Nanofibers Membrane Loaded with Titanium Oxide and Rifampicin as Controlled Drug Delivery System for Wound Dressing Applications

2.1 Materials

Materials used in this research are Chitosan (CS, with M.W. 161g/mol molecular weight) was purchased from Glentham (United Kingdom). Poly (vinyl alcohol) 124 (PVA-124, 88% hydrolyzed, Mw~67,000), Astic Acid 98-100% from Merck and Nano titanium dioxide, were purchased from Sky Spring Nanomaterials (USA), phosphate buffer saline (PBS), pH=7.4 The lysozyme (LZ) obtained from Sigma (USA) has a protein content of at least 90% and an activity level of at least 40,000 U/mg. The CDH (India) is the source of this product.

2.2 Preparation of PVA/Chitosan solutions

To prepare a nanofiber membrane with an electrospinning device, dissolve eight percent polyvinyl alcohol (PVA) in distilled water at 60 degrees Celsius. This is the first step in the preparation process. After that, the mixture is agitated for two hours. Furthermore, a solution with a 2% weight percent chitosan concentration was made by dissolving chitosan (CS) in a solution containing 2% weight of acetic acid. By combining liquids in a weight ratio of 85-15 weight percent and adding TiO₂ NP at three distinct concentrations (0.2, 0.4, and 0.6), the PVA-CS ratio was ascertained.

For an hour, the solution was constantly stirred. First of all, the makeup of the samples is explained in depth in this document. With this particular mix, electrospun fiber synthesis was carried out. This membrane was made using electrospinning apparatus, which involved pumping a polymer solution into a needle gauge 18 from a 10mL syringe. There was an 18kV voltage. The electrospinning process was run at 22±2℃, room temperature. A 12.5cm tip-to-collector distance was chosen. A flow rate of 0.5mL/h was used. Table 1 displays the makeup of the film blends after the produced nanofibers were dried at room temperature prior to additional examination.

Table 1. Code samples and their related chemical compositions

2.3 Fourier transform infrared spectroscopy

The vibration of functional groups in blended films was measured using FTIR microscopy (Bruker, Germany).

2.4 Characterization of morphology by (FESEM) field emission scanning electron microscopy and (EDX) energy dispersion X-ray spectroscopy

Mira 3-XMU FE-SEM was used to analyze the scaffolds' morphology after they were created. Before being examined with FESEM at 15KV accelerating voltage, the specimens have been gold plated (10nm) through sputtering. Fiber diameter and pore size were quantified in FESEM images using the Image j program.

2.5 Wettability test

When a drop of water rests on a lotus leaf, the Contact Angle (CA) it takes is often more than 160 degrees. The term "hydrophobic" has been in use since antiquity to characterize a solid surface's reluctance to hold liquid. The textile business, packaging, coating industry, bio-engineering, electrical devices, and medication delivery are just few of the many fields that might benefit from hydrophobic surfaces [5]. The angle that a liquid creates with a solid, known as the Static Contact Angle, is the most crucial feature in identifying superhydrophobic materials. The surface is hydrophilic if the water static contact angle (CA) is less than 90 degrees, hydrophobic if it is between 90 and 150 degrees, and superhydrophobic if it is greater than 150 degrees [6].

2.6 Degree of Swelling

The swelling degree of blended films was evaluated using the ASTM D4546-08 15 standard. The films were immersed in a phosphate-buffered saline (PBS) solution at pH 7.2 for 24 hours at room temperature. The mixed films were removed once they had become swollen, and the excess solution was drained using filter paper. Eq. (1) was used to determine the degree of swelling.

$Degree\ of\ swelling(\%)=\frac{(w 2-w 1)}{w 1} * 100$                    (1)

where, w1, w2 were: weights of dried, swollen samples, respectively.

2.7 Degradation rate

Blended films were immersed in a phosphate-buffered saline (PBS) solution containing lysozyme enzyme at a concentration of 0.0001g/L by ASTM F1635-04a 16. And kept in a 37℃ incubator for a month. Every three days, we would restart the solution. Films were bleached in solution, rinsed in phosphate-buffered saline (PBS), dried, and weighed once weekly.

