Applications of materials with high cleavage power and quantum efficiency for water treatment

Moêz Smiri; Mohammed Basahi

doi:10.25259/AJC_1159_2025

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Original Article

ARTICLE IN PRESS

doi:

10.25259/AJC_1159_2025

Applications of materials with high cleavage power and quantum efficiency for water treatment

Moêz Smiri^a,*, Mohammed Basahi^b

aDepartment of Biology, Applied College Shaqra, Shaqra, Saudi Arabia

bDepartment of Biology, Shaqra University, Applied College - Shaqra, Saudi Arabia

* Corresponding author: E-mail address: almoez@su.edu.sa (M. Smiri)

Received: 2025-09-26, Accepted: 2026-01-02, Epub ahead of print: 2026-04-04,

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This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

Abstract

The use of sustainable practices in the field of water treatment is of significant environmental concern. One of the primary applications of sustainable chemistry is the synthesis of polymeric metal oxide nanoparticles utilizing readily available, naturally occurring biological resources. Using U. dioica leaf extract, we were able to produce zinc oxide nanoparticles (ZnO-NPs) in a controlled manner in our current study. It was determined that the synthetic method was highly cost-effective, productive, and ecologically beneficial. The average crystalline size was around 25 nm, as determined by the Debye-Scherrer equation. The scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images indicate that the synthesized ZnO nanoparticles exhibit a range of particle sizes, with some variation in morphology. While many particles appear roughly spherical, there is noticeable diversity in shape and size, reflecting the inherent variability of the synthesis process. According to the scanning electron microscopy SEM analysis, while many particles appear roughly spherical, there is some morphological variability, as observed in the presented characterization data. The Box-Behnken design (BBD) in response surface methodology (RSM) was used to optimize several process variables, such as contact time (C: 20–70 min), catalyst dose (B: 1–3 g/L), and concentration dye [CV] (A: 10–30 ppm). The chosen RSM was effective at optimizing the conditions for Crystal Violet breakdown, as evidenced by the adjusted coefficient of determination (R²) value of 0. 99, which clearly demonstrated that the used model was well-suited.

Keywords

Box-Behnken design

Photocatalytic activity

RSM technique

U. dioica L

Zinc oxide nanoparticles

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1. Introduction

Nanotechnology is an exciting area combining physics, chemistry, biology, and materials science, focusing mostly on nanoparticles (NPs) that range from 1 to 100 nanometers. Their small size leads to higher surface reactivity, making them useful in many applications like catalysis, gas detection, electronics, and environmental cleanup [1-5]. Zinc oxide (ZnO) nanoparticles are particularly interesting due to their safety and special features, such as biocompatibility and biodegradability. They can be produced through various methods like the sol-gel process and co-precipitation, but greener methods using plant extracts offer a simpler and more eco-friendly alternative [6-10]. The uniqueness of the present work lies in the use of Urtica dioica extract, which is rich in bioactive compounds (such as phenolics and flavonoids) that act simultaneously as reducing and stabilizing agents. This contributes to controlled nucleation, good crystallinity, and effective photocatalytic performance. Compared to many reported plant-mediated syntheses, U. dioica is inexpensive, widely available, and requires minimal pretreatment, enhancing the sustainability of the approach. Research has shown that many plants can be used to synthesize zinc oxide nanoparticles (ZnO-NPs), with some studies focusing on extracts from fruits and leaves. Notably, the plant Urtica dioica, known for its medicinal properties, contains beneficial compounds that may help in creating nanoparticles. This study aims to use U. dioica extract to synthesize ZnO-NPs and examines their effectiveness in breaking down crystal violet dye [11-19]. The research employs a Box-Behnken design to optimize the process, investigating three key factors: initial dye concentration, catalyst dosage, and contact duration. This design helps minimize experimental trials while creating a predictive model for the photocatalytic degradation rate of the dye. By optimizing these conditions, the study also addresses the potential of ZnO-NPs as catalysts for treating wastewater, specifically from dairy facilities, to improve environmental management practices [20,21]. A direct experimental comparison with chemically synthesized ZnO nanoparticles was not performed. However, the green advantage of the proposed method is demonstrated through the avoidance of toxic chemicals, lower energy requirements, and the use of renewable plant resources. The study also explores the dual role of U. dioica extract as a reducing agent. Overall, the research aims to contribute to better wastewater treatment methods using environmentally friendly nano-synthesis procedures.

