |
30 |
0.3 97 |
32 9.4 |
32 8.9 |
11 49 |
0. 23 |
82 |
0. 36 |
36 .4 |
3.9 |
52 |
|
6 |
45 |
0. 95 |
45 |
0.2 59 |
32 5.6 |
32 4.2 |
10 40 |
0. 30 |
16 0 |
0. 37 |
41 .8 |
3.3 |
50 |
|
7 |
45 |
6. 00 |
45 |
0.3 53 |
32 5.4 |
32 4.1 |
11 47 |
0. 27 |
18 8 |
0. 36 |
31 .6 |
3.9 |
54 |
|
8 |
45 |
6. 00 |
45 |
0.3 91 |
32 4.1 |
32 3.0 |
11 46 |
0. 28 |
18 6 |
0. 35 |
38 .3 |
3.7 |
53 |
|
, 9 |
45 |
6. 00 |
45 |
0.3 79 |
32 2.7 |
32 1.4 |
11 46 |
0. 27 |
17 8 |
0. 35 |
39 .3 |
3.5 |
57 |
|
10 |
60 |
9. 00 |
30 |
0.4 26 |
33 4.9 |
33 3.5 |
12 56 |
0. 23 |
74 |
0. 36 |
39 .4 |
3.3 |
59 |
|
11 |
19 .7 |
6. 00 |
45 |
0.2 79 |
32 4.8 |
32 3.5 |
10 50 |
0. 26 |
12 8 |
0. 36 |
19 .6 |
2.9 6 |
51 |
|
12 |
60 |
9. 00 |
60 |
0.4 12 |
32 3.6 |
32 2.4 |
12 00 |
0. 24 |
69 |
0. 35 |
43 .2 |
2.8 7 |
58 |
|
13 |
30 |
9. 00 |
60 |
0.3 75 |
32 1.4 |
32 0.4 |
11 37 |
0. 23 |
73 |
0. 36 |
39 .4 |
2.8 |
57 |
|
14 |
30 |
3. 00 |
30 |
0.2 95 |
32 6.8 |
32 5.7 |
11 30 |
0. 23 |
14 8 |
0. 36 |
47 .2 |
2.6 4 |
54 |
|
15 |
30 |
3. 00 |
60 |
0.2 85 |
32 5.6 |
32 4.1 |
11 32 |
0. 25 |
14 6 |
0. 36 |
45 .2 |
2.8 6 |
55 |
|
16 |
70 .2 |
6. 00 |
45 |
0.3 96 |
32 9.6 |
32 8.5 |
12 11 |
0. 22 |
18 8 |
0. 33 |
51 .3 |
3.1 4 |
58 |
|
17 |
45 |
11 .0 |
45 |
0.4 14 |
33 3.7 |
33 2.6 |
11 36 |
0. 21 |
17 1 |
0. 35 |
35 .7 |
3.5 8 |
52 |
|
18 |
45 |
6. 00 |
70 .2 |
0.3 21 |
31 0.7 |
30 9.1 |
11 29 |
0. 25 |
46 |
0. 35 |
39 .6 |
3.6 2 |
58 |
|
19 |
60 |
3. 00 |
60 |
0.3 12 |
32 1.7 |
32 0.6 |
11 38 |
0. 26 |
16 0 |
0. 34 |
41 .3 |
2.9 6 |
56 |
|
20 |
45 |
6. 00 |
45 |
0.3 88 |
31 9.6 |
31 8.5 |
98 6 |
0. 27 |
15 1 |
0. 35 |
37 .2 |
3.5 7 |
53 |
Design of Experiments (DOE)
When a ferromagnetic substance is placed inside a very strong external magnetic field, large amounts of atomic magnetic dipoles will become aligned, along with the external field. Therefore, the volume of alignment along the external field reaches its maximum values. This condition is named magnetic saturation [94].
Figure 1. Magnetization of materials
In the present study, the maximum and minimum values of the magnetic saturations were observed in Runs 10 and 11, respectively. This phenomenon indicates that addition of silitin (kaolinite/silica) up to 9 grams to nanocomposite can increase magnetic saturation. In addition, magnetic saturation of Run16 and 11, which contain 70.23 and 19.77 ml of silver nitrate, increase with increasing in silver content. From the above results, it can be concluded that silver can increase magnetic saturation. From the experimental results, it is found that exposure to UV light (254 nm) for more than 45 minutes increases magnetic saturation. The experimental results show that exposure to UV Irradiation for less than 45 minutes can reduce it (see, Run 9 and 18).
