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Abstract

A new approach for functional finishing of cotton fabric using copper oxide nanoparticles and the phenolic compound of Azolla nilotica algae extract synergistically. In this sense, green synthesis nanoparticles have gained enormous attention in today’s world due to the ongoing demand to develop risk-free and high-efficiency functional cotton fabric compared to other methods. This study carried out the green synthesis of CuONPs with algae extract as a reducing agent and CuSO4 as a metal precursor. Phenolic compounds were prepared from algae extract through liquid-phase separation and combined with CuONPs to enhance the functionality of cotton. CuONPs were characterized using X-ray diffraction (XRD), a scanning electron microscope (SEM), FTIR spectral analysis, and a UV-vis spectrophotometer. The average particle size obtained was 21.59 nm. Optimization of process parameters for treating cotton fabric with CuONPs and phenolic compounds of algae extract was done using Box Behenken Design through the dip coating method. Finally, the fabric was evaluated for its multi-functionality in terms of antibacterial activity and percent blocking of ultraviolet radiation. From the optimization solution, the optimum values of 27.625 mm Zone of inhibition (ZOI) for gram-negative bacteria, 23.88 mm ZOI for gram-positive bacteria, and percent blocking of ultraviolet radiation with a value of 99.99% were obtained. In summary, the combination of CuONPs and phenolic compounds in Azolla notica algae extract possesses excellent potential for the functionalization of cotton fabric without affecting its comfort properties. Hence, they can be used as an inexpensive, promising, and efficient alternative for functional purposes.

Keywords

Synergy copper oxide nanoparticles green synthesis Azzola nilotica algae multifunctional

Introduction

Cotton is the most commonly used natural cellulosic fibrous material for textile and apparel manufacturing; however, due to its inherently nutritious and hydrophilic properties, cotton fiber provides an excellent environment for the growth of bacteria,¹ and fungi. Furthermore, due to the more ideal conditions that cotton fabrics provide for the growth of microorganisms like bacteria and fungi, they are more susceptible to microbial degradation than synthetic fibers. This can lead to a decline in the strength of the textile, unpleasant odors, allergic reactions, and hygiene and health problems.² They do not have an effective barrier to UV radiation, especially when dyed in light shades.³ Therefore, the growing consumer demand for improved functions in conventional textile products drives the modification of these fibers. Nowadays, textile materials undergo numerous finishes to impart multiple functions for different applications, such as sportswear, construction, medical, hygiene, transportation, and agriculture.⁴ Antimicrobials and antiviral active surfaces, especially textiles, are becoming more and more popular as a result of the growing interest in lowering the quantity of potentially infectious agents on important high-touch surfaces.⁵ Finishing involves modifying, activating, and functionalizing the exterior layers of textile materials. In actuality, the availability of functional textiles sparks innovation for new products that are tailored to the needs of the textile industry.⁶ Modification of cotton fabric using nanomaterials has been found to play an important role in developing protective properties against pathogenic bacteria,⁷ and UV radiation.⁸ In literature, previously plant extracts,⁹ Phenolic compounds of microalgae have been used for anti-inflammatory, antioxidant, and antimicrobial properties, among others,^10,11 and organic compounds have been used for functional finishing purposes.^12,13 The extraction of nanoparticles from the desired part of plant was economic or reduced ecological damage and could be considered a more sustainable, cheaper, and environmentally friendly source of phytoreducing agents, and this is a relatively new and unexplored area of nanoscience in textile technology.¹⁴ Furthermore, the aquatic macroalga, Azolla pinnata (azolla), is called floating fern, mostly grown in ponds and backwaters of rivers. In addition, Azolla has wide applications such as fertilizer (a green manure), animal fodder, antioxidant, antiviral, antimicrobial, anticarcinogenic, anti-inflammatory, anti-diabetic, hepato- and gastro-protective, neuro-protective, cardio-protective, and anti-hypertensive effects due to its high content in proteins, flavonoids, hormones, alkaloids, phenols, triterpenoid derivatives, essential amino and fatty acids, vitamins (vitamin A, vitamin B12, beta-carotene), growth promoter intermediaries, and minerals.^15,16 For this research based on the literatures,^17,18 Azolla nylotica algae was used to extract sliver oxide nanoparticles for functional finishing.

Therefore, the functionalization of cotton using natural substances of organic and inorganic compounds was studied to impart various properties, including antibacterial,¹⁹ UV protection,²⁰ wrinkle resistance,²¹ hydrophobicity,²² softening,¹² antioxidant properties,²³ and exceptional flame retardancy.²⁴ Copper oxide-titanium oxide nanocomposite for UV protection onto l-methionine-modified cotton fabrics,²⁵ copper oxide, silver oxide, zinc oxide, bacterial celluloses/polyvinyl alcohol/chitosan/copper oxide (BC/PVA/CH/CuO-NPs) nanoparticles,⁹ and silver/copper nanoparticles²⁶ have been used to create multifunctional cotton fabrics. Although organic compounds impart multi-functional properties to cotton fabric, their efficacy is restricted, and they are not environmentally friendly. In addition, these compounds need a cross-linking agent to bind to the surface cotton fabric and have no long-lasting life.²⁷ To overcome problems related to organic compounds, nanotechnology has become a novel discovery for functionalizing cotton fabric without adding a lot of weight, thickness, or stiffness.²⁸ For example, the combined antibacterial action of Ag and copper oxide nanoparticles with distinct functional groups against a range of microorganisms, including those that are multi-resistant, was studied previously.²⁶ However, the combination of metal nanoparticles increases the cost of finishing processes,²⁹ and using phenolic compounds of plant extract alone has low microbial activities.³⁰ The combination of copper oxide nanoparticles³¹ with phenolic compounds of plant extract³² has less cost of finishing than combining with metal nanoparticles. Based on the previously studies, the antimicrobial treated cotton fabrics were used for aprons, lab. coats, bed sheets, wound dressings, bandages, and casual apparel.³³

This study aims to make cotton fabric multifunctional with UV protection and antibacterial properties using the phenolic compounds of Azolla nylotica algae extract and copper oxide nanoparticles through simultaneous application in a synergistic way. The box-Behnken design approach is used to create an ideal formulation for optimization. In this research, in comparison to the one factor at a time approach, Design-Expert software is a very successful statistical tool-based strategy that tests multiple factors at once with fewer experimental runs.

Materials and methods

Materials

The bleached plain woven 100% raw cotton fabric was used for the research (20s of count, 60 EPI (ends per inch), 60 PPI (picks per inch), weight of 135 g/m², and thickness of 0.1 cm). The fabric and chemicals, such as copper sulfate (99.0% pure) and sodium hydroxide (99.8% pure), were supplied by the Bahirdar Textile Share Company (BDTSC), Ethiopia. Other chemicals used for the research, such as ethanol, were purchased from the market, while hexane (99% pure) was obtained from Bahir Dar University’s organic chemistry department. All chemicals used were analytical-grade chemicals. In addition, sample algae were collected from the Abay River and Lake Tana, which are found in Bahirdar, Ethiopia.