2. Materials and Methods

2.1. Plant extract

Fresh U. dioica L. leaves were collected and cleaned in water, then dried at 20°C. The dried leaves were ground into powder, mixed with deionized water, heated to boiling, filtered, and stored at 4°C.

2.2. Synthesis of zinc oxide nanoparticles

Fifty milliliters of plant leaf extract were added to ninety milliliters of zinc nitrate solution and stirred at 75°C. The color change indicated the formation of nanoparticles, which were then centrifuged, washed with distilled water and ethanol, and dried overnight. The dried powder was heated at 500°C for 2 h for final processing.

2.3. Material characterization

ZnO-NPs were characterized using a Shimadzu X-ray diffractometer with specific settings. Their optical properties were studied using a UV-Vis spectrophotometer, where the absorption spectrum was determined between 200 and 800 nm. Morphological characteristics were examined with scanning electron microscopy (SEM) and transmission electron microscopy (TEM), and the elemental composition was analyzed with energy dispersive spectroscopy (EDS). The average particle size was measured using a zeta sizer after dispersing the nanopowder in acetone. Fourier transform infrared (FTIR) analysis was conducted to identify organic compounds, and photoluminescence studies were evaluated using a fluorescence spectrophotometer. All experiments were repeated three times, with data analyzed using Origin 8 software.

2.4. Photocatalytic activity of nanoparticles

To examine the degradation rate of crystal violet (CV), a solution with a concentration of 20 ppm was prepared using double-distilled water. Tests were conducted using different initial dye concentrations (10 ppm, 20 ppm, and 30 ppm), catalyst concentrations (1-3 mg), and varied times (20 min–90 min). The solution was stirred under UV light at a distance of 10 cm and a constant temperature of 25°C. Prior to testing, it was stirred in the dark for 30 min. Samples were taken at set times for absorption analysis using a UV-Vis spectrophotometer. The efficiency of photocatalytic degradation was calculated using a specified equation (Eq. 1):

(1)

% C V r e m o v a l = (\frac{C 0 - C}{C 0}) * 100

where Co is the initial concentration of CV dye solution (mg/L), and C is the concentration of the CV dye solution (mg/L) after irradiation time.

2.5. Box–Behnken experimental design

The design expert software optimized CV degradation on the U. dioica leaf catalyst using a Box-Behnken design (BBD) with three levels and three factors. This design avoids extreme conditions and simultaneous maximum and minimum variables [22]. Dye degradation was the response variable. The data met requirements for quadratic modeling, were analyzed with analysis of variance (ANOVA), and fitted to a cubic polynomial equation (Eq. 2), yielding high correlation coefficient values:

(2)

Y = b 0 + \sum b j X j + \sum b j j X j 2 + \sum b i j X i X j

A 2nd-order polynomial response function was estimated through regression analysis for variables X1, X2, and X3 using Design Expert software (version 12).

2.6 Statistical analysis

Photocatalytic experiments were conducted in triplicate. The degradation efficiencies showed consistent trends with acceptable experimental variation. Average values were used for discussion. The synthesis was repeated in multiple batches, yielding consistent photocatalytic behavior, indicating good batch-to-batch reproducibility.

3. Results and Discussion

3.1. Characterization of the catalyst

3.1.1. Structure study

The X-ray diffraction patterns of biological ZnO nanoparticles showed distinct peaks confirming the hexagonal wurtzite structure. This matches previous studies, indicating high crystallinity. The average crystallite size of the ZnO-NPs was calculated using Debye-Scherrer’s formula (Eq. 3) [23]:

(3)

D = \frac{0.89 * λ}{β \cos θ}

where D is the particle size (nm), k is a constant equal to 0.89, λ is the wavelength of X-ray radiation (1.5406), is the full-width at half maximum (FWHM) of the peak (in radians), and 2θ is the Bragg angle (degree). The lattice parameters a and c, as well as the unit cell volume V, have been determined using the following equations (Eqs. 4-6) according to Taha et al. [24]:

(4)

a = \frac{λ}{3 \sin θ 100}

(5)

c = \frac{λ}{\sin θ 002}

(6)

V = \frac{3}{2} a^{2} c

The lattice strain ε and the volume lattice V are calculated through the following equation (Eq. 7):

(7)