Degradation rate was determined by the Eq. (2). [10]

$Weight\ loss (\%)=\frac{(w 0-w 1)}{w 0} * 100$                    (2)

where, w0 is the dry weight before degradation and W1 is the dry weight after degradation.

2.8 Antimicrobial activity

The agar well diffusion assay [11] was used to test the antibacterial properties of the produced Samples (1 to 6) against Gram's negative and Gram's positive bacterial strains. Muller-Hinton (MH) agar, in a volume of around 20mL, was placed sterilely on Petri plates. The bacterial strains were taken from their respective stock cultures with the use of a sterile wire loop [12]. After the organisms were cultured, wells were drilled with a sterile point into the agar plates at a diameter of 6mm. Different concentrations of the Samples (from 1 to 6) were injected into the drilled wells. After incubating the culture plates containing the Samples (1-6) and the test organisms at 37℃ for a full 24 hours, the average diameter of the zones of inhibition were measured and recorded [13].

2.9 In vitro cytotoxicity

The fibroblast vitality on the produced nanofibrous mats was assessed using the MTT test. Under usual conditions of 37℃ and 5% CO₂, the cells were grown in DMEM media supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin antibiotic. Every experiment was run three times for the 24 hours, 48 hours, and 72 hours of culture time that were indicated. We carried out a number of tests in order to improve the appraisal and assessment of biocompatibility [14].

First, we used the MTT to assess the cytotoxicity. Then, using fibroblast (L929) cells and the cell counting kit-8 (CCK-8) method, we assessed the strength and rate of cell division. Compared to MTT, MTS, or XTT, or other tetrazolium salts, the CCK-8 test is more sensitive. With the use of this analytical method, colorimetric assays with a high degree of sensitivity may be used to determine the number of living cells in proliferation tests and evaluate cytotoxicity [15, 16].

The normalized relative viability or cell growth (%) was calculated from the following equation:

For calculation of cell viability [14]:

$Survival\ rate\ \%=\frac{A S-A C}{A C} * 100$                    (3)

As: Mean absorbance of each sample

Ac: Mean absorbance control

$Cytotoxicity\ rate=100-Survival\ rate$                    (4)

2.10 In vitro drug release

Using UV spectrophotometry at 237nm, the release of rifampicin from samples with and without the addition of nanopowder was investigated. 500 μL of saline phosphate buffer (PBS) was added to two samples per condition, which were then evaluated and put on 24-well plates to assess the release of rifampicin. 500 μL of solution were taken from each well for the absorbance measurement after 1, 4, 24, 48, and 72 hours, and at each time point, fresh PBS was used in place of the release solution. The plates were kept moist and incubated at 37℃ in the absence of light to prevent PBS evaporation. Since ε237 nm is equal to 33 200, the released rifampicin was quantified using the Lambert-Beer equation and normalized on 5mg of the membrane [17].

2.11 Mechanical properties

Nanoindentation experiments were conducted using a Hysitron TriboLabs nanomechanical testing system equipped with a two-dimensional force-displacement detector. The transducer has a range of 1-10,000μN and can apply loads with a high load resolution of 1nN. In addition, it records a maximum penetration depth of 3000nm (3μm) and has a resolution of 0.04nm. H and Er values are measured using a three-sided pyramidal Berkovich diamond indenter with a 120nm radius of curvature. Before starting any experiments, fused silica, a reference material, is used for calibration to determine the tip radius (tip area function). The investigations are conducted in a controlled atmosphere with a temperature of 23℃ and a relative humidity of around 45% [18].

4.1 Fourier-transform infrared (Ftir) analysis

The FTIR spectra recorded from the samples are shown in Figure 1. Figure 1 (A) displays the unmixed chitosan spectrum. N-H and C-H stretching are responsible for the peaks at 2922.87 and 2874.07cm. The N-H stretching in amide II is responsible for the peak at 1630.38cm. The characteristic PVA spectrum is clearly seen in Figure 1 (B).