Methods

Preparation of plant extract

To prepare fine-sized powder, the collected algae were washed with tap water to remove dirt and dried with sun shad, then powdered using a mixer grinder. The resulting powder was passed through a 250-μm sieve mesh. Then, to prepare the crude extract, 10 g of powder was added to a cylinder containing 100 mL of distilled water with a 1:10 ratio at a temperature of 60°C. The resulting infusion is then filtered thoroughly until there is no insoluble material appears in the broth using Whitman’s high-grade filter paper (No. 1 filter paper).^34,35 The pH level significantly influences the extraction yield and stability of phytochemicals. In the literature,^36,37 different acidic pH was used to extract phenolic compounds. In acidic pH, the interaction between phenolic compounds and solvent is enhanced, leading to higher extraction yields.³⁸ Furthermore, direct studies specifically targeting Azolla nilotica may be limited, and similar studies on other plant materials suggest that maintaining a slightly acidic condition (around pH 3) is likely beneficial for maximizing phenolic extraction from Azolla nilotica leaves as well.^39,40 Therefore, in this research, the pH of the solution was maintained at 3 with continuous stirring for 30 min, and finally, the crude plant was extracted as shown in Figure 1. The yields of extractions were calculated by comparing the weight of the dried sample with the weight of originally dried ground samples.

Y i e l d o f e x t r a c t (%) = \frac{W o}{W p} \times 100

(1)

Where, Wo is the final weight of extract (g) and Wp is the initial weight of extract (g).

Figure 1.

Experimental setup for Azolla nilotica crude extraction processes.

Separation of phenolic compounds from the crude

Liquid-liquid phase separation, which is based on the variations in solubility of the various compounds in various solvents, was utilized to prepare the phenolic compounds and remove contaminants. Many other contaminants, including lipids and chlorophyll, were found in the crude extracts that were recovered after extraction. Shaking with a tiny amount of hexane removes these contaminants. Until there is no more green segment in the extract, the hexane layer holding the green chlorophyll portion is discarded, and the procedure is repeated.⁴¹ Pour the cooled crude algal extract into a separator funnel and add water and hexane in a 3:1 ratio to ensure proper mixing and extraction. Hexane and water are combined in a 70:30 ratio to coat the top layer of the crude extract.^42,43 Letting the mixture settle will allow the layers to separate based on their densities. Hexane, containing the dissolved nonpolar solvents, was the uppermost layer. Remove the uppermost layer of hexane carefully into another container. Dissolved nonpolar solvents should be present in this layer. To get the phenolic compounds, often known as antioxidants, recovery and purification procedures have been carried out to evaporate hexane from the collected layer.⁴⁴

Phytochemical screening

Tests for the presence of different chemical components, such as flavonoids and tannins, are part of the qualitative examination of phytochemicals in plants. The qualitative primary phytochemical screening was done based on the qualitative analysis of the previous literatures done by.⁴⁵ In addition, in the previous studies the Phytochemicals found in Azolla nilotica algae were characterized and the main Phytochemical components of these species are including flavonoids, alkaloids, phenolic compounds, tannins, amino acids, fatty acids, steroids and hormones.⁴⁶ For this research, the FTIR and qualitative characterization were done only for phenolic compounds (hexane-separated extracts). For this research, the FTIR and qualitative characterization were done only for phenolic compounds (hexane-separated extracts). The main objective is to determine which polar compounds are present in the extract after the separation of polar from non-polar of different phytochemical classes such as alkaloids, flavonoids , and tannins are a few of them Table 1.

Table 1.

Qualitative phytochemical screening of Azolla nilotica algae extract.

Phytochemicals	Reagents
Flavonoid	Alkaline reagent test: Utilize 3 mL of plant extract, gradually add 2% NaOH solution, and then dilute HCL with successive drops of NaOH. Next, a yellow hue emerges, signifying the existence of flavonoids
Protein	Biuret test: After making a 2% NaOH and 0.1 M CuSO4 solution, add drop by drop to the 3 mL plant extract. The presence of protein is shown by the color purple
Polyphenol	Sodium hydroxide test: Add a few drops of 2% NaOH solution to the 3 mL of plant extract, red color indicates the presence of polyphenols
Carbohydrate	Iodine test: When starch is added to an iodine solution (iodine dissolved in an aqueous potassium iodide solution), the solution’s hue turns blue-black
Chlorophyll	Visible light observation: To observe the color of the sample under visible light, no reagent is needed. Plant extracts usually have a green tint due to the presence of chlorophyll. Chlorophyll is present in the sample if it appears green
Tannin	Potassium dichromate test: After extracting 3 mL of the plant material, 1 mL of the 10% potassium dichromate solution is added. After a few minutes of reaction, the mixture’s brownish green color indicated the existence of tannins

Characterization

The chemical properties of the extract have been characterized. In the case of chemical property, FTIR was characterized. Qualitative phytochemical screening was done as a characterization for determining the main components.

Synthesis of copper oxide nanoparticles

To prepare CuO nanoparticles, 0.5 mM CuSO4 was dissolved in 100 mL of distilled water within a 500 mL baker at room temperature. Then the algae extract was mixed with CuSO4 solution at a 3:1 (v/v) ratio in a beaker, respectively.⁴⁷ To maintain the pH during extraction of copper oxide nanoparticles, a buffer solution was prepared. To prepare a buffer solution of pH nine for the extraction of copper oxide nanoparticles using plant extraction (Azolla nilotica algae), sodium bicarbonate (0.1MNaHCO₃), weak acid, and sodium hydroxide (0.1MNaOH), which are used for pH adjusting. This buffer can help maintain an alkaline environment suitable for extracting copper oxide nanoparticles from plant materials, as higher pH levels generally enhance metal ion solubility and extraction efficiency. After achieving and stabilizing at pH 9, proceed with the synthesis of CuO NPs by adjusting the temperature. Then the mixture was heated on a magnetic stirrer at 60°C for 2 h, and the solution was allowed to cool to room temperature. Finally, the dark brown color was separated from the cooled mixture using a centrifuge at 4000 r/min for 15 min. Therefore, centrifuges are essential in nanoparticle synthesis, improving separation efficiency, enabling purification, establishing concentration gradients for ordered structures, and facilitating controlled sedimentation and deposition methods. Then it was washed with distilled water to remove impurities and to maintain the pH at 7. The dark brown precipitate was kept in an oven at 70°C for 12 h. The dried CuO nanoparticles were kept in a furnace at 400°C for 2 h for complete evaporation of moisture. These copper oxide nanoparticles were obtained, which were packed with aluminum foil for future use. The synthesis design pictorial is shown in Figure 2.

Figure 2.

Experimental setup of copper oxide nanoparticle synthesis process.

