# Synthesis of an original Bi12CoO20/ZnO nanocomposites for lead adsorption

Serine Madji, Elhadj Mekatel, Mohamed Belmedani, Julie Cosme, Sarra

Zouaoui, Julien Vieillard

► To cite this version:

Serine Madji, Elhadj Mekatel, Mohamed Belmedani, Julie Cosme, Sarra Zouaoui, et al.. Synthesis of an original Bi12CoO20/ZnO nanocomposites for lead adsorption. Materials Science and Engineering: B, 2025, 319, pp.118345. 10.1016/j.mseb.2025.118345. hal-05421800

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Submitted on 23 Jan 2026

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# Synthesis of an original Bi₁₂CoO₂₀/ZnO nanocomposites for lead adsorption

Serine Madji<sup>a, *</sup>, Elhadj Mekatel<sup>a</sup>, Mohamed Belmedani<sup>a</sup>, Julie Cosme<sup>b</sup>, Sarra Zouaoui<sup>c</sup>, Julien Vieillard<sup>b, d</sup>

<figure><img src="image_2.png" /></figure>

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## ARTICLE INFO

### Keywords:

- Heavy Metal Adsorption

- Lead Removal

- Bi₁₂CoO₂₀/ZnO Nanocomposites

- Coprecipitation method

- Characterization

## ABSTRACT

This study explores the exceptional potential of Bi₁₂CoO₂₀/ZnO nanocomposites as highly efficient adsorbents for the removal of Lead (II) from aqueous solutions, highlighting their innovative application in wastewater treatment. These nanocomposites combine the unique properties of Bi₁₂CoO₂₀ and ZnO, offering a promising solution for environmental remediation. A comprehensive analysis has been performed on the characterization of the nanomaterials Bi₁₂CoO₂₀, ZnO, and Bi₁₂CoO₂₀/ZnO, where the structural, morphological, and physicochemical properties were examined using various characterization techniques, including thermo-gravimetric analysis, X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, Raman Spectroscopy, Brunauer-Emmett-Teller analysis for specific surface area and pH<sub>PZC</sub>. A parametric study was carried out to evaluate the impact of the main parameters on the lead (II) adsorption process. The experimental results obtained were carefully analyzed to evaluate the kinetics of lead adsorption and to determine the adsorption isotherms by applying two-parameter models. A 99 % yield was achieved at pH 7, 0.25 g L⁻¹, 50 mg L⁻¹ initial concentration, 35 °C and an equilibration time of just 30 min, with a maximum adsorption capacity of 204.081 mg g⁻¹. The pseudo-second-order kinetic model is the most suitable model for describing the experimental data related to the adsorption of Pb(II), indicating that the removal process of Pb²⁺ ions is associated with chemical adsorption, with the rate constant determined to be 1.2732 × 10⁻³ g mg⁻¹ min⁻¹ at a concentration of 50 mg L⁻¹. While Temkin's equilibrium isotherm model proved more appropriate to fit the experimental data and explain the adsorption process. Additionally, photocatalytic degradation experiments under solar irradiation of two organic pollutants (Basic Blue 41 and Sunset Yellow) were conducted using the Bi₁₂CoO₂₀/ZnO nanocomposite to confirm its dual functionality, and the results were satisfactory. These findings demonstrate the nanocomposites' potential for both adsorption and photocatalysis, marking them as promising candidates for advanced, sustainable water purification technologies.

## 1. Introduction

Water is a vital resource for life on Earth, both aquatic and terrestrial. It is used for human consumption, agriculture, and energy production. Its pollution is a major problem that threatens the health of ecosystems and humans. Environmentalists are increasingly concerned about this problem. The quality of drinking water is a growing challenge to global public health [1,2]. Industrial activities are a major cause of the degradation of surface water quality. Various pollutants such as pesticides, agricultural products, pharmaceutical products, and heavy metals could be released into the environment due to the leaching of industrial effluents [3–6]. Heavy metals are a growing concern for researchers

worldwide because they are more toxic to aquatic organisms than other types of pollutants and are not biodegradable, leading to bio-accumulation effects [7]. The accumulation of heavy metal ions in environmental water is due to a combination of factors, including industrial activities, such as electrolysis, electroplating, and metal smelting, as well as chemical contaminants present in the environment [8]. In addition, lead is one of the three most toxic metals (lead, mercury, and cadmium), even at low concentrations compared to other metals [9]. Lead can bioaccumulate, meaning it can build up in living organisms at the individual level and in the food chain. Therefore, controlling potentially hazardous chemicals in wastewater is a major challenge, but it is necessary to implement appropriate measures to treat and eliminate

<footnote><sup>a</sup> Laboratory of Transfer Phenomena, Faculty of Mechanical and Process Engineering (USTHB), B.P.32, El-Alia, Algeria</footnote>

<footnote><sup>b</sup> Univ Rouen Normandie, INSA Rouen Normandie, CNRS, Normandie Univ, CARMEN UMR 6064, INC3M FR 3038, 55 rue Saint Germain, 27000 Evreux, France</footnote>

<footnote><sup>c</sup> Applied Organic Synthesis Laboratory, Faculty of Exact and Applied Sciences, University Oran1, 31000 Algeria</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: serine.madji@gmail.com (S. Madji).</footnote>
them permanently. These measures must comply with treatment standards, operational objectives, and economic considerations, including investment and operational costs [6,10].