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Figure 1. Fourier Transform Infrared Spectroscopy (FTIR) Analysis A) cs; B) PVA; C) PVA+cs

Bonds between oxygen and hydrogen (at 2946.71cm) and carbon and hydrogen (at 2879.52cm) produce those spectral bands. As can be seen in Figure 1 (C) [18] when chitosan is added to PVA, a new peak appears at 1721.82cm, indicating interaction between O-H (for PVA) and N-H (for chitosan).

As can be seen in Figure 2, The improved properties of the mix can be due to the interactions between chitosan and PVA, specifically the aggregation of side chains with hydrophobic properties and the formation of intermolecular and intramolecular hydrogen bonds. [19, 10].

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Figure 2. CS and PVA interaction [10]

From Figure 3, all of the expected peaks could be seen clearly once TiO₂ was included, demonstrating that the two materials are chemically compatible [20]

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Figure 3. Fourier Transform Infrared Spectroscopy (FTIR) Analysis: A) PVA+CS; B) PVA+CS/0.02TiO₂; C) PVA+CS/0.04TiO₂; D) PVA+CS/0.06TiO₂

4.2 Nanofiber diameter and distribution

The PVA/CS exhibits an average pore size of 267.064nm and an average fiber diameter of 48.093nm that illustrated in Figure 4 (a). The FESEM micrographs of the PVA/CS nanofiber modification with TiO₂ nanoparticle addition are displayed in Figures 4 (b) and (c). The fiber's morphology remained unchanged upon the addition of TiO₂ nanoparticles; it exhibited a distinctive ribbon structure with few bead defects. The average fiber diameter and pore size of PVA/CS+0.02 TiO₂ were measured at 126.466nm and 277.105nm, respectively. Figure 4 (c) show FESEM micrographs of the PVA/CS+TiO₂ 0.4gm, which exhibit an increase in fiber diameter as a result of the particle embedding and the random distribution of TiO₂ particles among PVA: CS fibers, average fiber diameter (100.157) nm and the average pore size (620.463) nm.

Figure 4 (d) shows the FESEM micrographs of the PVA/CS+TIO₂ 0.6gm, Since the particles in this scenario are nanometric in size, they have a greater propensity to agglomerate and adhere in the form of aggregates to the polymeric fibres, which has a detrimental impact on the sample's homogeneity across broad regions, the average fibre diameter of PVA/CS modification is (267.1659) nm and the average pore size to be (559) nm.

FESEM micrographs of the (PVA/CS nanofibers)+RIF can be shown in Figure 4 (e). The inclusion of RIF in composite nanofibers significantly reduced the diameter of PVA nanofibers, average fibre diameter is (57) nm for the PVA/CS blend+RIF, across all layers, the morphology reveals a web of random, non-woven, one-dimensional polymeric structures [21]. the potential for a reduction in nanofiber width due to the incorporation of polar components, with an average pore size of 831.591nm.

Figure 4 (f) show the FESEM micrographs of the PVA/CS+TiO₂ 0.4gm+RIF, an average fibre diameter of PVA/CS+TiO₂ 0.4gm+RIF modification, was found to be (133.3407) nm, that means increase fibre diameter when computation because adding TiO₂ as nanoparticles. with average pore size (336.916) nm [22].

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Figure 4. Fiber diameter and pore size of A) PVA+CS; B) PVA+CS/0.2TiO₂; C) PVA+CS/0.4TiO₂; D) PVA+CS/0.6TiO₂; E) PVA+CS+RIF; F) PVA+CS+0.4TiO₂+RIF

4.3 Wettability test

All the contact angle data was the average of seven readings taken at various positions on the surface, and the water contact angles were determined using the low bond axisymmetric drop shape analysis technique [10] The surface was splattered with a single drop of water. A high-speed CCD camera was used to record this procedure at 35 frames per second [23].

Figure 5 displays the contact angle values of PVA+CS (about 75° degrees). Because TiO₂ is hydrophilic, the contact angle values for (PVA+CS) TiO₂ were reduced. After 10 minutes, observed values of (60°) were seen for (PVA+CS) TiO₂, when liquid was released over these nanofibrous scaffolds. Contact angles were reduced, although only slightly, in a (PVA+CS) TiO₂+RIF nanofibrous scaffold. The value dropped to (55°) degrees.