Characterization

In this research article, UV-Vis spectroscopy was used for the characterization of copper oxide nanoparticles. It typically covers a wavelength range of 190 nm to 1100 nm at a best resolution ranging from 1 nm to 5 nm with an operating range of 20 °C–25°C. In addition, Fourier transform infrared spectroscopy (FTIR) identifies chemical bonds in a molecule by producing an infrared absorption spectrum. The synthesized CuO NPs were characterized by Fourier transform infrared spectroscopy (FTIR) Perkin Elmer version over the frequency range from 4000 to 500 cm⁻¹ at the best resolution of 0.5 cm⁻¹ with an operating range of 5 °C–45°C. Another tool used for characterization and identification of the crystal structure, crystallographic orientation, and phase composition of nanomaterials, particularly copper oxide nanoparticles, was X-ray diffraction. Moreover, the specific surface morphology of the copper oxide nanoparticle was investigated and characterized by scanning electron microscopy. SEM images can provide information about the distribution of the CuO NPs on the surface and whether particles are evenly distributed from clusters, depending on the synthesis method and condition. In addition, the thermal stability of copper oxide nanoparticles was characterized using Thermo gravimetric analysis (TGA). It was determined using a Perkin Elmer Thermo gravimetric analyzer (TGA4000), which works up to a temperature of 1000°C and is 21 CFR Part 11 compatible.

Factor selection for optimization

The value of each factor and its range was determined based on the considerations from previously done research. Concentration is the main factor for both plant extract^48,49 and copper oxide nanoparticles⁵⁰ during coating of cotton fabrics for anti-microbial and UV protection applications. In addition, the percentage of the extract is expressed in percentage olume-to-volume ratio (%v/v). For example, 10% v/v equals 10 mL, and the same for others. Whereas the concentration of CuO NPs is expressed in molarity, which was first dispersed in distilled water and then mixed with the plant extract according to the value assigned for each run. The material-to-liquid ratio was 1:20, and a 5 g sample was taken to perform each experimental run. The Box-Behnken Design technique was used for developing an experimental plan with three variables using design expert software. These variables include phenolic compounds, CuO NPs, and time, such as 10%–30%, 0.1-0.5 M, and 20-40 min, respectively, as shown in Table 2. The dip-dry-cure process was used to apply the active agents to the cotton fabric at a temperature of 50°C, MLR = 1:20, and pH = 8. It was dried at 80°C for 30 min and cured at 140°C for 3 min.

Table 2.

Run of experimental design for applying copper oxide Nanoparticles and phenolic compounds on cotton fabric by dip coating method.

Run numbers	Factor 1	Factor 2	Factor 3
Run numbers	A: Phenolic compounds%	B: CuO NPs	C: Time
1	20	0.3	30
2	30	0.1	30
3	10	0.1	30
4	20	0.1	40
5	20	0.5	40
6	30	0.5	30
7	20	0.1	20
8	30	0.3	40
9	10	0.3	20
10	10	0.5	30
11	20	0.3	30
12	30	0.3	20
13	20	0.5	20
14	10	0.3	40

Testing and evaluating

Antibacterial test

A qualitative technique agar diffusion plate test was used according to Standard ‘SNV 195920-1992’ to evaluate the antibacterial activity (S. aureus and Escherichia coli) of treated fabric through the zone of inhibition technique. The bacteriostatic agar medium was prepared by adding the dehydrated agar powder to distilled water, heating it, and then autoclaving at 121°C for 15 min. After autoclaving, it was allowed to cool to 45 °C–50°C and then pour it into sterile petri dishes, filling them to a depth of 4 mm, followed by solidification at room temperature. The agar plates were inoculated by spreading a 24-h broth culture of the test bacteria evenly over the surface of the agar using a sterile inoculating spreader. Then, 10 × 10 mm of fabric was put on an agar plate that had been injected with a particular strain of bacteria. Incubation was done for the inoculated agar plates at 37°C for 18-24 h (zone of inhibition). Greater antibacterial activity was indicated by a greater zone of inhibition.⁵¹ A rough indication of inhibition zone diameter provides the potential for antibacterial properties to be formed as the antibacterial agent diffuses in the agar media Table 3.

Table 3.

UVR rating and protective category.

UPF Rating	Percentage block of UV Radiation	UV Protection Category
50+	98% −100%	Excellent
40-50	97.5%–98%	Excellent
25-39	96%–97.4%	Very good
15-24	93.3%–95.8% <	Good Poor

UV protection test

The UV-protection test was done based on the percent blocking of ultraviolet radiation by taking the transmittance of treated samples from a UV spectrophotometer. This method determines the effectiveness of the fabric in blocking UV radiation. The sample was exposed to UV radiation and measured how much radiation was transmitted; the protective categories are shown in Table 4 below.⁵² Higher percentage values indicate better UV protection. The percent blocking of ultraviolet radiations for each sample was calculated using the following formula as per the AATCC 183-2000 method.⁵³

% Blocking UVR = 100 % - TUVRav

(2)

Where, UVR is ultraviolet radiation and TUVRav is the average transmittance of UV radiation.

Table 4.

Results of the experimental run for the optimization process.

		Factor 1	Factor2	Factor 3	Response 1	Response 2	Response 3
Std	Run	A: Phenolic compounds (%)	B: CuO NPs	C: Time	ZOI gram-negative bacteria	ZOI Gram-positiveBacteria	%Blocking UVR
Std	Run	%	Molarity	Minute	Mm	Mm	%
13	1	20	0.3	30	22	21	97.91
2	2	30	0.1	30	24	20	96.73
1	3	10	0.1	30	16	14	95.81
11	4	20	0.1	40	21	18	96.9
12	5	20	0.5	40	24	22	94.96
4	6	30	0.5	30	26	26	89.5
9	7	20	0.1	20	18	16	95.81
8	8	30	0.3	40	24	22	95.8
5	9	10	0.3	20	16	16	90
3	10	10	0.5	30	20	18	89
14	11	20	0.3	30	24	20	96.8
6	12	30	0.3	20	23	21	92.8
10	13	20	0.5	20	22	21	95.07
7	14	10	0.3	40	17	17	87.22

Wash durability test

The AATCC 22 method, which is based on the laundry machine concept, evaluated the wash durability of treated fabrics to measure the fabric’s water resistance after treatment.

Air permeability test

It is the main fabric comfort property testing method since it is related to breathability. The comfort property of treated fabrics was tested as per FX 3300 air permeability tester ASTMD737-96.

Tensile strength test

This test evaluates the fabric’s elasticity and strength following its nanoparticle treatment. The test was conducted per ISO 13934/2 standards, and the results offer important insights into how the nano-treatment impacts the mechanical properties of the fabric, particularly its tensile strength and elongation characteristics.

Fabric stiffness testing

Fabric handles and drapes are influenced by factors such as fabric stiffness and bending angle length. Both the warp and weft directions were evaluated for the effect of finishing chemicals on stiffness. The 20 by 20 cm sample was created, and it was examined using the ISO13934 stiffness test method, which analyzed the bending length of the treated and control samples. Three samples, one for each warp and weft direction, were averaged for the tests.