Many water purification processes are currently used, including chemical precipitation, flocculation and chemical coagulation, membrane filtration, flotation, photocatalysis, and adsorption. These processes are chosen based on their simplicity, efficiency in degrading non-biodegradable substances, environmental friendliness, and low cost [11,12]. Adsorption is a promising method for the removal of heavy metals from wastewater, due to its many advantages, including its cost-effectiveness, practicality, efficiency, ease of use, flexibility, and regenerability [6,8,13]. This process involves the attachment of molecules of a fluid (liquid or gas), called adsorbate, to the surface of a porous or non-porous solid, called adsorbent. Adsorbate molecules are attracted and held to the surface of the adsorbent by intermolecular interactions [14]. Several adsorbents have been used for heavy metal removal, including activated carbon [15], silica gel, zeolite [16] and clays [17]. However, these conventional adsorbents have a number of drawbacks due to their limited regeneration capacity, poor metal ion kinetics, high cost, low stability, and irregular pore size distribution [18,19]. Therefore, to overcome these limitations, researchers are focusing on the development of new adsorbent materials. Currently, nanomaterials are attracting significant interest as adsorbents in the decontamination of heavy metal laden wastewater thanks to their advantages [20,21], in particular their non-toxic nature, availability, nanometric size, high affinity for metal ions, long-term chemical stability, photocatalytic activity, and corrosion resistance. What's more, they can be recycled and reused repeatedly, making them cost-effective, and particularly attractive for adsorbing heavy metal ions. Among the most commonly used nanomaterials are metal nanomaterials and metal oxides [22] such as zinc oxide (ZnO), titanium dioxide (TiO₂) [23], iron oxide and aluminum oxide (Al₂O₃) nanoparticles [24]. These nanomaterials are also classified as semiconductors, and show notable efficacy in the reduction of metal ions as well as in the degradation of organic contaminants by photocatalytic processes, thanks to their exceptional photocatalytic properties.

In this paper, a new composite adsorbent based on metal oxide nanomaterials has been prepared by the coprecipitation method, and the adsorption performance of Pb (II) on this nano-adsorbent has been studied. Our choice focused on combining bismuth cobalt oxide (Bi₁₂CoO₂₀) nanoparticles with zinc oxide (ZnO). Zinc oxide (ZnO), a semiconductor, has garnered increasing attention in recent years due to its remarkable properties, including non-toxicity, environmental friendliness, high electron mobility, cost-effective synthesis, and high adsorption capacity [25,26]. Therefore, integrating the adsorption properties of ZnO with the distinctive characteristics of Bi₁₂CoO₂₀ could provide a significant advantage by enhancing the adsorption efficiency of the nanocomposites by increasing the overall surface area available for pollutant adsorption ([27,28]. These nanocomposites also exhibit synergistic effects resulting from the surface attachment between zinc oxide and cobalt oxide sillenite, a broad visible light absorption, an abundance of reactive sites, and a reduced charge carrier recombination rate. Thus, the formation of these nanocomposites significantly enhances their dual functionality by optimizing both pollutant adsorption and photocatalytic efficiency, thereby providing a more effective and versatile approach compared to conventional materials [29].

Numerous studies have focused on the synthesis and performance of various nanocomposites for adsorption and photocatalytic applications. For instance, Bita Taghiloo et al. developed a composite by integrating TiO₂, carbon quantum dots, and alginate, achieving effective adsorption and photodegradation of methylene blue. Their study reported an adsorption capacity of 44.13 mg g⁻¹ within 90 min [30]. Dadan Hadian et al. concluded that the use of the TiO₂/ZnO/SiO₂ nanocomposite is highly effective and promising for the removal of Pb(II) from wastewater, achieving a removal rate of 99.5 % [28].

The application of such composite to treat water is original and the

results presented in this work are promising. These nanocomposites have demonstrated excellent photocatalytic performance for the degradation of a pharmaceutical product (Amoxicillin) with a maximum removal rate of 85 % [31]. This is primarily attributed to the reduction in bandgap energy during the creation of the Bi₁₂CoO₂₀/ZnO. Moreover, they exhibit excellent stability and high reusability, making them promising for large-scale industrial applications while reducing operational costs and environmental impact. With these characteristics, they effectively overcome the limitations of conventional nanomaterials, offering an innovative and sustainable solution for water purification. The main objective of this study is to investigate whether these composite nanomaterials exhibit dual functionality, namely their ability to act both as an effective adsorbent and as a high-performance photocatalyst.