= \frac{β}{4 \tan θ}

The average size of ZnO-NPs is about 25 nm (Table 1). The strong diffraction peak confirms the ideal crystalline phase [23]. Lattice parameters are provided in Table 2. FTIR analysis identified organic molecules in plant extracts that help ZnO nanoparticles bind. The analysis shows a peak at 3420 cm⁻¹ for O-H stretching and a band at 2348 cm⁻¹ for C=C stretching. A peak at 576 cm⁻¹ (Figure 1) confirms successful synthesis of ZnO-NPs using U. dioica leaf extract, highlighting the role of biomolecules in capping the nanoparticles [10,13,25]. The study explains a green method to create ZnO-NPs using U. dioica leaf extract (Table 3). It details the phytochemical analysis of the extract, which identified several bioactive compounds. The process begins with the reduction of Zn²⁺ ions to Zn atoms, driven by active molecules in the leaf that act as reducing agents. These molecules contain functional groups that help transfer electrons. Next, Zn atoms react to form ZnO nuclei through nucleation, influenced by factors like temperature and pH. After nucleation, the nuclei grow by adding more Zn and O atoms. Finally, bioorganic molecules stabilize the ZnO-NPs and prevent aggregation. This method is simple, cost-effective, and has various applications, including in catalysis and sensors.

Table 1. Average crystallite size.

(hkl)	2ϴ (°)	β (rad)	Cos (ϴ)	k	D (nm)	ɛ
(100)	31,562	0,005224	0,962346	0,89	27,33879637	9,55559E-05
(002)	34,387	0,007864	0,955356	0,89	18,31440521	0,000143846
(101)	36,206	0,007500	0,950549	0,89	19,30011471	0,000137188
(102)	47,729	0,005179	0,91459	0.89	29,04494127	9,47328E-05
(110)	56,838	0,008192958	0,87961	0.89	19,09274631	0,000149863
(103)	62,903	0,006937	0,85325	0.89	23,24658388	0,00012689
(200)	66,335	0,005209	0,83720	0.89	31,54407277	9,52816E-05
(112)	68,361	0,005058	0,82743	0.89	32,874403	9,25195E-05
(201)	69,161	0,005110	0,82352	0.89	32,69338139	9,34707E-05
(004)	72,812	0,006960	0,80502	0.89	24,55620682	0,00012731
(202)	77,058	0,008704	0,78250	0.89	20,20014697	0,000159211
	Crystallite average size (nm)				25,9388272

Table 2. Lattice parameters values of green ZnO-NPs.

ZnO NPs	2ϴ₁₀₀	2ϴ₀₀₂	a (Å)	c (Å)	V (Å³)
ZnO NPs		31.562	34.387	3.297	5.198	69.20

(a) X-ray Diffraction (b) Fourier transforms infrared spectrum of ZnO-NPs.

Table 3. Examples of greener ZnO-NPs and their photodegradation efficiency of CV dye.

Photocatalyst	Synthesis route	Time/Light source	Degradation rate %	Reference
ZnO-NPs	Green process	60 min under UV light	95%	54
ZnO-NPs	Thermal decomposition	120 min under UV light	90%	55
MWCNTs/Cd-ZnO-NPs	Coprecipitation	60 min under UV light	99%	56
G0@ZnO-NPs	Direct solvothermal	80 min under UV light	97%	57
ZnO-NPs	Green process	90 min under UV light	99%	12
ZnO-NPs	Green process	45 min under solar light	100%	58
ZnO-NPs	Chemical synthesis	80 min under UV light	96%	59
ZnO-NPs	Thermal evaporation technique	70 min under UV light	95%	60
ZnO	Green process	60 min under UV light	98%	This work

3.1.2. Morphology study and dynamic light scattering (DLS) measurement

Figures 2(a and b) show SEM and EDS images of ZnO-NPs made using U. dioica extract. The analysis showed that the nanoparticles have a diverse size distribution. The SEM image presents spherical ZnO-NPs that have clustered due to polarization and electrostatic attraction. Elemental analysis using EDX confirmed the presence of zinc and oxygen in the nanoparticles, showing a high purity level. Figure 2(c) displays TEM images, indicating that the ZnO-NPs are spherical with some hexagonal shapes, ranging from 15 to 30 nm in size. The agglomeration of particles is likely caused by bioactive substances in the plant extract. Overall, the nanoparticles are well-dispersed and predominantly spherical (Figure 2d). The size and stability of the biosynthesized ZnO nanoparticles (ZnO-NPs) were studied using DLS. The nanoparticles, made from U. dioica leaf extract, showed a zeta potential of -27.1 mV, indicating high stability as they are highly anionic (Figure 3). The particles measured 20 nm in size, and the polydispersity index was 0.311, suggesting a good size distribution with some smaller particles present [26-28].