Bending length = falling length (θ)

(3)

Result and discussion

Characterization of phenolic compounds

The FTIR spectra, which is used for determining potential functional biomolecules in the plant extract. The spectra of hot water extract of Azolla nilotica algae phytochemicals used for the reduction and stabilization of CuO NPs in the bioreduction process are shown in Figure 3.

Figure 3.

FTIR spectra of hot water extract of Azolla nilotica.

The maximum wavenumber measured in Azolla nilotica hot water extract showed peaks at 3655 cm⁻¹ indicating the presence of strong O-H bonding of carboxyl groups. While 939 cm⁻¹ shows the bending of O-H groups. 2920 cm⁻¹ indicating the -CH stretching of aliphatic groups; 1619 cm⁻¹ representing the bonds of COO⁻ anions and C = C aromatic are conjugates; and 1462 cm⁻¹ indicating C = O groups from aromatic rings having conjugation; and moreover 1400 cm⁻¹ showing bending vibrations of C-OH alcoholic group and C-O single bond vibrations of ether linkages. Furthermore, based on the previous literature,⁵⁴ functional groups such as C-O, OH, C = O, and COOH have a strong affinity to bind metals to produce highly stable nanoparticles. The IR band indicates different phytochemicals present in the Azolla nilotica extract, including phytochemicals that were not screened well by the reagent phytochemical screening methods.

Characterization of copper oxide nanoparticles

The hot water extract of Azolla nilotica was used to achieve the synthesis of CuO NPs. The extraction yield obtained was 71.1% among 7.98 g of copper sulfate, with an actual yield of 5.67 g CuO NPs. It confirmed that the efficiency of Azolla nilotica algae extracts can rapidly synthesize copper oxide nanoparticles due to the presence of strong reducing and stabilizing phytochemicals such as flavonoids, phenolics, and tannins.

UV-vis spectroscopic analysis

As peak positions and forms are sensitive to particle size, UV-visible spectroscopy is a particularly effective tool for studying metal nanoparticles. The signature of the creation of nanoparticles is the surface Plasmon resonance peak, according to this study.⁵⁵ It happens when the energy of the photons equals the energy of the free electrons in the nanoparticles, causing the electrons to oscillate and form a surface Plasmon. In this study, the properties of surface Plasmon resonance (SPR) with an absorbance of 421 nm were obtained. This shows the presence of copper oxide nanoparticles displayed in the UV-visible absorption spectrum of the nanoparticle, scanned from 300 nm to 800 nm, and the UV-visible analysis of copper oxide nanoparticles is illustrated in Figure 4.

Figure 4.

UV–Visible analysis of copper oxide nanoparticles extracted with Azolla nilotica algae hot water extract.

FTIR analysis

From the FTIR GRAPH, the FTIR of the copper oxide nanoparticles appears to be a mirror image of the FTIR of the algal extract from Azolla nilotica, except for a little shift in the peak of the copper oxide nanoparticles as shown in Figure 5. This graph shows that the extract biomolecules contribute to the formation of CuO NPs, improving their ability to reduce, stabilize, and cap the nanoparticles. In addition, the comparison was done for the FTIR of copper sulfate and CuO NPs. A broad absorption peak was observed in the FTIR spectrum of CuO NPs compared to copper sulfate (Cu₂SO₄), which is caused by the adsorbed water molecules and functional group of the reducing agents. Furthermore, the adsorption of water is due to the high surface area-to-volume ratio of the nanoparticles. Although both copper sulfate and copper oxide nanoparticles contain copper-oxygen bonds, the specific Cu-O stretching frequencies and presence of additional functional groups differ between the two chemical species based on their chemical composition and synthesis methods.

Figure 5.

FTIR spectra of Copper oxide nanoparticles and copper sulfate.

The above Figure 5 shows that the FTIR spectra were recorded in the solid phase at a range of 4000–500 cm⁻¹ for the precursor and nanoparticles. The peak at 3720 cm⁻¹ indicates the presence of strong O-H bonding of carboxyl groups that is O-H bond stretching. In addition, the peak 2929 cm⁻¹ shows that -CH stretching of aliphatic groups, while the peak 1600 cm⁻¹ represents the bonds of COO^-anions and C = C aromatics are conjugates. Moreover, the peak at 1405 cm⁻¹ was indicating C = O groups from aromatic rings having conjugation, and 1025 cm⁻¹ showed bending vibrations of the C-OH alcoholic group and C-O single bond vibrations of ether linkages. In conclusion, the C = O bond indicates the presence of aromaticity in the synthesized nanoparticles.

SEM analysis

The surface morphology of copper oxide nanoparticles was recorded at 6000x, 3000x, 1000x, and 600x magnifications through SEM. The surface morphology analysis was important because the antimicrobial activity of the nanoparticle depends on the morphology of the nanoparticles. Therefore, the CuO NPs graph depicts the SEM image of these samples laid out and clearly shows low and high aggregation white backgrounds with some distributed dark areas, which could be phytochemical components distributed on copper oxide nanoparticles. As can be seen from Figure 6, the nanoparticles appeared small and some agglomerated, with different morphologies, from spherical shapes of various sizes to amorphous shapes. The observations from copper oxide nanoparticle images were recorded at 6000x magnification by SEM (as shown in Figure 6(a)) is distributed in a good manner, and as a result, it has a proper and well-defined homogenous crystallized structure with low aggregations.

Figure 6.

SEM image of synthesized copper oxide nanoparticles.

The micrograph-derived CuO NPs recorded at 3000x, 1000x, and 600x magnification by SEM (as shown in Figure 6(b), (c) and (d)) are exhibited as voluminous and agglomerated. The agglomeration of nanoparticles is usually explained as a common way to minimize their surface-free energy due to polarity and the strong electrostatic attractive inter-particle force of CuO NPs. The more voids and pores present in the sample show the large number of gases produced during the synthesis of the nanoparticles.⁵⁶

XRD analysis

The synthesized CuO NPs from copper sulfate and Azola nilotica algae extract were confirmed 2θ using X-ray diffraction measurements. The diffracted intensities were recorded in a wide scanning range from 0° to 90°, which is shown in Figure 7. The diffraction major peaks were observed at 2θ values of 19.45°, 22.79°, 28.35°, 29.89°, 31.76°, 34.09°, 35.69°, 36.58°, 38.79°, 42.57°, 48.93°, 58.45°, 61.69°, 65.92°, and 67.97°. The absence of diffraction peaks in the XRD patterns and crystal size show the low purity of synthesized CuO NPs. The mean average crystal size of the synthesized CuO NP was calculated using Debye Scherrer’s formula used to calculate the crystalline size of the nanoparticles as shown in equation (3). The average crystal size of CuO NPs corresponding to the most intense peaks was 21.56 nm.

D = \frac{K λ}{β Cos θ}

(4)

Where D is the nanoparticles crystalline size, K represents the Scherrer constant (0.98), λ denotes the wavelength (1.54), β denotes the full width at half maximum (FWHM).

Figure 7.

XRD pattern of CuO NPs synthesized using Azolla nilotica algae extract.