## 2. Experimental

### 2.1. Chemicals

Zinc oxide (ZnO) (99.97 %), bismuth nitrate pentahydrate [Bi(NO₃)₃·5H₂O] (98.5 % Chem-Lab), cobalt chloride hexahydrate [CoCl₂·6H₂O] (98 % Biochem), hydrochloric acid (HCl) (37 %), sodium hydroxide (NaOH) (98 %) and nitric acid (HNO₃) (65 %) were used to form the heterosystem (Bi₁₂CoO₂₀/ZnO). Lead nitrate (Pb(NO₃)₂) was purchased from Sigma Aldrich. All the solutions are prepared with distilled water.

### 2.2. Preparation of the nanocomposites Bi₁₂CoO₂₀/ZnO

Cobalt bismuth oxide nanoparticles Bi₁₂CoO₂₀, were prepared by the coprecipitation route [31] from stoichiometric amounts of cobalt chloride [Cl₂Co·6H₂O] and bismuth nitrate [Bi(NO₃)₃·5H₂O]. 5 % Nitric acid (65 %) is added to the stoichiometric solution to promote dissolution. The solution is then stirred at 40 °C for 10 min at a speed of 350 rpm and NaOH is added dropwise until the pH reaches 12. The solution is left in a closed container for 24 h at room temperature to allow precipitation followed by washing until neutrality. The resulting gel is filtered with Buchner and then dried at 80 °C for 12 h. The obtained powder is ground, denitrified at 300 °C, and finally calcined at 750 °C for 4 h in a muffle furnace to enhance its crystallinity, to increase its crystallinity [32]. The Bi₁₂CoO₂₀/ZnO nanocomposites were prepared by a simple physical mixing method. The pre-synthesized Bi₁₂CoO₂₀ nanoparticles were combined with commercial ZnO oxide in a ratio of 75 % Bi₁₂CoO₂₀ and 25 % ZnO. Fig. 1 presents the key steps in the formation process of Bi₁₂CoO₂₀.

### 2.3. Characterization of the samples

To better understand the physicochemical properties and structural and morphological behavior of the nanomaterials, we used various characterization techniques. Bi₁₂CoO₂₀ nanomaterials were thermally analyzed using the simultaneous TG-DSC technique, using a Setaram KEP TECHNOLOGIES TG-DSC thermogravimetric analyzer. Mass and heat variations captured by the system are recorded as a function of temperature rise up to 1000 °C. The Bi₁₂CoO₂₀, ZnO, and Bi₁₂CoO₂₀/ZnO samples were characterized by X-ray diffraction (XRD) using a PANalytical Empyrean diffractometer, with Cu Kα monochromatic radiation (λ = 1.540598 Å) in the 2θ range of (5 – 90°). The samples were metallized by a gold layer (18 mA for 360 s, Biorad E5200 device) and the morphology of the surface was studied using a JEOL JCM 6000 scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDS) analysis was performed with a ZEISS EVO 15 scanning electron microscope equipped with an ED-XRF X-ray analyzer. The synthesized of the samples were characterized using a RENISHAW Raman microscope (Centrus OLL824) equipped with a Laser with an excitation wavelength of 532 nm, measurements were carried out in the spectral range from 5 to 700 cm⁻¹. The specific surface area of the
<figure><img src="image_3.png" /><figcaption>Fig. 1. Experimental protocol for the synthesis of Bi$_{12}$CoO$_{20}$ nanomaterials.</figcaption></figure>

samples was determined using the Brunauer-Emmett-Teller (BET) method based on the adsorption-desorption isotherm of inert nitrogen gas, with a liquid density of 0.808 g cm$^{-3}$, a temperature of 77.350 K, and a cross-sectional area of 16.2 Å$^{2}$. The point of zero charge (PZC) was determined using the NaCl (0.01 M) salt addition method over a pH range of 2 to 12 [33].

## 2.4. Lead adsorption experiment

Bi$_{12}$CoO$_{20}$/ZnO nanocomposites were tested for Pb(II) adsorption. To do this, a 1 g L$^{-1}$ Pb(II) stock solution was prepared by dissolving a precise amount of lead nitrate Pb(NO$_{3}$)$_{2}$ in distilled water. Serial dilutions were used to prepare Pb(II) solutions at different concentrations (10 to 100 mg L$^{-1}$). In a typical approach, 0.2 g of the Bi$_{12}$CoO$_{20}$/ZnO nano-adsorbent was placed in a beaker containing 200 mL of a 10 mg L$^{-1}$ Pb(II) solution with a free pH of 5.3. The solution was stirred at a moderate rate on a mechanical shaker for a sufficient time for the system to reach equilibrium. After a predefined time, 15 mL were taken from each solution using a syringe filter. These aliquots were then centrifuged for 15 min at 5000 rpm in a SIGMA 4 K15 centrifuge. After centrifugation, the solutions were filtered through a 0.2 µm nylon filter, thus avoiding peak distortion on polarography analyses. All adsorption experiments were performed in triplicate to ensure the reproducibility and reliability of the results. The remaining concentration of Pb (II) in the supernatant was measured by polarography, using the 797 VA Computation (Metrohm). A preliminary test was conducted to evaluate the effectiveness of the filtration process in retaining lead, both with and without the use of the filter. The results indicated that the filter did not retain any lead. To determine the optimal conditions for lead removal, a parametric study was conducted on the following factors: contact time (0 to 180 min), nanocomposites dose (0.25 to 1 g L$^{-1}$), pH (3 to 9) adjusted using 0.1 M HCl or NaOH, initial lead (II) concentration (10 to 100 mg L$^{-1}$) and temperature (24 to 41 °C). The Pb(II) removal efficiency