Figure 2. Schematic of saturated magnetic on impregnated polyester fabric with nano composite
Passage of air through the fabric is one of the most important parameters to make clothes more comfortable [96-98]. Air permeability describes with a standard and must be taken into consideration by the manufacturer which is directly, depends on the fabric usage, according to the ASTM D737 standard, 10 × 10 cm pieces of the fabric specimens were placed between the jaws clamps of the device (METEFEM, Hungry) and then turned it on. For the experiments, we used 4 different air columns. According to the standard method, the largest one relates to the maximum volumetric air flow, and the other columns show air flow rates with higher accuracy. In another hand, sum of numbers which resulted from the columns is used to accurate calculation of absolute air flow rate. Air pressure was adjusted at 100 Pa. This value can vary for different specimens, but it is very important that pressure should be fixed at 100 Pa for different experiments.
From the experimental results, maximum and minimum values of air permeability belonged to Runs 16 and Run11, respectively. The results also reveal that air permeability of the fabric increases with increasing the silver nitrate content. It means that, as prepared samples are more comfortable. Therefore, in-situ coating can reduce air permeability of the polyester fabric.
Figure 3. Schematic of air permeability on impregnated polyester with nano composite
Fabric strength tests were conducted to determine the sample resistance along with possible tensions during manufacturing process [99-100]. Strength of fabric is evaluated along the warp or weft directions [101]. Fabrics with different chains, twill and circular warp textures, have an acceptable strength [102]. Fabric strength can be increased by adding some kind of chemical composites to the fabric. According to ASTM D5034 standard, 5.19 × 5 cm pieces of the fabric specimens were placed between the two clamps of the device (MESDAN, Italy) And then their strengths were tested, successfully. In this research, maximum strength value along the warp or weft directions was observed in Run3, where UV irradiation was adjusted at the minimum value. Therefore, change in UV radiation can have a significant effect on the strength of specimens (see, Run18). A slightly smaller difference was observed between warp and weft directional strengths which is due to the variety in densities of the warp and weft yarns (15.1 and 22.1 cm, respectively).
Figure 4. Schematic of strength on impregnated polyester with nano composite, (a) maximum strength by using low ultraviolet irradiation time (b) minimum strength by using high ultraviolet irradiation time
Abrasion resistance test is one of the most important experiments in the textile industry [103]. According to ASTM D3885 (standard test method), 10×10 cm pieces of fabric specimens (regarding to the clamps and their holding sizes) were put into the holding clamps and then the number of cycles which fabric can endure before the yarn breaks was recorded for each specimen. In this experiment, thick texture (new chemical substances coating) increase abrasion resistance of the fabric. In this study, abrasion resistance increased along with the increase in silitin content of three-component nanocomposite. In addition, abrasion resistance decreased along with increasing in ultraviolet irradiation (Run3 and 18).
According to ASTM D3108 standard, 10 × 8 cm pieces of fabric specimens (regarding to metal clamp sizes range) were put into the holding clamps and then plate metal smooth started to move. When the plate was slipping down on the fabric, sensor activated and showed the friction angle. The coefficient of friction (COF) was calculated by the following relation: tanθ=μs (1)((Where θ is the bend angle of the plate and μs)).
Figure 5. Schematic of abrasion on impregnated polyester with nano composite, (a) High abrasion resistance of the impregnated polyester fabric with nano composite (b) Very low abrasion resistance of the raw polyester fabric
Figure 6. Abrasion test with laboratory machine
As shown in Table 1 for run17, friction is smaller than one which observed for the control specimen. It can be concluded that friction decreased by increasing in silitin content of the in- situ impregnated polyester fabric. It can be found that friction decreases along with increasing UV light exposure over 60 minutes, when comparing two experimental results concerning run9 and 18.