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Figure 5. Scaffold standard deviations of contact angle values

4.4 Antibacterial activity

The data were statistically analyzed using GraphPad Prism [24]. The average and standard deviation (mean ± SD) of three different tests is used to illustrate the data. Indicate a significant difference at the 0.05 significance level (p<0.05) [25]. The results of antibacterial activity at various concentrations are shown in Table 3, illustrated the inhibition zone against E. coli bacteria.

Table 3. Antibacterial activity (inhibition zone)

4.5 The swelling tests

Figure 6 displays the results of testing that are noted increasing swelling capacity for the membrane when TiO₂ as a nanoparticle because the increasing surface area means increased absorption of water then promotes a higher swelling rate, and TiO₂-NPs in the membrane is hydrophilic, which is important to assist for quick absorption of exudates. Better absorption of exudates will keep wounds dry and prevent airborne infection [24, 26].

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Figure 6. Swelling tests analyses

4.6 Degradation test

Decomposition should occur and new skin is produced. Cross-linked TiO₂ degradation of (PVA+CS). Tissue engineering relies heavily on in vitro biodegradation as a measuring stick. For the enzyme to degrade the film, it must penetrate the film's surface and react with the polymer mixture.

It is evident from the data that the PVA/CS membrane degrades more quickly than the PVA/CS/TiO₂ membrane. This is because the addition of TiO₂ nanoparticles to the polymer matrix strengthens it, giving the membrane reinforcement and rigidity [27, 28].

After one week, two weeks, and three weeks in PBS medium, all of the as-fabricated bandages degraded by 24-45%, 39%-48%, and 45-70%, respectively. TiO₂NPs slowed down the pace at which the composite bands degraded. This may be the reason why TiO₂NPs react with CS/PVA bandages [29] shown by the Figure 7.

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Figure 7. Weight loss of samples

4.7 Cell viability

The evaluation of viable fibroblasts was accomplished using the MTT assay, which assessed the in vitro cell proliferation across six separate samples. Figure 8 shows the cell viability on different nanofibrous samples at 24 hours, 48 hours, and 72 hours.

Cell culture plates without any nanofibrous material were used as controls. Significantly, compared to the control cultures (cells grown on the plastic surface of the culture plate), the proliferation and vitality of L929 cells on the membranes exceeded those in the former. Furthermore, it was noted that fibroblast cells showed the highest proliferation and survivability of all the created composite membranes. The greater surface area accessible on composite membranes in comparison to standard cultures may be the cause of this improved responsiveness. However, the cell attachment was significantly increased for all the mentioned periods and that indicates no-cytotoxic excretion for all membranes [30, 31].

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Figure 8. MTT assay for the evaluation of viability of cells cultured on the samples

4.8 Drug release properties of RIF loaded (PVA+CS) and (PVA+CS)+TiO₂ nanofiber membranes

Since Rif, CS, PVA, and TiO₂ are water-soluble compounds, they can be rapidly dissolved in aqueous solutions, leading to a significant initial bursting at short periods. It reached equilibrium two hours into the release. The inner medicines eventually diffused to the buffer solutions through the carrier as the PVA+CS+TiO₂ nanofiber membranes swelled in the buffer solutions and finally reached release equilibrium. Due to the ability of TiO₂ nanoparticles to influence drug delivery, RIF release is greater when a drug is loaded in (PVA+CS)+TiO₂+RIF compared to (PVA+CS)+RIF (as shown in Figure 9) [32].

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Figure 9. Rifampicin release kinetic from (PVA+CS) and (PVA+CS)+TiO₂ membrane

4.9 Analysis of the samples using nanoindentation

To treat burn wounds, many synthetic and natural polymer materials have been developed; however, as Table 4 illustrates, their use is frequently limited by their poor mechanical qualities and slow rates of water absorption. In the context of treating burn wounds, improvements in mechanical qualities have been put into place to overcome these constraints.