and adsorption capacity were calculated using the following equations [34,35]:

$$R(\%) = \frac{C_0 - C_e}{C_0} \times 100 \quad (1)$$

$$q = \frac{C_0 - C_e}{m} \times V \quad (2)$$

The initial and equilibrium concentrations of lead (II) are C$_{0}$ and C$_{e}$, respectively, expressed in mg L$^{-1}$. The volume of the solution is V, in L, and the weight of the nanocomposites used is m, in grams.

All the analyses are triplicated.

# 3. Results and discussion

## 3.1. Characterization of nanomaterials

### 3.1.1. Morphological analysis

Fig. 2 provides information on the morphology and size distribution of particles of BCO (Bi$_{12}$CoO$_{20}$), ZnO, and Bi$_{12}$CoO$_{20}$/ZnO nanocomposites. Fig. 2 (a-b) shows that Bi$_{12}$CoO$_{20}$ powder consisted of fine, uniform cubic particles with an average size of 1.599 µm. SEM images of ZnO nanomaterials (Fig. 4c) reveal relatively uniform nanorod-shaped particles, with the nanoparticle size distribution indicating an average size of approximately 490 nm (Fig. 2d). Furthermore, the SEM images reveal that Bi$_{12}$CoO$_{20}$ nanoparticles are more agglomerated than those of ZnO. This strong agglomeration is mainly attributed to the ultrafine nature of BCO, which promotes Van der Waals interactions and electrostatic forces between the particles, a phenomenon commonly observed in micron-sized powders [36]. Additionally, this difference in agglomeration behavior also results from variations in the composition and physicochemical properties of the two materials [29]. Indeed, BCO has a more complex structure, which influences its degree of
<figure><img src="image_4.png" /><figcaption>Fig. 2. SEM images and size distribution for the Bi₁₂CoO₂₀ (a-b), ZnO (c-d) and Bi₁₂CoO₂₀/ZnO (e-f) nanomaterials.</figcaption></figure>

agglomeration. SEM analysis of Bi₁₂CoO₂₀/ZnO nanocomposites (Fig. 4e) shows that ZnO nanorods are distributed relatively evenly on the surface of cubic Bi₁₂CoO₂₀ particles. However, some local areas of Bi₁₂CoO₂₀ particles appear devoid of ZnO nanorods. The interface quality and uniform distribution of ZnO on the surface of Bi₁₂CoO₂₀ in most observed areas indicate the successful formation of Bi₁₂CoO₂₀/ZnO nanocomposites with an average size of 78.56 nm.

### 3.1.2. EDX elemental analysis

The chemical composition of the sample surface was determined using energy-dispersive X-ray spectroscopy (EDX). EDX analysis was performed on several distinct areas of the Bi₁₂CoO₂₀ sample surface, selected on the SEM image, to verify the homogeneity of the composition. The EDX spectrum of BCO (Fig. 3a) presents characteristic peaks for bismuth, cobalt, and oxygen, which are the expected elements in this compound. Traces of gold and chromium are also detected, as indicated by the spectrum. The presence of these traces is attributed to the

<figure><img src="image_5.png" /></figure>

metallization process of the powder. Fig. 3b clearly shows the presence of zinc and oxygen, the main components of ZnO, through intense characteristic peaks in the EDX spectrum. Residual peaks are also detected, corresponding to the elements silver, gold, and iodine. These residual signals are likely due to impurities in the sample or an artifact of the EDX analysis. The presence of characteristic peaks of bismuth, cobalt, zinc, and oxygen detected in Fig. 3c confirms that the association between Bi₁₂CoO₂₀ and ZnO was successfully achieved within the sample.