Figure 7. Schematic of friction on impregnated polyester with nano composite, (a) low friction resistance of the impregnated polyester fabric with high ultraviolet irradiation (b) high friction resistance of the raw polyester fabric
According to AATCC 79-2000 standard method, 2.5 × 8 cm pieces of fabric specimens were placed on a glass plate and then a drop of water was poured over them where we used dropper at a 60° angle. After that, water absorption of the specimens was measured by a stopwatch. Control specimen test showed a minimum hydrophobicity about 20 seconds. Therefore, in-situ coating of polyester fabrics with silica/Kaolinite/silver can increases hydrophobicity. Experimental results show a maximum hydrophobicity, which is related to run16 and 7, and also a minimum hydrophobicity which is reported for run18. Therefore, hydrophobicity increases with increasing silver nitrate content, and decreases along with increasing ultraviolet light irradiation for more than 45 minutes.
Figure 8. Schematic of drop absorption on impregnated polyester with nano composite
Figure 9. Drop Absorption test
According to ASTM D1777 standard test, 4 × 4 cm pieces of fabric specimens were placed between the clamps of the device and pressure was set as 1 N. In this experiment, thickness display in millimeters when you press the start button. When ultraviolet radiation is minimum, fluffs and staples remain on the fabric surface and they are not destroyed. Hence, thickness reaches its maximum value. Maximum ultraviolet radiation reduces fabric thickness (Run16).
According to ASTM D6828 standard Test, 2.5 × 8 cm pieces of fabric specimens were placed on bending platform with a specific steel ruler on it. Notice that, when the bending reaches the red line, its value is recorded in centimeters.
According to ASTM D3990 standard test, 2.5 × 5 cm pieces of fabric specimens were placed under the weight machines. After 5 minutes, the specimens were placed on a goniometer. First, the crease angle was recorded, and then after 5 minutes, the crease recovery angle was measured which can generate by the following expression:
Crease recovery angle = (Ultimate crease recovery angle) – (Calculated Crease angle).
Statistical analysis
Design Expert is powerful software which is widely used for design of experiments. In the present study, response surface quality optimization tool (RSM)1 was considered which is widely used for optimizing manufacturing processes and product designs following equations (1 to 10) show the generated mathematical models. Response surface methodology is an optimization methodology which can yield 3D models to show what variable has minimum or maximum effect on the results to solve the problem of researches. This will happen by using a set of mathematical and statistical techniques.
Ms(emu/gr) = +0.38+0.035 × [silver nitrate]+0.046 × [silitin N85]+4.989E-003 × [UV irradiation time]+2.747E-003 × [silver nitrate] × [silitin N85]+2.020E-003 × [silver nitrate] × [UV irradiation time]-3.098E-003 × [silitin N85] × [UV irradiation time]-9.420E-003 × [silver nitrate]2-9.570E-003 × [silitin N85]2-0.018 × [UV irradiation time]2-2.400E-004 × [silver nitrate] × [silitin N85] × [UV irradiation time]+4.361E- 003 × [silver nitrate]2 × [silitin N85]-0.011 × [silver nitrate]2× [UV irradiation time]-0.021 × [silver nitrate] × [silitin N85]2 (1)
Strength (Warp) (N) = +313.45+1.84 ×[silver nitrate]+0.34 × [ silitin N85]-5.89 × [UV irradiation time]-0.99 ×[silver nitrate]× [ silitin N85]-2.11 ×[silver nitrate]× [UV irradiation time]- 0.044×[ silitin N85]× [UV irradiation time]+1.90 ×[silver nitrate]2+2.66 ×[ silitin N85]2+0.42 ×[UV irradiation time]2 (2)
Strength (weft) (N) = +313.68+1.86 ×[silver nitrate]+0.36 ×[ silitin N85]-5.98 ×[UV irradiation time]-0.91 ×[silver nitrate]×[silitin N85]-2.11×[silver nitrate]×[UV irradiation time]+0.024×[ silitin N85]×[UV irradiation time]+1.92 ×[silver nitrate]2+2.60 ×[ silitin N85]2+0.48 ×[UV irradiation time]2 (3)
Abrasion (round) =+1142.09+32.71 × [silver nitrate]+27.35 ×[ silitin N85]-5.11 × [UV irradiation time]+20.50 × [silver nitrate] × [ silitin N85]-4.75 × A× [UV irradiation time]-9.75× [ silitin N85] × [UV irradiation time]+4.61 × [silver nitrate]2-10.42 × [ silitin N85]2+5.31 × [UV irradiation time]2 (4)