(a) SEM image (b) EDX spectra (c) TEM image and (d) Size distribution of ZnO-NPs.

Dynamic light scattering (a) Size distribution (b) Zeta potential of ZnO-NPs.

3.1.3. Optical properties

The UV-vis spectra of ZnO in water show a peak at 373 nm, confirming earlier studies (Figure 4a). ZnO nanoparticles have excellent UV absorption, ideal for industrial and medical uses [28]. The band gap energy was calculated from the absorption edge using equation Eq. (8):

(8)

E g = \frac{h c}{λ}

(a) UV−visible diffuse reflectance spectrum, (b) Photoluminescence spectra of ZnO-NPs.

where h is the Planck’s constant (6.662 × 10⁻³⁴ Js), c the velocity of light (310⁸ m s⁻¹), and λ (373 nm) the wavelength. The band gap energy of the ZnO-NPs was found to be approximately 3.32 eV. These results are consistent with those reported in earlier studies [28]. The photoluminescence spectrum of ZnO shows a UV emission at about 383 nm linked to free-exciton recombination, indicating good crystallinity (Figure 4b). A violet-blue emission near 449 nm arises from intrinsic defects. These defects improve ZnO’s brightness and make it effective for photocatalytic uses due to oxygen vacancies and electron traps.

3.2. Photocatalytic activity of ZnO-NPs

The study explored the breakdown of cristal violet in water using UV light and ZnO-NPs as a catalyst to help reduce water pollution. Various experiments tested how different amounts of the ZnO catalyst affected the degradation of the dye. At neutral pH, the catalyst amount ranged from 1 to 6 mg while keeping the dye volume constant at 10 mL with a concentration of 10 ppm. Results showed that as more catalyst was added, the dye degradation initially increased up to 3 mg, but adding more had little effect. This was because too much catalyst could block light from penetrating, reducing its effectiveness (Figure 5a). Additionally, changing the initial dye concentration showed that higher concentrations resulted in lower degradation rates (Figure 5b). It also examined how contact time impacted dye degradation (Figure 5c). Tests were done at different time intervals from 10 to 100 min, maintaining a constant catalyst amount and dye concentration. Over time, degradation improved until it stabilized when the catalyst surface became saturated with dye molecules. Additionally, changing the initial dye concentration showed that higher concentrations resulted in lower degradation rates. This happened because strong dye colors made it harder for light to penetrate, limiting the reactions needed for effective degradation.

(a) Photocatalytic degradation rates of the biosynthesized ZnO-NPs at different catalyst dose, (b) at different initial concentration dye, (c) at different time, and (d) Kinetic plot for photodegradation of CV dye.

The photodegradation kinetics of CV dye using greener ZnO nanoparticles were analyzed using the Langmuir-Hinshelwood kinetic model. This model is expressed mathematically using equation Eq. (9):

(9)

ln (C 0 / C) = kt

where C₀ is the initial dye concentration, C is the dye concentration at time t, k is the apparent rate constant, and t is the reaction time.

The graph in Figure 5(d) shows a linear relationship that indicates the degradation follows pseudo-first-order kinetics. When UV light hits the ZnO NPs, it creates electron-hole pairs, which only happens if the light energy is high enough. This process leads to the formation of reactive oxygen species (ROS) that effectively degrade organic dyes like CV [13,15]. Photocatalytic activity occurs when the catalyst interacts with UV or visible light. ZnO-NPs generate reactive radicals that help degrade organic dyes like CV dye (Figure 6). The reactions involved in the photocatalytic degradation of crystal violet using ZnO under UV irradiation are summarized in Eqs. (10–13).

(10)

ZnO + h ν (UV - light) \to h^{+} (VB) + e^{-} (CB) photoexcitation

(11)

h^{+} (VB) + H_{2} O \to H^{+} +^{●} OH photoreduction

(12)

e^{-} (CB) + O_{2} \to^{●} O_{2}^{-} photooxidation

(13)

CV + {OH}^{●} /^{●} O_{2}^{-} \to Intermediates \to {CO}_{2} + H_{2} O

Plausible mechanisms involved in photocatalytic degradation of CV dye.