### 3.1.3. Structural analysis and phase identification

Fig. 4 shows the X-ray diffractograms of three nanomaterials: pure Bi₁₂CoO₂₀, pure ZnO, and Bi₁₂CoO₂₀/ZnO nanocomposites. The characteristic peaks of pure Bi₁₂CoO₂₀ are observed at 24.69°, 27.66°, 30.36°, 32.86°, 39.51°, 41.53°, 43.47°, 45.34°, 48.91°, 52.30°, 53.94°, 55.54° and 61.68°. These peaks correspond to the (220), (310), (222), (321), (024), (332), (422), (134), (521), (035), (600), (611) and (631)
<figure><img src="image_6.png" /><figcaption>Fig. 3. Energy-dispersive X-ray (EDX) analysis of Bi₁₂CoO₂₀ (a), ZnO (b) and Bi₁₂CoO₂₀/ZnO (c).</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Fig. 4. XRD patterns of nanomaterials (Bi₁₂CoO₂₀, ZnO and Bi₁₂CoO₂₀/ZnO).</figcaption></figure>

indices of the Bi₁₂CoO₂₀ crystal structure respectively (JCPDS No. 01-82-1324). The average crystallite size (D = 45 nm) was calculated using the Debye-Scherrer formula [37], and the results are summarized in Table 1.

$$D = \frac{K\lambda}{\beta\cos\theta} \qquad (3)$$

Where K is the Scherrer constant (K = 0.9), λ is the wavelength of the X-ray beam used (λ = 0.15406 nm), β is the full width at half maximum (FWHM) in radians, and θ is the diffraction angle.

The analysis of the commercial ZnO allows us to identify 8 characteristic peaks (2theta = 31.77°, 34.42°, 36.26°, 47.54°, 56.61°, 62.85°,

<table><caption>Table 1
Structural parameters of sillenite Bi₁₂CoO₂₀.</caption><thead><tr><td>2θ (°)</td><td>β (°)</td><td>Crystallite size (nm)</td><td>D (nm)</td></tr></thead><tbody><tr><td>24.77</td><td>0.24</td><td>33.40</td><td rowspan="11">45</td></tr><tr><td>27.68</td><td>0.14</td><td>55.00</td></tr><tr><td>30.35</td><td>0.13</td><td>62.81</td></tr><tr><td>32.91</td><td>0.18</td><td>44.71</td></tr><tr><td>41.62</td><td>0.16</td><td>53.04</td></tr><tr><td>43.63</td><td>0.35</td><td>24.33</td></tr><tr><td>45.41</td><td>0.12</td><td>66.43</td></tr><tr><td>52.33</td><td>0.22</td><td>39.72</td></tr><tr><td>53.99</td><td>0.19</td><td>45.91</td></tr><tr><td>55.55</td><td>0.25</td><td>35.68</td></tr><tr><td>61.70</td><td>0.23</td><td>39.52</td></tr><tr><td>78.54</td><td>0.27</td><td>36.91</td></tr></tbody></table>

66.39°, 67.96°, and 69.10°) marked by their indices ((100), (002), (101), (102), (110), (103), (200), (112), and (201)), by the data from the JCPDS card No. 01-007-5399. Furthermore, the diffractogram of the Bi₁₂CoO₂₀/ZnO confirms the successful formation of the nanocomposites, highlighting the presence of all crystallization planes of both nanomaterials, Bi₁₂CoO₂₀ and ZnO. The results show that both Bi₁₂CoO₂₀ and ZnO nanomaterials retained their crystal structure even after being mixed, suggesting that these materials possess a good crystalline structure.

### 3.1.4. Raman analysis

The Raman spectrum of Bi₁₂CoO₂₀ nanomaterials (Fig. 5) shows three distinct wave number regions: the 20–200 cm⁻¹ region is associated with Bi-O vibrations, and the 200–600 cm⁻¹ region corresponds to the vibrations of the [BiO5E] octahedra. The 600–700 cm⁻¹ region is attributed to the vibrations of the MO4 tetrahedra in sillenite [38,39]. The lattice of zinc (Zn) atoms vibrates at the frequency of the peak at 80
<figure><img src="image_8.png" /><figcaption>Fig. 5. Raman spectra of Bi₁₂CoO₂₀, ZnO and Bi₁₂CoO₂₀/ZnO.</figcaption></figure>

cm⁻¹, while the vibrations of the oxygen (O) atoms are manifested by the peaks at 419 cm⁻¹ and 459 cm⁻¹. In addition, the weak peaks observed at 359 cm⁻¹ and 363 cm⁻¹ are attributed to the E2(top)-E2 (bottom) multiphoton mode [40]. Analysis of the Raman spectrum of BCO/ZnO reveals the presence of all the vibrational modes characteristic of sillenite and ZnO, confirming the successful formation of the nanocomposites. These results indicate the high crystallinity of the nanomaterials prepared, in agreement with the results of the DRX analysis. The spectral variations observed in the Bi₁₂CoO₂₀/ZnO nanocomposites indicate significant interfacial interactions between the two nanomaterials. The slight shifts in vibration peaks, compared to the pure components, suggest the formation of new metal-oxygen bonds or electronic interactions between them. These modifications result from perturbations in atomic vibration modes induced by charge transfers, structural constraints, or alterations in local electronic environments during nanocomposite formation. These spectral changes not only confirm the effective integration of both nanomaterials but also highlight the complexity of interactions at the nanoscale [32].