Friction (µs) =+0.27-1.072E-003 ×[silver nitrate] -0.017× [silitin N85]+5.838E-003× [UV irradiation time]-1.000E-003× [silver nitrate] × [silitin N85]-5.000E-004 × [silver nitrate] × [UV irradiation time]-2.500E-003× [silitin N85] × [UV irradiation time]-9.257E-003× [silver nitrate]2-5.898E-003× [silitin N85]2-0.012× [UV irradiation time]2 (5)
Drop absorption(s)=+168.31+17.84×+3.27 × [silitin N85]-Air permeability (m3/m2/1hr/100pa) =+37.58+9.45×[silver nitrate] -× [silitin N85]-1.77 × [UV irradiation time]+2.28 × silver nitrate] × silitin N85]+0.55 × silver nitrate] × UV irradiation time]+0.89 × silitin N85] × [UV irradiation time]-0.25 × silver nitrate] 2+0.91 × silitin N85]2+2.28×UV irradiation time]2- 0.35× silver nitrate]×silitin N85]×[UV irradiation time]- 0.078× silver nitrate]2 × silitin N85]+2.59 × silver nitrate]2× UV irradiation time]-10.02 × silver nitrate] × silitin N85]2 (8)
Bending (cm)=+3.69+0.039 ×[silver nitrate]+0.12×[silitin N85]-0.20×[UV irradiation time]-0.16×[silver nitrate]×[silitin N85]+0.014×[silver nitrate]×[UV irradiation time]-0.18× [silitin N85]×[UV irradiation time]-0.31× [silver nitrate]2-0.17× [silitin N85]2+0.016×[UV irradiation time]2 (9)
Crease Recovery Angle(CRA)=+54.15+1.23×[silver
nitrate]+1.05×[ silitin N85]+1.79×[UV irradiation time] (10)
(a)
(b)
(c)
Figure 10. Response surface for Ms (emu/gr) as a function of: (a) AgNO3 and silitin N85, (b) AgNO3 and UV irradiation time, (c) UV irradiation time and silitin N85
According to the Figure 10, there is a response for the Ms (emu/gr) in three 3D charts. Chart (a) can show that silver nitrate in 60 ml with 52.50 min UV irradiation time is the best situation for high Ms(emu/gr). In chart (b) which is showing silitin N85 and silver nitrate effect, the high red peak in chart is for 9 gr and 60 ml of the materials. The last chart (c) showing the effect of silitin N85 and UV Irradiation time which has high peak in red color for 45 min and 9 gr.
(a)
(b)
(c)
Figure 11. Response surface for strength(warp) as a function of: AgNO3 and silitin N85, (b) AgNO3 and UV irradiation time, (c) UV irradiation time and silitin N85
According to the Figure 11, here the warp strength of fabric tested which is showing that in chart (a), silver nitrate has good effect by 60 ml and silitin N85 can improve these properties with 9 gr value. In Chart (b) there is a high peak at the right of the chart with green and yellow color which is the best result for the strength. Chart (c), strength has significant effect from UV and silitin N85 which is showing by red color.
(a)
(b)
(c)
Figure 12. Response surface for strength(weft) as a function of: (a) AgNO3 and silitin N85, (b) AgNO3 and UV irradiation time, (c) UV irradiation time and silitin N85
Weft strength has same result like the warp strength which is showing that the composite has same effect on fabric structure. The highest effect is for Silitin N85 and UV irradiation.
(a)
(b)
(c)
Figure 13. Response surface for Abrasion (round) as a function of: (a) AgNO3 and silitin N85, (b) AgNO3 and UV irradiation time, (c) UV irradiation time and silitin N85
According to the Figure 13, 3D chart (a) is showing the effect of the Silitin N85 and silver nitrate for the fabric abrasion. The best fabric abrasion is 1220 round which is showing by the yellow color on the chart. In chart (b), the optimization of the abrasion by the 30 min UV irradiation and 60 ml silver nitrate is 1117 round. The best result for the silitin N85 and UV irradiation can see in chart (c) which is 1145 round.
(a)
(b)
(c)
Figure 14. Response surface for Friction (µs) as a function of: AgNO3 and silitin N85, (b) AgNO3 and UV irradiation time, (c) UV irradiation time and silitin N85
According to the Figure 14, there is a normal behavior of the material. In chart (a), the yellow color of the chart can show the trend of the friction behavior because of the materials. The highest peak is for the 38 ml silver nitrate and 3.5 gr Silitin N85. Chart (b), 45 ml silver nitrate and 45 min UV irradiation is the best result for the friction of the fabric.