Thermal analysis

To find out how stable CuO NPs would be at high temperatures, their thermal stability was evaluated using Thermogravimetric analysis. When nanoparticles were exposed to controlled temperature fluctuations, the resulting weight changes were measured as shown in Figure 8. There are about two weight losses from 50 to 200°C and from 200 to 450°C. The first weight loss of about 10% was due to the loss of moisture content on exposure to the atmosphere, whereas the second weight loss, about 40%, was due to the decomposition of copper oxide nanoparticles.

Figure 8.

TGA curve of copper oxide nanoparticles.

Data presentation

Data presentation about antibacterial test

The antibacterial test for the experimental runs was done, and the results were presented as gram-negative bacteria (E. coli) and gram-positive bacteria (Staphylococcus aurous) (as shown in Figure 9 and respectively) by the zone of inhibition method. However, the samples without an inhibition zone concede that they do not have an antibacterial effect. Therefore, the control sample, which was not treated with antibacterial active agents, did not show a clear inhibition zone. This means the antimicrobial activity of the untreated cotton fabric was too much less compared to the treated one. The test mechanism was done by putting a 10 × 10 mm fabric sample on a nutrient agar plate, inoculating it with a bacterial culture, and then incubating it. Following incubation, the circumference of the inhibition zone surrounding the fabric sample was measured carefully. The measured test results were expressed in millimeters of diameter, as shown in Figure 9.

Figure 9.

Antibacterial test (a- gram-negative and b -gram-positive bacteria) for treated total run samples.

In conclusion, each sample was leveled with numbers; for example, the sample with number one indicates the sample for run number one, and the letter C indicates the control sample or untreated sample, the same for others for both gram-negative and gram-positive bacteria.

Data presentation about UV protection test

The ultraviolet radiation protection test was done in terms of percent blocking of UVR based on average transmittance of radiations. A wavelength of 280-400 nm was taken to calculate the average transmittance of 14 experimental runs for determining the response percent block of UVR. The result was expressed as a percent block rating category. For example, run number one with an average transmittance of 2.0830% will be 97.91% based on equation (1). Therefore, the percent block for run number one is 97.91%. The same % block UVR was recorded for each run as shown in Table 4.

% Block UVR = 100 % - TUVav % block UVR = 100 % - 2.0830 % = 97.91 %

Data analysis

Model fitting

Model fitting and the analysis of variance response surface method were employed with a Box–Behnken design to investigate the effects of phenolic compounds, CuO NPs, and time on the zone of inhibition of gram-negative bacteria gram-positive bacteria, and the percent blocking of ultraviolet radiation of the treated plain cotton fabric. About responding gram-negative bacteria, the difference between the adjusted R² of 0.9262 and the expected R² of 0.7821 is less than 0.2. In addition, there is less than a 0.2 difference between the adjusted R² of 0.9613 and the expected R² of 0.8665 for gram-positive bacteria, indicating a satisfactory agreement. The modified R² of 0.9751 and the projected R² of 0.8910 are reasonably in agreement; that is, the difference in percent blocking of UV light is less than 0.2. A ratio that is higher than four is preferred. Therefore, the model can be used to navigate the design space.

Multiple regressions was applied by analyzing the actual data, and models for each of the three responses were expressed by the following quadratic polynomial model Table 5. The generated equations demonstrated the empirical relationship between the dependent and independent variables for each response. A statistical method based on ANOVA was used to obtain the coefficient of determination R² for gram-negative bacteria, gram-positive bacteria, and percent blocking of ultraviolet radiation which were 0.9773, 0.9881, and 0.9923, respectively. A good fit with high correlation is achieved if the regression model has an R² value of above 0.9. The R² values obtained indicated that more than 99% of the response variables could be described by the model. The high values of R² for each response indicated that the Box–Behnken design fitted well into the developed quadratic polynomial models. These results confirmed the predictability of the models in determining the optimum conditions needed to obtain the highest antibacterial and percent blocking of ultraviolet radiation activity of the treated cotton fabric.

Table 5.

Quadratic polynomial equations for the three responses in terms of coded factors.

Responses	Equations
Gram-negative bacteria	$Y = 26 + 3.75 A + 2.87 B + 0.8750 C + 4.55 AB + 2.71 AC + 1.99 BC - 1.88 C^{2}$ (5)
Gram-positive bacteria	$Y = 23.5 + 2.75 A + 2.12 B + 1.92 C + 3.89 AB + 1.421 AC + 1 . 63BC - 0.8758 A^{2}$ (6)
Percent block UVR	$Y = 87.5 + 4.50 A + 3.01 B + 7.73 AB + 3.21 BC - 1.72 B^{2}$ (7)

In these equations, Y is the predicted response, A, B, and C are the values of the independent variables, phenolic compounds (%), CuO NPs (M), and time, respectively.

Regression equation

In the regression equation, only coefficients of significant factors are included. The following formula gives the quartic model of three factors.

Y = β_{0} + β_{1} X_{1} + β_{2} X_{2} + β_{3} X_{3} + β_{11} X_{1}^{2} + β_{22} X_{2} + β_{33} X_{3}^{2} + β_{12} X_{1} X_{2} + β_{13} X_{2} X_{3} + β_{23} Y_{2} Y_{3}

where: Y is the dependent variable, βi, βii … βin indicates the value of linear, quadratic and interactive coefficients respectively and β₀ is constant.

ANOVA

The data was analyzed for the response of the zone of inhibition of gram-negative bacteria, zone of inhibition of gram-positive bacteria, and percent blocking of ultraviolet radiation with the help of design expert software analysis tools as shown in Table 6.

Table 6.

ANOVA for the quadratic polynomial models developed for the response variables; zone of inhibition of gram-negative bacteria, zone of inhibition of gram-positive bacteria, and %Blocking UVR. ZOI gram-negative bacteria ZOI gram-positive bacteria %Blocking UVR.

Source	Some of squares	DF	MeanSquare	F-value	p-value	Some of Squares	DF	MeanSquare	F-value	p-value	Sum of Squares	DF	Mean Square	F-value	p-value
Model	161.46	9	17.94	19.14	0.0040	103.61	9	11.51	36.84	0.0017	437.22	9	48.58	57.55	0.0007
A-phenolic compounds	112.50	1	112.50	120.00	0.0007	53.78	1	54.79	184.78	0.0005	45.60	1	45.60	54.03	0.0018
B-CuO NPs	28.12	1	28.12	30.00	0.0054	34.12	1	34.12	97.60	0.0008	11.90	1	11.90	14.10	0.0199
C-time	6.13	1	6.13	6.53	0.0629	3.13	1	3.13	10.00	0.0341	1.54	1	1.54	1.82	0.2481
AB	119.8	1	119.95	125.78	0.0004	60.50	1	60.50	193.60	0.0002	361.94	1	361.94	428.80	<0.0001
AC	46.9	1	47.57	50.4	0.0049	6.90	1	6.90	7.12	0.0458	0.0025	1	0.0025	0.0030	0.9592
BC	27.49	1	27.87	29.91	0.0068	2.50	1	2.65	8.00	0.0421	48.05	1	48.05	58.33	0.0158
A²	4.05	1	4.05	4.32	0.1062	2.45	1	2.45	7.84	0.0488	3.19	1	3.19	3.78	0.1237
B²	0.0500	1	0.0500	0.0533	0.8287	1.25	1	1.25	4.00	0.1161	9.51	1	9.51	11.26	0.0284
C²	11.25	1	11.25	31.00	0.0257	1.25	1	1.25	4.00	0.1161	0.0022	1	0.0022	0.0026	0.9617
Residual	3.75	4	0.9375			1.25	4	0.3125			3.38	4	0.8441
Lack of fit	1.75	3	0.5833	0.897	0.6588	0.7500	3	0.2500	0.5000	0.7478	2.88	3	0.9588	1.92	0.4776
Pure error	2.00	1	2.00			0.5000	1	0.5000			0.5000	1	0.5000