### 3.1.5. Study of the specific surface area of nanomaterials

BET analysis was used to characterize the surface of Bi₁₂CoO₂₀, ZnO, and Bi₁₂CoO₂₀/ZnO nanomaterials. The results show that the specific surface area of Bi₁₂CoO₂₀ is 0.884 m² g⁻¹, that of ZnO is 2.887 m² g⁻¹, and that of the Bi₁₂CoO₂₀/ZnO nanocomposites is 2.045 m² g⁻¹. The specific surface area of Bi₁₂CoO₂₀ is higher than that reported in the literature [38], which is likely due to the synthesis method used. This method allows for the production of smaller and more dispersed particles, which increases the specific surface area. The formation of the nanocomposites increased the specific surface area of Bi₁₂CoO₂₀, thanks to the presence of ZnO, which has a higher specific surface area than Bi₁₂CoO₂₀. This increase suggests a strong binding of zinc oxide to the surface of Bi₁₂CoO₂₀, thereby providing additional active sites on the nanocomposite surface for the adsorption of Pb²⁺ ions, which can explain the improved adsorption capacity.

### 3.1.6. Thermo-gravimetric analysis

The sample mass degradation process takes place in three phases, as illustrated by the ATG-DSC thermogram shown in Fig. 6. A first significant decrease in mass, equivalent to 3.26 %, is observed in the 27 °C – 300 °C temperature range, indicating partial dehydration and elimination of volatile matter. This initial phase is followed by a further loss of 1.33 % between 30 °C and 500 °C, attributed to the elimination of nitrates present in Bi(NO₃)₃·5H₂O. The exothermic peak observed in the 500 °C – 800 °C temperature range is attributed to the calcination

<figure><img src="image_9.png" /><figcaption>Fig. 6. Thermo-gravimetric analysis of the Bi₁₂CoO₂₀ nanomaterials.</figcaption></figure>

reaction, promoting the formation of Bi₁₂CO₂₀ nanoparticles. The mass loss observed beyond 750 °C in the Bi₁₂CO₂₀ nanomaterial results from a complex mechanism combining oxygen release and slight structural modifications. This mass loss is primarily characterized by the formation of oxygen vacancies, a potential reduction of cobalt ions (Co³⁺ → Co²⁺), and localized structural rearrangements. Above 850 °C, a gradual decrease in heat flow is observed, indicating the possibility of partial or total melting of certain Bi₁₂CO₂₀ constituents. These observations are consistent with the hypothesis that bismuth oxide nanomaterials melt at these temperatures [41]. The results obtained indicate that the optimum calcination temperature is 750 °C. The thermal stability of Bi₁₂CO₂₀ plays a crucial role in enhancing its durability and reusability in adsorption applications. It ensures the material's structural integrity and adsorption efficiency over multiple cycles, making it a cost-effective and sustainable choice for practical use in environmental remediation [42,43].

### 3.1.7. Point of zero charge ($pH_{PZC}$)

The salt addition method, a simple and rapid approach to determining $pH_{PZC}$, involves several steps. First, 50 mL of NaCl (0.01 M) sodium chloride solution is poured into six separate beakers. Next, the pH of these solutions is adjusted to values of pH 2, 4, 6, 8, 10, and 12 using sodium hydroxide NaOH (0.1 M) and hydrochloric acid HCl (0.1 M). Next, 0.05 g of the sample is added to each beaker, followed by continuous stirring for 48 h. After this step, the NaCl solution is

<figure><img src="image_10.png" /><figcaption>Fig. 7. Zero point of charge of Bi₁₂CoO₂₀/ZnO nanocomposite.</figcaption></figure>
recovered by filtration, and the final pH values of the solutions are measured.

According to the results in Fig. 7, illustrating the evolution of pHf-pHi as a function of the initial adjusted pH, we found that the pH<sub>PZC</sub> of Bi<sub>12</sub>CoO<sub>20</sub>/ZnO was 7.32, indicating a neutral character for this material. Therefore, the surface charge of our material is positive below the pH at the point of zero charge (pH<sub>PZC</sub>), which reduces the adsorption efficiency of Pb<sup>2+</sup> ions. In contrast, above the pH<sub>PZC</sub>, the surface charge becomes negative, thereby promoting the adsorption of Pb<sup>2+</sup> ions due to the strong electrostatic interaction between the negatively charged nanocomposites and the Pb<sup>2+</sup> ions.

## 3.2. Adsorption kinetic of lead adsorption on Bi<sub>12</sub>CoO<sub>20</sub>/ZnO

This study is essential to determine the contact time required to achieve equilibrium adsorption of lead (II) on Bi<sub>12</sub>CoO<sub>20</sub>/ZnO nanocomposites. The results of this study are shown in Fig. 8. The results indicate that the adsorption capacity of Pb<sup>2+</sup> ions increase with increasing contact time, reaching a maximum value corresponding to the maximum adsorption capacity. Moreover, adsorption occurs in three phases: the first, very short phase (5 to 10 min), corresponds to rapid adsorption due to the availability of the most accessible adsorption sites for Pb<sup>2+</sup> ion binding. The second, longer phase (10 to 30 min) corresponds to the diffusion of Pb<sup>2+</sup> ions towards the least accessible sites. The third, constant phase corresponds to adsorption equilibrium, reached when all adsorption sites are saturated. Fig. 8 clearly shows that a contact time of 30 min is sufficient to reach adsorption/desorption equilibrium. The maximum adsorption efficiency for lead (II) is 89 %. In subsequent experiments, a contact time of 30 min was used.