(a)
(b)
(c)
Figure 15. Response surface for Drop Absorption (s) as a function of: (a) AgNO3 and silitin N85, (b) AgNO3 and UV irradiation time, (c) UV irradiation time and silitin N85
There is a huge difference in chart (a) about materials behavior in Drop absorbtion test. There is two high peaks in red color, one is for the silver nitrate 30ml / Silitin N85 30gr and another is for silver nitrate 60 ml/Silitin N85 30 gr. It is showing that after increasing silver nitrate up to 60, the optimization of the drop absorption will be increase. Chart (b) is showing that there is dramatically drop absorption time increasing because of the UV irradiation time which colored by red. Chart (c) has smooth growing in uv irradiation time (45min). after that by the increasing the time of irradiation, the drop absorption time is going down.
(a)
(b)
(c)
Figure 16. Response surface for Thickness (mm) as a function of: (a) AgNO3 and silitin N85, (b) AgNO3 and UV irradiation time, (c) UV irradiation time and silitin N85
According to the Figure 16, the thickness of the fabric has some changes which is showing in all charts. The highest changing in chart (a) happened by increasing Silitin N85 component which is predicable. In chart (b) thickness decreased by the UV irradiation time which is showing that UV Irradiation can destroyed some of the layers on the top or bottom of the fabric. Chart (c) showing that by increasing silitin N85 again the thickness will change.
(a)
(b)
(c)
Figure 17. Response surface for Air permeability (m3/m3/1hr/100pa) as a function of: (a) AgNO3 and silitin N85, AgNO3 and UV irradiation time, (c) UV irradiation time and silitin N85
According to the Figure 17, the air permeability is increasing in silver nitrate 65ml and Silitin N85 6 gr (chart (a)), in chart (b), there is twi high peak which is highlighted by the red color in the corner of the shape. When the silver nitrate is 60 ml, in UV irradiation time at the minimum and maximum there is high air permeability. Chart (3), has smoothly changes. The optimize point is in yellow color.
(a)
(b)
(c)
Figure 18. Response surface for Bending (cm) as a function of: AgNO3 and silitin N85, (b) AgNO3 and UV irradiation time, (c) UV irradiation time and silitin N85
Regarding the Figure 18, there is the low peak by the blue color which is showing that minimum silver nitrate and Silitin N85 have low affect on fabric bending. Chart (b) is showing that the silver nitrate 45 ml and UV irradiation 45 min can deliver the optimize bending. In Chart (c), low UV irradiation with high silitin N85 component can deliver the optimize bending in fabric.
(a)
(b)
(c)
Figure 19. Response surface for crease recovery angle (cra) as a function of: (a) AgNO3 and silitin N85, (b) AgNO3 and UV irradiation time, (c) UV irradiation time and silitin N85
One of the simple models in DX software is linear. Regarding all charts in Figure 19, when the nanocomposite components are high the CRA is optimize.
RSM not only can reduce the computational and simulation cost, but also predicts and shows normal trend of process optimization which is mainly followed with non-linear relationships. Although the generated models are second, third, or sometimes fourth order, many optimization and decision making programs cannot generate third- (or higher) order models. In the other words, they are less able to find the optimum ultimate response. ANOVA test was used (Design -Expert software, version 7.0.0.1) to investigate and determine the difference between response surface.