An analysis of variance in the case of gram-negative bacteria reveals an F value of 19.14, indicating a 0.6% probability that noise may cause a high value. Less than 0.05 of the 95% confidence level is represented by the p-value of 0.0040. When studying gram-negative bacteria, model terms are significant, according to both P and F values. Furthermore, the F-value of 0.897 indicates that the lack of fit is not statistically significant in terms of pure error. The p-value, which is greater than 0.05 at a 95% confidence interval, is 0.6588 (0.6588 > 0.05). In contrast to the components B² and C², which are not significant, Table 4 demonstrates that factors like A, B, C, AB, AC, BC, and A² are significant model terms since their p-values are less than 0.05 in a 95% confidence interval. After all, their p-value is bigger than 0.05 in a 95% confidence interval because of terms for the specified model. Additionally, the ANOVA table demonstrates that the majority of terms A, B, C, AB, AC, BC, and A² significantly influence how gram-positive bacteria respond in the zone of inhibition. Furthermore, the 0.50 F-value for lack of fit indicates that the lack of fit is not statistically significant compared to the pure error. In the case of gram-positive bacteria, the p-value at a 95% confidence interval is 0.7478, which is more than 0.05 (0.7478 > 0.05), indicating a non-significant lack of fit. The ANOVA for percent blocking of ultraviolet radiation protection makes clear that factors such as A, B, AB, BC, and B² are significant model terms. The other components from the analysis of the variance table are not significant for the given model because their p-value exceeds 0.05 of the 95% confidence interval. The lack of fit F-value of 1.92 implies the lack of fit is not significant relative to the pure error. The p-value at a 95% confidence interval shows 0.4776, which is greater than 0.05 (0.4776 > 0.05), resulting in a lack of fit that is not significant. Therefore, a non-significant lack of fit is good; we want the model to fit. This indicates that a quadratic model properly observes the zone of inhibition of gram-negative bacteria, the zone of inhibition of gram-positive bacteria, and the percent blocking of UVR. The percent blocking of ultraviolet radiation protection with the factors phenolic compounds, copper oxide nanoparticles, and time.

Effect of main factor on the response

The effect of main factors offers a simple method to evaluate the influence of a single factor on the result by quantifying the average change in response variable brought about by varying its level.

From Figure 10 above, the factor (A) or phenolic compounds have an enhanced effect on response. When the concentration changes from left to right, the inhibition of gram-negative bacteria increases since the hydroxyl group of the extract increases. This means the percentage concentration of the OH group increases in a solution prepared. In addition, the hydroxyl group of the phenolic compounds can penetrate, disrupt, and bind to inactivate bacterial enzymes essential for growth and survival. The lipid bilayer causes leakage of cellular contents and ultimately death in bacterial cells.⁵⁷ In the case of factor (B) or copper oxide nanoparticles, based on the previous literature, an electron transfer between the negatively charged bacteria and copper oxide nanoparticles is one of the effective mechanisms that cause the bacterial membrane to rupture and exert antibacterial activity.⁵⁸ The Cu2+ and Cu + released from CuONPs dissolution undergo a chemical reaction, producing many oxidative free radicals (ROS), which can damage the cell respiratory chain and membrane structure and cause DNA cleavage in gram-negative bacteria. Furthermore, factor (C) or time from the one-factor interactions shown in Figure 10 shows that there is an increasing effect on the response from left to right or from 20 to 30 min. After 30 min, there is a decreasing effect since increasing dipping time of the fabric with active agents reaches a saturation point.⁵⁹

Figure 10.

Effect of main factors on the zone of inhibition of gram-negative bacteria.

From Figure 11 above, factor A, or phenolic compounds, has a higher effect on the ZOI of gram-positive bacteria. As the concentration changes from left to right, the inhibition of gram-positive bacteria increases since the concentration of the hydroxyl group in phenolic compounds increases. This means the OH group reacts with the bacterial cell, and there is an increase in the inhibition of gram-positive bacteria. Therefore, higher quantities of these antibacterial compounds would be more effective. It can be assumed that raising the concentration of phenolic compounds from low to high would likely result in a larger zone of inhibition against gram-positive bacteria. The hydroxyl group of the phenolic compounds could disrupt and bind to inactivate bacterial enzymes essential for the growth and survival of bacteria.⁶⁰ In addition, the effect of copper oxide nanoparticles, or factor B, on the response shows an increasing effect, as from left to right. The graph shows the same increasing effect as the gram-negative bacteria. The electron transfer between the negatively charged bacteria and copper oxide nanoparticles is one of the effective mechanisms that cause the bacterial membrane to rupture and exert antibacterial activity. The Cu2+ and Cu + released from CuO NP dissolution undergo a chemical reaction, producing a large number of oxidative free radicals (ROS), which can damage the cell respiratory chain and membrane structure and cause DNA cleavage in gram-negative bacteria. Furthermore, the dipping time of the fabric to active agents during the coating process affects the ZOI of gram-positive bacteria. There is an increase in nanoparticle deposition through time. Factor C, or time from the one-factor interaction, shows that there is a reasonable increment of up to 30 min and then a decrease afterward due to enough amounts of active agents deposited on the fabric.⁶¹

Figure 11.

Effect of main factors on zone inhibition of gram-positive bacteria.

As the value of factor A, or phenolic compounds, increases from left to right, the percent blocking of ultraviolet radiation increases. This is due to the increment of hydroxyl free radicals in Azolla nilotica algae, which come from flavonoids, alkaloids, and tannin. The graph of the phenolic compound against percent-blocking ultraviolet radiation shows an increasing effect. Therefore, further increasing the concentration of phenolic compounds in Azola nilotica algae extracts leads to an increase in the percent blocking of ultraviolet radiation.⁴⁶ As Figure 12 illustrates, the copper oxide nanoparticles, or factor B, have a sharp increasing effect on the response factor, or UVR. As the concentration increased from 0.1 to 0.5 molarity, there was an increase in the percent blocking of ultraviolet protection, which means the positive holes that absorb ultraviolet radiation in copper oxide nanoparticles increased as the concentration increased. In addition, the electrons and holes react with oxygen and water molecules to generate O2, H2O2, and hydroxyl radicals based on the previous literature. Furthermore, the effect of factor A (phenolic compound) on the percent blocking ultraviolet radiation shows an increasing effect from left to right. This indicates that as the concentration increases from 10 to 30%, the percent blocking of factor A (phenolic compound) increases due to the deposition of more phenolic compounds on the surface.⁶²

Figure 12.