The toxicity of Crystal violet and its degradation products is a complex issue that varies with several factors [29]. It is crucial to reduce their release into the environment. The study found that green ZnO-NPs from U. dioica leaf extract are more effective for degrading CV dye (Table 3).

The observed photocatalytic activity of the ZnO nanoparticles can be attributed to several key factors. First, their high surface area provides a greater number of active sites for interaction with target molecules, enhancing light absorption and surface reactions. Second, surface defects, such as oxygen vacancies, act as traps for electrons and holes, reducing their recombination rate and prolonging charge carrier lifetimes, which facilitates the generation of reactive oxygen species (OH and ·O₂⁻) responsible for pollutant degradation. Third, the exposure of reactive crystalline facets further increases the chemical reactivity of the nanoparticles. Finally, upon light irradiation, electron–hole pairs are generated efficiently, and the nanoscale size ensures close contact with the pollutants, promoting effective degradation. Collectively, these structural and morphological features provide a mechanistic explanation for the enhanced photocatalytic performance observed in the low-cost and environmentally friendly synthesis of ZnO nanoparticles.

The photocatalytic efficiency of ZnO nanoparticles is closely related to their microstructural features [30]. Such microstructural understanding helps explain the observed photocatalytic activity [31]. TEM analysis offers detailed information on particle dimensions, morphology, and surface imperfections, all of which play a crucial role in determining light absorption, charge carrier dynamics, and surface reactions. Understanding these structural aspects provides a mechanistic explanation for the enhanced photocatalytic behavior observed in nanoparticles synthesized via low-cost and environmentally friendly methods. Commercial ZnO was not used as a control in this study. Instead, the photocatalytic performance was compared with previously reported ZnO-based systems in the literature. While both plant-mediated and chemically synthesized nanoparticles can effectively degrade crystal violet under UV light, the biogenic ZnO shows additional benefits. The plant extract acts as both a reducing and stabilizing agent, eliminating the need for toxic reagents and high-temperature conditions typically required in chemical synthesis. Moreover, the green-synthesized ZnO demonstrates similar or slightly higher photocatalytic efficiency, likely due to bioorganic molecules capping the nanoparticles and inducing beneficial surface defects that enhance reactive oxygen species generation. This comparison not only underscores the environmental and safety advantages of the green method but also highlights its potential for cost-effective and scalable wastewater treatment applications, aligning with sustainable chemistry principles. The current study focused on UV-driven photocatalysis due to the intrinsic band gap of ZnO. The extension of this approach to visible or solar irradiation is identified as an important direction for future work.

3.3. Statistical analysis of crystal violet degradation using BBD

3.3.1. Modeling analysis

The BBD was used to study and improve the conditions affecting the degradation of CV by ZnO nanoparticles under UV light (Table 4). Three variables were tested: initial CV concentration, catalyst dose, and contact time. Fifteen experiments helped to optimize the photocatalyst process. The results were analyzed using mathematical and statistical methods, including ANOVA, to understand the relationships between the factors and their effects. The findings include different models, such as linear and quadratic adjustments to fit the BBD response values. The regression Eq. (14) obtained is as follows:

(6)

\begin{matrix} Y = 63, 430 + 1.6290 * A - 0.0 3804 * A^{2} - 9.9001 * B + 2.929 * B^{2} \\ + 0. 1783 * C + 0.00 224 * C^{2} + 0.0 502 * AB - 0.00 731 * AC - 0.0 237 * BC \end{matrix}

Table 4. Box Behnken experimental designs, effect of initial concentration, catalyst dosage and contact time.