### 3.2.1. Modelling adsorption kinetics using the surface reaction model

Various models can be applied to describe an adsorption mechanism. In this study, two models were applied to evaluate the kinetics of Pb(II) adsorption: the surface reaction model (pseudo-first-order and pseudo-second-order), and the material transfer model (intraparticle diffusion). The experimental study was carried out for different initial Pb(II) concentrations (10, 25, 50 and 100 mg L<sup>-1</sup>), with a Bi<sub>12</sub>CoO<sub>20</sub>/ZnO dose of 0.25 g L<sup>-1</sup>, pH ~ 7 and a temperature of 25 °C.

Lagergren's pseudo-first-order kinetic model suggests that the decisive step in the adsorption reaction is mainly controlled by a phys-isorption phenomenon, and the mathematical equations can be expressed as follows [44]:

<figure><img src="image_11.png" /><figcaption>Fig. 8. Effect of contact time on lead adsorption by Bi<sub>12</sub>CoO<sub>20</sub>/ZnO. (pH ~ 5.3, dose = 1 g L<sup>-1</sup>, [Pb<sup>2+</sup>] = 10 g L<sup>-1</sup>, T = 25 °C).</figcaption></figure>

$$ \ln(q_e - q_t) = \ln q_e - k_1 t \quad (4) $$

With q<sub>t</sub> and q<sub>e</sub> (mg g<sup>-1</sup>), the amounts of metal ions adsorbed at time t and equilibrium respectively. k<sub>1</sub> is the rate constant of the pseudo-first-order adsorption process, expressed in (min<sup>-1</sup>).

Ho and Mc Kay's pseudo-second-order kinetic model suggests that the decisive step in the adsorption reaction is mainly controlled by a chemisorption phenomenon, and the mathematical equation can be expressed as follows [45]:

$$ \frac{t}{q_t} = \frac{1}{k_2 q_e^2} + \frac{1}{q_e} t \quad (5) $$

Where k<sub>2</sub> is the pseudo-second-order adsorption rate constant expressed in g mg<sup>-1</sup> min<sup>-1</sup>.

By plotting the linear forms of these two models, we can identify the kinetic parameters and the order of the overall reaction. The curves and kinetic parameters relating to the surface reaction models are presented and grouped in Fig. 9 and Table 2, respectively.

The correlation coefficient R<sup>2</sup> of the pseudo-first-order kinetic model ranges from 0.6 to 0.9, while that of the pseudo-second-order kinetic model is between 0.999 and 1 for all concentrations. Following graphical analysis and comparison of the R<sup>2</sup> linear regression coefficients, it appears that the pseudo-second-order kinetic model is the most appropriate model for describing the experimental data on Pb(II) adsorption. This indicates that the Pb<sup>2+</sup> ion removal process is related to chemical adsorption, involving the formation of chemical bonds between the metal ion molecules and the functional groups of the nano-adsorbents [46]. These interactions are typically stronger than physisorption and are indicative of a surface reaction occurring at active sites. Similar results have been reported by several researchers, indicating that the adsorption kinetics of Pb(II) is well described by the pseudo-second-order kinetic model [23,47–49]. In addition, the R<sup>2</sup> values are very close to unity, and the adsorption capacity values calculated by this model are similar to the experimental values in the study. On the other hand, the kinetic constants k<sub>2</sub> are inversely proportional to the initial Pb (II) concentration. This is mainly attributed to the saturation of active sites on the nanocomposite surface, observed at higher concentrations.

### 3.2.2. Modeling adsorption kinetics using the intraparticle diffusion model

To complete the kinetic study, the intraparticle diffusion model established by Weber and Morris was applied. This model represents the evolution of the adsorbed quantity as a function of the square root of time, and assumes that the limiting step is adsorption into the pores [50]. The model equation is shown below. The results are shown in Fig. 10 and Table 3.

$$ q_t = k_i t^{1/2} + C \quad (6) $$

Where k<sub>i</sub> is the intraparticle diffusion rate constant expressed in mg g<sup>-1</sup> min<sup>-1/2</sup> and C is a model constant related to the boundary layer thickness expressed in mg g<sup>-1</sup>.

The results indicate that the values of the linear regression coefficients obtained by the intraparticle diffusion model are lower than those obtained by the pseudo-second-order model. Furthermore, the straight lines in the graphical representation of adsorption kinetics for the different initial concentrations do not pass through the origin. Based on these interpretations, it can be concluded that intraparticle diffusion is not the only step influencing the rate of Pb(II) adsorption [51].