Effect of main factors on percent blacking of ultraviolet radiation.

3D surface

The 3D surface shows the effect of significant of independent variables, which are phenolic compounds, copper oxide nanoparticles, and time on to the response zone of inhibition of gram-negative bacteria, gram-positive bacteria, and percent blocking ultraviolet radiation with the three-dimensional graph. The interaction effects of factors on the 3D graph were shown for each response as follows.

The 3D surface (A) shows that the interaction effects of phenolic compounds and CuO NPs on the response zone of inhibition of gram-negative bacteria are shown in Figure 13 above. The response with a maximum zone of inhibition of gram-negative bacteria of 23 mm was obtained with the factors CuO NPs (0.29 molarity) and phenolic compounds (20%), respectively. In addition, the 3D surface (B) shows the interaction effect of phenolic compounds and time on the response zone of inhibition of gram-negative bacteria. As a result, the maximum inhibition zone for the response of gram-negative bacteria at 23 mm was obtained with factor phenolic compound 20% and a time of 30 min, respectively. Furthermore, the 3D surface (C) of the interaction effect of phenolic compounds and time on the response zone of inhibition of gram-negative bacteria. The maximum inhibition zone for the response of gram-negative bacteria at 23 mm was obtained with a factor CuO NPs value of 0.3 molarity and a time of 30 min, respectively. Overall, the value of the response is determined by the change in the level of one factor depending on the level of the other.

Figure 13.

Interaction effects of independent factors on the zone of inhibition of gram-negative bacteria.

The 3D surface, as shown in Figure 14, shows that the factor with phenolic compounds and copper oxide nanoparticles is in the response zone of inhibition of gram-positive bacteria. From the 3D graph (D), the response with a maximum zone of inhibition of gram-positive bacteria of 21 mm was obtained with CuO NPs of 0.3 molarity and phenolic compounds of 20%, respectively. In addition, the 3D surface (E) shows the phenolic compounds and time on to the response zone of inhibition of gram-positive bacteria. The response with a maximum zone of inhibition of gram-positive bacteria of 21 mm was obtained with a factor time of 30 min and a phenolic compound of 20%, respectively. Furthermore, the interaction effects of CuO NPs and time (F) factors on the response zone of inhibition of gram-positive bacteria. The response with a maximal zone of inhibition of 21 mm for gram-positive bacteria was reached with a factor of 0.3 M and 30 min, respectively.

Figure 14.

The 3D surface of an interaction effect of factors on the zone of inhibition of gram-positive bacteria.

The three-dimensional surface, in Figure 15 (G) shows the interaction effect of phenolic compound concentration and copper oxide nanoparticles on the response of percent-blocking ultraviolet protection (UVR). Here, the maximum percent blocking ultraviolet protection was 95% obtained at 0.3 molarity of CuO NPs and 20% of phenolic compounds, respectively. In addition, the 3D surface (H) shows the combined effect of copper oxide nanoparticles and time on the response percent blocking ultraviolet protection. As a result, the maximum percent blocking ultraviolet protection was 95.8% obtained at 0.3 molarity of CuO NPs and a time of 30 min, respectively.

Figure 15.

Phenolic compounds and CuO NPs 3D surface of percent blocking ultraviolet protection.

Optimization processes

In this section, the maximum optimized result of the responses of the zone of inhibiting gram-negative bacteria, zone of inhibition of gram-positive bacteria, and percent blocking of ultraviolet protection was summarized and illustrated as in Table 7.

Table 7.

The optimized value of independent factors based on response variables.

A: Phenolic compounds	B: CuO NPs	Time		ZOI gram-negative bacteria	ZOI gram-positive bacteria	%Blocking UVR (%)	Desirability
30.000	0.500	30.0	27.625	23.88	99.99	0.767	Selected

Cotton fabric treated with copper oxide nanoparticles and phenolic compounds was found to have better antibacterial and ultraviolet protection. This is due to the impact of copper ions released from copper oxide nanoparticles with different oxidation states (Cu⁺ and Cu²⁺⁾ that react with the negatively charged bacteria cells. Therefore, the released ions attached to the cellular metabolism inhibit bacterial cell growth and suppress respiration.⁶³ In addition, the phenolic compounds from Azola nilotica alga extract have an impact on bacteria as copper oxide nanoparticles. This is due to the presence of OH ions that react with bacterial cells and exhibit better antimicrobial effects.⁶⁴ In conclusion, These free radicals from copper oxide nanoparticles and phenolic compounds can trap ultraviolet radiation, based on the previous literature.⁶⁵ When combining the two factors, the values in this indicate that the synergistic effect of the two active agents increases the antimicrobial and ultraviolet radiation protection abilities of plain cotton fabric.

Result for transmittance of blank, optimized, and washed sample

The transmittance data was obtained using a spectrophotometer by measuring the transmittance for each of the blanks, optimized for five wash cycles and 10 wash cycles. The value was expressed as percent transmittance (T), as shown in Table 8.

Table 8.

Transmittance data of blank, optimized, 5 and 10 wash cycles.

Wavelengths	Blank sample (white)	OptimizedSample	5- washCycle	10-wash cycle
Λ	T%	T%	T%	T%
280	14.08	0.022	5.032	12.032
285	14.07	0.025	4.035	12.042
290	13.09	0.012	5.022	12.043
295	14.07	0.013	4.023	12.047
300	13.04	0.011	4.021	12.033
305	13.05	0.012	3.022	12.032
310	13.04	0.025	3.035	12.034
315	13.03	0.011	5.031	11.036
320	13.04	0.013	5.033	11.043
325	14.02	0.015	5.043	11.034
330	15.03	0.011	4.021	12.039
335	15.03	0.014	4.029	12.043
340	14.03	0.022	5.034	12.038
345	12.04	0.012	4.042	12.049
350	14.04	0.023	4.033	12.038
355	13.01	0.011	5.035	12.037
360	13.02	0.024	5.032	12.043
365	14.04	0.022	4.026	12.044
370	12.06	0.021	4.025	17.032
375	15.04	0.012	4.027	16.032
380	14.05	0.022	5.028	12.035
385	12.03	0.021	4.038	12.043
390	15.03	0.012	5.035	12.053
395	13.04	0.011	4.031	11.045
400	15.05	0.012	4.032	13.034

Testing and evaluation of the treated samples

Wash durability

In this section, a wash fastness test for assessing the antimicrobial and percent blocking of ultraviolet protection was done. The high antimicrobial activity of the active agents treated on cotton fabric was obtained with a value of 27.625 mm and 23.87 mm for gram-negative and gram-positive bacteria in the optimized sample, respectively. This was due to the high antioxidant activity of phenolic compounds found in Azolla silica algae extract and the high oxidative stress of copper oxide nanoparticles.⁶⁶ In addition, the wash fastness of antimicrobial was better for five washes cycles compared to 10 wash cycles, even though there was a decrease as illustrated in the Table 9. However, there was a significant decrease after 10 wash cycles. This was due to the hydrolysis of hydrogen bonds, which were formed with cotton and phenolic compounds extracted from Azolla nylotica algae, and the removal of nanoparticle complexes from the surface.⁶⁷

Table 9.