Run	Catalyst dose/(mg/L)	[CV]/(ppm)	Contact time (min)	Coded values			Response (% CV)
Run	Catalyst dose/(mg/L)	[CV]/(ppm)	Contact time (min)	A	B	C	Experimental	Predicted
1	1	10	45	-1	-1	0	69.12	68.23
2	3	10	45	1	-1	0	74.0	73.45
3	1	30	45	-1	1	0	82.12	81.99
4	3	30	45	1	1	0	76.88	76.21
5	1	20	20	-1	0	-1	56.98	57.56
6	3	20	20	1	0	-1	60.80	60.12
7	1	20	70	-1	0	1	86.23	86.44
8	3	20	70	1	0	1	79.45	78.996
9	2	20	20	0	0	-1	50.10	50.70
10	2	10	20	0	-1	-1	58.93	58.32
11	2	30	20	0	1	-1	79.15	79.01
12	2	30	70	0	1	1	82.25	83.01
13	2	20	45	0	0	0	92.79	92.75
14	2	20	45	0	0	0	93.74	93.74
15	2	20	45	0	0	0	92.90	92.87

The equations show both positive and negative effects on dye degradation. A positive coefficient means that increasing a factor helps with degradation, while a negative one suggests no improvement or possible reduction in efficiency. All variables and their interactions were found to be significant in the study. The model, supported by strong statistical values, accurately depicted the relationship between response and conditions. Linear terms A and C showed a positive impact, while B had a negative effect. The negative squared term A² indicated an opposing effect, and interaction terms varied in their influence. ANOVA confirmed that most factors were statistically significant and influenced CV degradation. The data shows a strong correlation between observed and theoretical results in the degradation of CV dye, confirming the effectiveness of the quadratic model. The coefficients’ significance is evaluated using p and F values, with those below 0.05 considered significant. The interactions in the photocatalytic degradation process have low p-values and high F-values, indicating their importance. The model’s results for CV photodegradation using ZnO nanoparticles are supported by high R² values, confirming a strong fit with an R² of 99.79%. A significant F-value of 258.28 and a p-value less than 0.0001 further support the model’s relevance. The model’s accuracy rate is noted as 48.9527, with a close correlation between adjusted R² and actual data points from repeated experiments. Figure 7(a) shows a normal probability plot of the residuals for the BBD model, indicating proper assumptions. Figure 7(b) confirms the model’s accuracy with nearly identical values [16,21]. The externally studentized residuals (Figure 7c) show no significant outliers, confirming the adequacy and reliability of the model. The deviation from the reference point (Figure 7d) demonstrates that the response is sensitive to variations in the studied factors, indicating their significant influence.

(a) Normal probability plot verus predicted, (b) residual plot, (c) residual histogram plot, (d) residual versus plot.

3.3.2. Model optimization

Figure 8 shows mean consequence curve data. The goal was to find settings for the highest degradation efficiency, achieving removal rates within 96% of predicted values. The response surface methodology (RSM) model can predict dye removal efficiency.

Optimization plots for the predicted percentage removal of CV dye.

3.3.3. Influences of factors and their interactions on the degradation of dye removal

To find the best conditions for color removal of CV dye, researchers used 3D surface plots and 2D contour plots. Figures 9(a-f) show these plots from the BBD, helping to visualize how three factors affect CV dye degradation. The graphical method used shows that the response surface data align with their research findings [19,20,24,30]. The 3D plots examine the interaction between two factors, showing how they impact degradation rates. For example, Figures 9(a,c,e) highlight the combined effect of catalyst dose and initial dye concentration on CV degradation. The contour plots in Figures 9(b,d,f) confirm these interactions by fixing other variables. Figure 9(b) shows that degradation increases with catalyst dose, especially at around 20-ppm dye concentration. This happens because more dye molecules are available to interact with the catalyst; however, too high a dye concentration can limit light penetration, which reduces degradation efficiency. Figure 9(d) demonstrates that longer contact times with a dye concentration of 20 ppm lead to higher degradation rates, as more photons are absorbed, generating reactive oxygen species needed for breaking down the dye. Yet, once concentration hits its optimal point, degradation slows as the dye concentration becomes too high. According to Figure 9(f), the best degradation rates occur with a 3 mg catalyst dose, as it provides more active sites for the reaction. However, excessive catalysts can cause aggregation, limiting light availability and decreasing effectiveness. Longer contact times generally improve degradation until all active sites on the catalyst are filled, after which extending the time does not help further. This study shows that the Box-Behnken Design effectively optimizes the degradation process. It highlights that increasing catalyst concentration enhances dye degradation and that more degradation occurs over time, emphasizing the importance of both factors in the process.

(a, c, e) 3D and (b, d, f) contour plot showing the effects of (a, d) catalyst dose and initial concentration (b, e) initial concentration and contact time and (c, f) catalyst dose and contact time on CV degradation by ZnO-NPs respectively.