Table 2. ANOVA results of saturated magnetic for polyester impregnated with nanocomposite
|
ANOVA for Response Surface Cubic Model |
|||||
|
Source |
Sum of Squares |
Df |
Mean Square |
F Value |
p-value Prob > F |
|
Model |
0.0477273 |
13 |
0.0036713 |
7.0320793 |
0.0125 |
|
A-silver |
0.0069384 |
1 |
0.0069384 |
13.289862 |
0.0108 |
|
B-silitin n 85 |
0.012011 |
1 |
0.012011 |
23.005794 |
0.0030 |
|
C-UV |
0.0001408 |
1 |
0.0001408 |
0.2696583 |
0.0222 |
|
AB |
6.039E-05 |
1 |
6.039E-05 |
0.1156712 |
0.7454 |
|
AC |
3.264E-05 |
1 |
3.264E-05 |
0.0625248 |
0.8109 |
|
BC |
7.676E-05 |
1 |
7.676E-05 |
0.1470187 |
0.7146 |
|
A^2 |
0.0012788 |
1 |
0.0012788 |
2.4494858 |
0.1686 |
|
B^2 |
0.00132 |
1 |
0.00132 |
2.5282525 |
0.1629 |
|
C^2 |
0.0046789 |
1 |
0.0046789 |
8.9619292 |
0.0242 |
|
ABC |
4.608E-07 |
1 |
4.608E-07 |
0.0008826 |
0.9773 |
|
A^2B |
6.303E-05 |
1 |
6.303E-05 |
0.1207218 |
0.7401 |
|
A^2C |
0.0004062 |
1 |
0.0004062 |
0.7779746 |
0.4117 |
|
AB^2 |
0.0014738 |
1 |
0.0014738 |
2.8230131 |
0.1439 |
|
Residual |
0.0031325 |
6 |
0.0005221 |
|
|
|
Lack of Fit |
0.0021052 |
1 |
0.0021052 |
10.246877 |
0.0240 |
|
Pure Error |
0.0010273 |
5 |
0.0002055 |
|
|
|
Cor Total |
0.0508598 |
19 |
|
|
|
According to Table 2, test reliability was smaller than 0.05 for the RSM Proposed model. There is a significant difference between the effects of different variables on magnetic saturation. Hence, it can be concluded that silver nitrite, silitin, and UV radiation can have a significant effect on optimization of magnetic saturation of in-situ impregnated polyester fabric with silica / Kaolinite / silver nanocomposite. Since F-statistic parameter for silitin is higher than the F-statistic of model, silitin content has a greater impact on magnetic saturation.
Figure 20 shows magnetic saturation of the optimized specimen. The maximum magnetic saturation belongs to the optimum specimen (41.5599×10-3 emu/g).
Table 3. ANOVA results of air permeability for polyester impregnated with nanocomposite
|
ANOVA for Response Surface Cubic Model |
|||||
|
Source |
Sum of Squares |
Df |
Mean Square |
F Value |
p-value |
|
Model |
714.3922 |
13 |
54.95324 |
4.549858 |
0.0366 |
|
A-silver |
504.6665 |
1 |
504.6665 |
41.7839 |
0.0007 |
|
B-silitin n 85 |
18.41031 |
1 |
18.41031 |
1.524283 |
0.2631 |
|
C-UV |
17.81448 |
1 |
17.81448 |
1.474951 |
0.2702 |
|
AB |
41.74695 |
1 |
41.74695 |
3.456442 |
0.1124 |
|
AC |
2.414503 |
1 |
2.414503 |
0.199909 |
0.6705 |
|
BC |
6.399253 |
1 |
6.399253 |
0.529827 |
0.4941 |
|
A^2 |
0.88472 |
1 |
0.88472 |
0.073251 |
0.7957 |
|
B^2 |
11.89996 |
1 |
11.89996 |
0.985258 |
0.3592 |
|
C^2 |
74.70396 |
1 |
74.70396 |
6.18512 |
0.0474 |
|
ABC |
0.962578 |
1 |
0.962578 |
0.079697 |
0.7872 |
|
A^2B |
0.020082 |
1 |
0.020082 |
0.001663 |
0.9688 |
|
A^2C |
22.18956 |
1 |
22.18956 |
1.837186 |
0.2241 |
|
AB^2 |
332.8406 |
1 |
332.8406 |
27.55757 |
0.0019 |
|
Residual |
72.46807 |
6 |
12.07801 |
|
|
|
Lack of Fit |
19.00139 |
1 |
19.00139 |
1.776937 |
0.2400 |
|
Pure Error |
53.46668 |
5 |
10.69334 |
|
|
|
Cor Total |
786.8602 |
19 |
|
|
|
Table 4. ANOVA results of friction for polyester impregnated with nanocomposite
|
ANOVA for Response Surface Quadratic Model |
|||||
|
Source |
Sum of Squares |
Df |
Mean Square |
F Value |
p-value |
|
Model |
0.0074633 |
9 |
0.0008293 |
3.5755005 |
0.0299 |
|
A-silver |
1.568E-05 |
1 |
1.568E-05 |
0.0676242 |
0.8001 |
|
B-silitin n 85 |
0.0037504 |
1 |
0.0037504 |
16.170712 |
0.0024 |
|
C-UV |
0.0004654 |
1 |
0.0004654 |
2.0068058 |
0.1870 |
|
AB |
8E-06 |
1 |
8E-06 |
0.0344937 |
0.8564 |
|
AC |
2E-06 |
1 |
2E-06 |
0.0086234 |
0.9278 |
|
BC |
0.00005 |
1 |
0.00005 |
0.2155854 |