Wash fastness for antimicrobials and %blocking of UV test.

	Gram-negative bacteria	Gram-positive bacteria	%Block UVR	%Block UVA	%Block UVB	UVR rating
	ZOI (mm)	ZOI(mm)(mm)	%	%	%	UVR rating
5- Washing Cycle	23	20	95.65	95.52	95.8	Very good
10- Washing Cycle	19	17	87.7	87.63	88.09	Poor
UntreatedSample	_	_	86.36	86.3	86.57	Poor

UVR after 10 washes is poor in the rating category, as shown in Table 12, because the treated active agents were removed due to repeated washing. As per the study of,⁶⁸ the optimized UVR for phenolic compounds obtained from plant extract was 98.3%, which is categorized in the excellent rating category. Also, CuO NPs have the highest ultraviolet radiation protection compared with the other metal nanoparticles.⁶⁹ This implies the UVR and antimicrobial activity of the treated cotton fabric show high before washing but decreases in activity after 5 and 10 wash cycles.

Tensile strength

Tensile strength was calculated by averaging three samples, and the result was expressed in terms of percent elongation at break. The effect of copper oxide nanoparticles and the phenolic compound of Azolla nylotica algae extract on plain cotton fabric are illustrated in Table 10.

Table 10.

Tensile strength test.

S/No.	Sample	Force (N/mm²)		Elongation at break (%)
S/No.	Sample	Warp	Weft	Warp	Weft
1	Control sample	298	274	18.1	12.4
2	Treated sample	298	274	19.2	13.2

Elongation at the break of the treated sample was increased due to the deposition of phenolic compounds and copper oxide nanoparticles on cotton fabric, as shown in Table 10. In addition, both phenolic compounds and copper oxide nanoparticles act as reinforcement agents and enhance interactions between fibers with hydrogen bonds.

Fabric stiffness testing

This test was done to analyze the flexibility and handling properties of the treated fabric. This helps to know the impact of the finishing agents on stiffness. Three tests have been done, and their average result is shown in Table 11.

Table 11.

Stiffness test.

Sample type	Bending length (cm)
Sample type	Warp	Weft
Control sample	1.7	1.6
Treated sample	1.9	1.75

Therefore, from Table 11, the result shows that the bending length of the treated sample was greater than that of the control sample. It suggests that the finishing agents are responsible for increasing stiffness.

Air permeability

The ease of airflow through a fabric is a crucial attribute of textile materials that determines its level of comfort and breathability. Table 12 illustrates the permeability of the treated fabric and how its permeability was decreased. Therefore, the change in surface characteristics of treated fabric results in decreased air permeability. This is due to the pore blockage and the roughness produced by the treated active substances, which decrease air permeability by raising airflow resistance.⁷⁰

Table 12.

Air permeability test.

Sample type	Air permeability in Cm³/cm²/s
Control sample	16.7
Treated sample	11.3

Conclusion and future work

Conclusion

In conclusion, cotton fabric was functionalized based on the two active agents (phenolic compounds and CuO NPs). Crude Azolla nilotica algae extract has been used to get the intended phenolic compounds using a hexane liquid-liquid separation technique. From 10 g of Azolla nilotica Algae powder, 3.1 g of polar compounds were obtained after the separation of polar from nonpolar compounds, and the percentage yield was 31%. Then, green synthesis of copper oxide nanoparticles was done following the preparation of the extract, as a result, the percentage yield of copper oxide nanoparticles was 71.1% among 7.98 g of copper sulfate with an actual yield of 5.67 g CuO NPs. Finally, optimization was done by treating cotton fabric with these two active agents. The optimum results obtained were gram-negative bacteria with a zone of inhibition of 27.625 mm, gram-positive bacteria with a zone of inhibition of 23.88 mm, and percent blocking of ultraviolet radiation 99.99%.

Future work

In the global textile and apparel sector, cotton is the most extensively used natural fiber. It has a distinct advantage over other materials in a variety of textile and apparel applications. Although it has distinct advantages, it also has some limitations. To make cotton fabric ideal for the wearer, this research used a combination of the two active agents to develop multifunctional finished cotton fabric. Therefore, the following points are promising actions that were not addressed in this research work.

• Active agents used for multifunctional finishing processes also impart functional properties such as, self-cleaning, electrical conductivity for copper oxide nanoparticles and antiviral activity and fire retardancy properties.

• Exploring the combination of phenolic compounds with other nanoparticles like TiO2 or ZnO could also lead to synergistic effects and further enhance the functional properties of the treated cotton fabric.

• Knowing and determining the number of phytochemical components quantitatively in Azolla notice algae extract is needed for further investigation.

• During the synergetic combination of copper oxide nanoparticles and phenolic compound of Azolla nylotica algae extract there is no use of any cross-linking agent in this research work, this needs further improvement.

• In this research, we use hexane for the removal of non-polar compounds from crude extract to get the polar compounds. On the other hand, it is possible to separate polar compounds from crude extracts using ethanol’s with the principles of like dissolves like.

Footnotes

Author contribution

All authors listed have significantly contributed to the development and the writing of this article review.

Declaration of conflicting interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Girma Moges

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Synergetic antibacterial and UV-protective finishing of cotton fabric functionalized with copper oxide nanoparticles and phenolic compounds of Azolla Nilotica algae extracts

Abstract

Keywords

Introduction

Materials and methods

Materials

Methods

Preparation of plant extract

Separation of phenolic compounds from the crude

Phytochemical screening

Characterization

Synthesis of copper oxide nanoparticles

Characterization

Factor selection for optimization

Testing and evaluating

Antibacterial test

UV protection test

Wash durability test

Air permeability test

Tensile strength test

Fabric stiffness testing

Result and discussion

Characterization of phenolic compounds

Characterization of copper oxide nanoparticles

UV-vis spectroscopic analysis

FTIR analysis

SEM analysis

XRD analysis

Thermal analysis

Data presentation

Data presentation about antibacterial test

Data presentation about UV protection test

Data analysis

Model fitting

Regression equation

ANOVA

Effect of main factor on the response

3D surface

Optimization processes

Result for transmittance of blank, optimized, and washed sample

Testing and evaluation of the treated samples

Wash durability

Tensile strength

Fabric stiffness testing

Air permeability

Conclusion and future work

Conclusion

Future work

Footnotes

Author contribution

Declaration of conflicting interests

Funding

ORCID iD

References