In this study nanoindentation tests can be noticed in the elongation-force curve, which is equivalent to the Stress-strain curve in Figures 10 and 11. The load-unload curves for the chitosan (CS), polyvinyl alcohol (PVA), and chitosan-polyvinyl alcohol (CS+PVA) are shown in Figure 10, It is seen that increased Mechanical properties through blend Cs with PVA. When compared with cs alone and in Figure 11 observed adding 0.2wt.% TiO₂, caused an increase in Mechanical properties, it is noticed that by adding TiO₂ to the CS+PVA membrane, the mechanical properties will increase [33, 34].

Table 4. Mechanical properties of the sample

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Figure 10. Load-unload curves at A: (CS); B: (PVA); C: CS+PVA)

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Figure 11. Load-unload curves at A: (CS+PVA); B: (CS+PVA)+TiO₂

It is clear from Figure 12, which shows lowered modulus and hardness, that adding less TiO₂ nanoparticle content causes the membranes' hardness to climb as TiO₂ content does.

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Figure 12. A: Hardness values of samples; B: reduced modulus (Er) values of samples.

Up to 0.2 weight per cent of TiO₂, the composite's increased decreased modulus shows a linear increase. However, the hardness of the (PVA+CS)+nTiO₂ nanocomposite membranes decreases with additional increases in TiO₂ nanoparticle content (0.4 and 0.6 wt.%). A lower weight % of TiO₂ nanoparticles has a more noticeable reinforcing effect, increasing the tensile modulus and preventing polymer stretching.

When compared to the pure (PVA+CS) membrane, the (PVA+CS) membrane containing 0.2 weight per cent TiO₂ nanoparticles exhibits greater hardness [35]. This is explained by the fact that the high surface energy of the nanoparticles causes them to aggregate easily, leading to poor dispersion in the polymer matrix. This tendency becomes much more pronounced with an increase in TiO₂ content, which causes TiO₂ aggregates to develop inside the polymer matrix. By serving as concentration points for tension, these aggregates prevent stress from moving from the polymer matrix to the fillers. As a result, the dispersion of TiO₂ in the (PVA+Cs) polymer matrix is more uniform at lower percentages of TiO₂ concentration. The result is enhanced mechanical properties, including a more even distribution of stress, a decrease in the formation of stress-concentration points, and an increase in the contact area for stress transfer between fillers and the polymer matrix [7].

4.10. Taguchi results

4.10.1 (DOE) Design of experimental

Four distinct experiments are carried out for each test condition in a total of 16. Trials containing experiments under the previously mentioned parameters. The Hardness findings and decreased modulus (Er) are displayed in Table 4.

The smaller-the-best principles, which are utilized to assess the ideal condition connected to the lowest hardness value, were included in the research. The graphical representations presented in Figure 13 are employed to determine the optimal set of parameters. Based on these charts, the maximum force (µN) at level 4 (185.6µN) produced the most successful result, the contact area (3.06) at level 1, the control factor of Reinforcement (g) at level 3 (0.6) produced the best result, and the contact stiffness (µN/nm) control factor (7.8) produced the best result at level 4 max depth (124.2nm) at level 2, and Figure 14 displayed Response Optimisation hardness (Gpa) [36].

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Figure 13. Taguchi Inspection: Main effects plot for Hardness: smaller is better

On the other hand, the greatest modulus of elastase Er-which would be the ideal condition for this study-is found using the greater is better criteria. The best combination of parameters is found using the charts in Figure 14. Based on these charts, the best outcome was obtained with the control factor of Reinforcement (g) at level 1 (0.2). While the maximum depth (468.7nm) at level 4, the maximum force (µN) at level 1 (113.6µN) offered the best result, and the contact area (3.06) at level 1, Figure 13 shows the respond optimization modulus of elastase Er (Gpa), the contact stiffness (µN/nm) control factor (7.8) gave the best result at level 4.

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Figure 14. Taguchi Analysis: Main effects plot for Mean of Means for Er smaller is better

4.10.2 Analysis of Variance (ANOVA)

A study was conducted to determine the process parameters that have significant effects on the response variable. The error sum of squares was combined and the findings of the Hardness and elastic modulus Er test percentage were examined using an ANOVA method. The factors and levels in designing a factorial design are summarized in supplementary Table 5 and Table 6 [37], the model created by analysis of variance (ANOVA) in Eq. (5) for Hardness and Eq. (6) for elastic modulus. Table 7 illustrated Taguchi L16 orthogonal array of designed experiments.