0.6524 |
|
A^2 |
0.001235 |
1 |
0.001235 |
5.3248015 |
0.0437 |
|
B^2 |
0.0005014 |
1 |
0.0005014 |
2.1617937 |
0.1722 |
|
C^2 |
0.0019836 |
1 |
0.0019836 |
8.5525459 |
0.0152 |
|
Residual |
0.0023193 |
10 |
0.0002319 |
|
|
|
Lack of Fit |
0.0021773 |
5 |
0.0004355 |
15.332861 |
0.0047 |
|
Pure Error |
0.000142 |
5 |
0.0000284 |
|
|
|
Cor Total |
0.0097826 |
19 |
|
|
|
Table 5. ANOVA results of drop absorbtion for polyester impregnated with nanocomposite
|
ANOVA for Response Surface Cubic Model |
|||||
|
Source |
Sum of Squares |
Df |
Mean Square |
F Value |
p-value |
|
Model |
32734.205 |
13 |
2518.016 |
4.071171 |
0.0474 |
|
A-silver |
1800 |
1 |
1800 |
2.910271 |
0.1389 |
|
B-silitin n 85 |
60.5 |
1 |
60.5 |
0.097817 |
0.7651 |
|
C-UV |
4512.5 |
1 |
4512.5 |
7.295887 |
0.0355 |
|
AB |
66.125 |
1 |
66.125 |
0.106912 |
0.7548 |
|
AC |
55.125 |
1 |
55.125 |
0.089127 |
0.7754 |
|
BC |
91.125 |
1 |
91.125 |
0.147332 |
0.7143 |
|
A^2 |
1082.0835 |
1 |
1082.084 |
1.749531 |
0.2341 |
|
B^2 |
521.15357 |
1 |
521.1536 |
0.84261 |
0.3941 |
|
C^2 |
14271.835 |
1 |
14271.84 |
23.07495 |
0.0030 |
|
ABC |
21.125 |
1 |
21.125 |
0.034155 |
0.8595 |
|
A^2B |
5541.9361 |
1 |
5541.936 |
||
Here, 20 characteristic values of silica/Kaolinite/silver nanocomposite were optimized for polyester fabric coating. Designed copies were all in-situ impregnated on the olyester fabric. Physical/chemical properties of as-prepared pure and modified nanocomposites were investigated using MAPPING/EDX and FESEM and FTIR analysis. Moreover, FESEM and Mapping images revealed the presence of nanoparticles on the polyester fabric. EDX and FTIR analyzes also confirmed that nanocomposite particles were impregnated on the polyester fabric. This research done tochange the performance of the polyester fabric by using the nano composite. The experimental results from magnetic saturation test indicated that the optimized nanocomposite can increase magnetic saturation up to 41.559E-3 (emu / gr). Silica and Kaolinite can maintain magnetic property after being placed under a magnetic field. So, these minerals can increase the magnetic saturation by attaching silver along with combining in-situ polyester fabric. Optimized Polyester fabrics, depending on coating materials, can increase their mechanical properties which is very useful for producing the garments and apparel. After impregnation of polyester fabrics, some properties like thickness, strength, abrasion resistance, water permeability, bending and CRA were enhanced. It can affect the fabric comfort because of this fabric can use for formal apparels so these results showed that comfort system of the fabrics were accepted. In addition, UV light exposure time have a significant effect on reducing fabric friction. With increasing in silver nitrate content, air permeability and bending increased which can enhance comfortability. These properties can be fine for making special clothes with comfort properties to protect the people body from EMP, EMR and EMT waves. Furthermore, using statistical software to forecast the variables effects on each other is very important because researchers can get help and understand their situation and terms of the materials. PLS- SEM is one of the best statistical software which can do it very well. In this research results showed that chemical and textile engineering can use the software very easy to check and improve the researcher’s job. This solution will make the way of the projects in the industrial sizes easier.
The author(s) received no financial support for the research, authorship, and/or publication of this article.
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