3.3.4. Reusability and regeneration of zinc oxide nanoparticles

The study examined the reuse of ZnO-NPs as a photocatalyst for degrading CV dye. After the reaction, the ZnO-NPs were recovered and washed for reuse. Their effectiveness decreased only slightly after five cycles, from 93% to 89%, showing they are durable and recyclable (Fig. 10). This aligns with previous studies on other compounds [32]. The crystalline structure of the ZnO remained stable after multiple uses, as indicated by X-ray Diffraction (XRD) analysis. Overall, ZnO-NPs maintain their activity and stability even after being reused multiple times.

(a) Reusability performance of ZnO catalyst (b) XRD spectrum after treatment at optimum condition: Catalyst dose 2g/l, CV concentration 20 mg.L-1, and contact time 60 min.

4. Conclusions

This work presents a green and low-cost way for the synthesis of ZnO nanoparticles using Urtica dioica extract as a natural reducing and stabilizing agent. The use of this plant-based extract offers an environmentally benign alternative to conventional chemical methods by avoiding toxic reagents and minimizing energy consumption. The obtained ZnO nanoparticles exhibit good crystallinity and demonstrate effective photocatalytic activity under UV irradiation, which can be attributed to their microstructural characteristics and surface-related features. Beyond laboratory-scale performance, the simplicity of the synthesis process and the availability of the raw materials suggest potential applicability in wastewater treatment. Nevertheless, further studies are required to evaluate the stability of the ZnO-NPs under realistic wastewater conditions, assess long-term reusability, and explore their activity under visible or solar irradiation. In addition, future work should address comparative benchmarking, detailed toxicity assessment, and energy–cost analysis to fully validate the practical and environmental advantages of this green synthesis approach.

Acknowledgment

The authors would like to thank the Deanship of Scientific Research at Shaqra University for supporting this work.

CRediT authorship contribution statement

The authors confirm sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation.

Declaration of competing interest

There are no conflicts of interest.

Declaration of generative AI and AI-assisted technologies in the writing process

The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.

Data availability

All data generated or analyzed during this study are included in this published article

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1. Introduction

2. Materials and Methods

2.1. Plant extract
2.2. Synthesis of zinc oxide nanoparticles
2.3. Material characterization
2.4. Photocatalytic activity of nanoparticles
2.5. Box–Behnken experimental design
2.6 Statistical analysis

3. Results and Discussion

3.1. Characterization of the catalyst
3.2. Photocatalytic activity of ZnO-NPs
3.3. Statistical analysis of crystal violet degradation using BBD

4. Conclusions

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[17] Caliskan U.K., Aka C., Oz M.G.. Plants used in anatolian traditional medicine for the treatment of hemorrhoid. Records of Natural Products. 2017;11:235-250.
[Google Scholar]

[18] Ibrahim M., Rehman K., Razzaq A., Hussain I., Farooq T., Hussain A., Akash M.S.H.. Investigations of phytochemical constituents and their pharmacological properties isolated from the genus urtica: Critical review and analysis. Critical Reviews in Eukaryotic Gene Expression. 2018;28:25-66. https://doi.org/10.1615/CritRevEukaryotGeneExpr.2018020389
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Applications of materials with high cleavage power and quantum efficiency for water treatment

Abstract

Keywords

Box-Behnken design

Photocatalytic activity

RSM technique

U. dioica L

Zinc oxide nanoparticles

1. Introduction

2. Materials and Methods

2.1. Plant extract

2.2. Synthesis of zinc oxide nanoparticles

2.3. Material characterization

2.4. Photocatalytic activity of nanoparticles

2.5. Box–Behnken experimental design

2.6 Statistical analysis

3. Results and Discussion

3.1. Characterization of the catalyst

3.1.1. Structure study

3.1.2. Morphology study and dynamic light scattering (DLS) measurement

3.1.3. Optical properties

3.2. Photocatalytic activity of ZnO-NPs

3.3. Statistical analysis of crystal violet degradation using BBD

3.3.1. Modeling analysis

3.3.2. Model optimization

3.3.3. Influences of factors and their interactions on the degradation of dye removal

3.3.4. Reusability and regeneration of zinc oxide nanoparticles

4. Conclusions

Acknowledgment

CRediT authorship contribution statement

Declaration of competing interest

Declaration of generative AI and AI-assisted technologies in the writing process

Data availability

References

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