Regression Equation

$\begin{aligned} & \text { Hardness }=\mathrm{a} 0-\mathrm{a} 1 \times 192.2+\mathrm{a} 2 \times 1124.2+\mathrm{a} 3 \times 1289.3\\&-\mathrm{a} 4 \times 1 \_468.7+\mathrm{b} 1 \times 2 \_3.06+\mathrm{b} 2 \times 2 \_3.48-\mathrm{b} 3 \times 2 \_5.99-\\&\mathrm{b} 4 \times 2 \_6.54-\mathrm{c} 1 \times 3 \_113.6-\mathrm{c} 2 \times 3 \_147.2+\mathrm{c} 3 \times 3 \_179.0\\&+\mathrm{c} 4 \times 3 \_185.6+\mathrm{d} 1 \times 4\_1.3-\mathrm{d} 2 \times 4 \_5.5+\mathrm{d} 3 \times 4 \times 6.5\\&-\mathrm{d} 4 \times 4\_7.8+\mathrm{e} 1 \times 5\_0.2-\mathrm{e} 2 \times 5\_0.4+\mathrm{e} 3^* \times 5\_0.6\end{aligned}$                    (5)

A: max depth(nm); B: contact area(nm²); C: max force(µN); D: contact stiffness(µN/nm); E: reinforcement content (g).

$\begin{gathered}\text { Elastic modulus. } \mathrm{Er}=\mathrm{a} 0+\mathrm{al} \times 1 \_92.2-\mathrm{a} 2 \times 1 \_124.2-\mathrm{a} 3 \\ \times 1 \_289.3+\mathrm{a} 4 \times 1 \_468.7+\mathrm{b} 1 \times 2 \_\mathrm{b} 1 \mathrm{~b} 1 \times 2 \_3.48-\mathrm{b} 1 \\ \times 2 \_5.99-\mathrm{b} 2 \times 2 \_6.54+\mathrm{c} 1 \times 3 \_113.6-\mathrm{c} 2 \times 3 \_147.2-\mathrm{c} 3 \\ \times 3 \_179.0-\mathrm{c} 4 \times 3 \_185.6-\mathrm{d} 1 \times 4 \_1.3+\mathrm{d} 2 \times 4 \_5.5+\mathrm{d} 3 \\ \times 4 \_6.5+\mathrm{d} 4 \times 4 \_7.8+\mathrm{e} 1 \times 5 \_0.2-\mathrm{e} 2 \\ \times 5 \_0.4-\mathrm{e} 3 \times 5 \_0.6\end{gathered}$                    (6)

A: max depth(nm); B: contact area(nm²); C: max force(µN); D: contact stiffness(µN/nm); E: reinforcement content (g).

Table 5. Component of Eq. (3)

Table 6. Component of Eq. (4)

Table 7. Taguchi L16 orthogonal array of designed experiments

4.10.3 Analysis of Variance and Percentage Contribution

An analysis of variance (ANOVA) was conducted to assess the statistical significance of each parameter. ANOVA can be employed for a quantitative study of control factors and their impact on the properties of the end product. This analysis helps determine the percentage contribution of control factors to the hardness and elastic modulus (Er) of the products.

The ANOVA analysis results indicate that the contact area (measured in nm²) is a significant factor in the process of determining hardness., with a contribution of 67%, followed by max force(µN)with a contribution of 28%, but considered Contact stiffness(µN/nm), reinforcement content (g) and max depth (nm²) not significantly factor with contribution (2.8%) (0.8%), (0.1%) respectively illustrated that in (Table 8).

The results indicate that the mechanical properties, specifically hardness, are mostly influenced by the contact area (measured in nm²) and maximum force (measured in µN) [36]. therefore, can be negligible contact stiffness, reinforcement content (g) and max depth(nm), from the model because not significantly factor, the model became as in Eq. (7):

$\begin{aligned} \text { Hardness (Gpa) }= & b 1 \times 2 \_3.06+b 2 \times 2 \_3.48 \\ & -b 3 \times 2 \_5.99-b 4 \times 2 \_6.54 \\ & -c 1 \times 3 \_113.6-c 2 \times 3 \_147.2 \\ & +c 3 \times 3 \_179.0+c 4 \times 3\_185 .6\end{aligned}$                    (7)

The ANOVA analysis results for the elastic modulus (Er) reveal that contact stiffness is a crucial factor in the process, contributing significantly at 50%. Following this, the maximum depth (nm) contributes 17%, while the contact area (nm²) is not considered a significantly influential factor, with a contribution of 9%. Other factors such as maximum force (µN) and reinforcement content (g) contribute 12% and 10%, respectively, as illustrated in Table 9. These results for elastic modulus Er are being more influenced by the contact stiffness (µN/nm) and max depth (nm) [38], therefore can be negligible, contact area (nm²), max force (µN) and reinforcement content (g) from the model because not significantly factor the model became as Eq. (8):

$\begin{aligned}

\mathrm{Er}=a 1 \times 1 \_92.2 & -a 2 \times 1 \_124.2-a 3 \times 1 \_289.3 \\

& +a 4 \times 1 \_468.7-d 1 \times 4 \_1.3 \\

& +d 2 \times 4 \_5.5+d 3 \times 4 \_6.5 \\

& +d 4 \times 4\_7.8

\end{aligned}$                    (8)

Table 8. Illustrated Analysis of Variance for Hardness (Gpa)

Table 9. Analysis of Variance for Er

4.10.4 Estimating the performance properties in optimal conditions

The distribution of data can be effectively analyzed and modelled using a linear regression equation. A statistical model is developed utilizing linear regression equations by using Taguchi's orthogonal array and MINITAB software. Each material combination test is represented using a linear regression equation that accounts for all of the constituent parts. To determine the necessary outcomes and percentage of variability, the values of the response test combinations for the hardness test are calculated using the linear regression equation. For every test, Figure 15 shows the residual errors together with the associated R-square values. On the other hand, it is noted that the hardness response may be measured with the same set of conditions and provide a value of 98.21%. As a consequence, the outcome suggests that the parameters are statistically appropriate for the optimization study [8, 39].

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Figure 15. (A) Regression prediction plots of hardness (Gpa); (B) Regression prediction plots of elastic modulus (Gpa)

4.10.5 Response surface plot of hardness

The 3-D surface plots in Figure 16 illustrate the combined impact of reinforcement content (g), contact stiffness (µN/nm), maximum force (µN), contact area (nm²), and maximum depth (nm). When calculating the optimal values for these variables, a crucial factor to take into account is the surface response. remarkably, all surface plots exhibit convex forms, indicating that the independent variables are carefully chosen. As indicated by a p-value<0.05, it is found that increasing the contact area (nm²) and Max force (µN) significantly has affected hardness. A smaller hardness is obtained when a high contact area (6.45nm²,) while a lower Max force (113µN) was obtained this is illustrated in Figure 16 (A). while in Figure 16 (B) obtained smaller hardness (0.2) with contact area(6.45nm²), contact stiffness (7.8µN/nm).

Whereas can be obtained higher value for Er (4.03Gpa), with Max depth (92.2nm) and contact stiffness(7.8µN/nm) this is illustrated in Figure16 (C), in Figure 16 (D) optimum value of elastic modulus Er (3.69Gpa) vs max depth(469nm), contact stiffness (7.8 µN/nm) [40].

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Figure 16. A) surface plot of hardness (Gpa) vs contact area (nm²), max force (µN); B) surface plot of hardness (Gpa) vs contact area (nm²), contact stiffness (µN/nm); C) surface plot of elastic modulus Er (Gpa) vs max depth(nm), Contact stiffness (µN/nm); D) surface plot of elastic modulus Er (Gpa) vs contact stiffness, contact stiffness (µN)

“Thanks for laboratories of Materials Engineering, University of Technology-Iraq, Baghdad.”