Bi<sub>12</sub>CoO<sub>20</sub>/ZnO nanocomposites were prepared with the aim of improving the adsorption capacity of the synthesized Bi<sub>12</sub>CoO<sub>20</sub> and maximizing Pb<sup>2+</sup> removal efficiency. The results are shown in Fig. 11.

Relatively low Pb<sup>2+</sup> adsorption was observed when using pure Bi<sub>12</sub>CoO<sub>20</sub> and ZnO as adsorbents, with yields of, 18.6 % for Bi<sub>12</sub>CoO<sub>20</sub> and 52.8 % for ZnO, corresponding respectively to adsorption capacities of 1.86 mg g<sup>-1</sup> and 5.28 mg g<sup>-1</sup>. A significant improvement in adsorption efficiency was detected by combining the two nanomaterials to
<figure><img src="image_12.png" /><figcaption>**Fig. 9.** Adsorption kinetics for Pb²⁺ on Bi₁₂CoO₂₀/ZnO; Linear representation of the pseudo-first order (a), and the pseudo-second order kinetic model (b) (dose = 0.25 g L⁻¹, pH ~ 7, T = 25 °C).</figcaption></figure>

<table><caption>**Table 2**

Parameters of the pseudo-first-order and pseudo-second-order model.</caption><thead><tr><th rowspan="2">Kinetic models<br>C<sub>0</sub> (mg L<sup>-1</sup>)</th><th colspan="4">Pseudo-first order</th><th colspan="4">Pseudo-second order</th></tr><tr><th>R<sup>2</sup></th><th>q<sub>e</sub></th><th>k<sub>1</sub><br>(min<sup>-1</sup>)</th><th>χ<sup>2</sup></th><th>R<sup>2</sup></th><th>q<sub>e</sub></th><th>k<sub>2</sub><br>(g mg<sup>-1</sup> min<sup>-1</sup>)</th><th>χ<sup>2</sup></th></tr></thead><tbody><tr><td>10</td><td>0.7961</td><td>1.049</td><td>0.0042</td><td>1590.85</td><td>0.9998</td><td>39.698</td><td>0.0459</td><td>0.122</td></tr><tr><td>25</td><td>0.5523</td><td>6.083</td><td>0.01238</td><td>693.29</td><td>0.9998</td><td>87.719</td><td>0.0092</td><td>3.177</td></tr><tr><td>50</td><td>0.9</td><td>6.296</td><td>0.02756</td><td>1404.51</td><td>0.9999</td><td>111.111</td><td>0.0162</td><td>1.045</td></tr><tr><td>100</td><td>0.8497</td><td>71.885</td><td>0.03967</td><td>251.07</td><td>0.9989</td><td>212.766</td><td>0.00168</td><td>4.546</td></tr></tbody></table>

<figure><img src="image_13.png" /><figcaption>**Fig. 10.** Linear representation of the kinetic model of intraparticle diffusion (dose = 0.25 g L⁻¹, pH ~ 7, T = 25 °C).</figcaption></figure>

<table><caption>**Table 3**

Kinetic parameters of the intraparticle diffusion model.</caption><thead><tr><th>C<sub>0</sub> (mg L<sup>-1</sup>)</th><th>k<sub>1</sub> ((mg g<sup>-1</sup> min<sup>-1/2</sup>)</th><th>C (mg g<sup>-1</sup>)</th><th>R<sup>2</sup></th></tr></thead><tbody><tr><td>10</td><td>1.7436</td><td>23.9376</td><td>0.159</td></tr><tr><td>25</td><td>3.5896</td><td>35.285</td><td>0.3357</td></tr><tr><td>50</td><td>4.7828</td><td>54.077</td><td>0.2565</td></tr><tr><td>100</td><td>11.555</td><td>86.55</td><td>0.4916</td></tr></tbody></table>

<caption>**Fig. 11.** Comparison between the adsorption capacity of Bi₁₂CoO₂₀ (on the left), ZnO (in the center) and Bi₁₂CoO₂₀/ZnO nanocomposite. (pH ~ 5.3, dose = 1 g L⁻¹, [Pb²⁺] = 10 g L⁻¹, T = 25 °C),</caption>

formation of nanocomposites with zinc oxide. This suggests a good bond between the two nanomaterials, enabling the creation of additional active sites favorable to the adsorption of Pb²⁺ since the increase in adsorbent surface area is directly proportional to the improvement in its adsorption efficiency [52]. A mass ratio of 75 % Bi₁₂CoO₂₀ and 25 % ZnO was selected for further study.

### 3.3. Optimization of the experimental parameters

#### 3.3.1. Effect of pH

The pH of an aqueous solution is a critical parameter that affects the ability of an adsorbent to remove contaminants, especially heavy metals. The effect of pH on the adsorption of lead (II) ions on the Bi₁₂CoO₂₀/ZnO nanocomposites was studied over a pH range of 3 to 9. The other
parameters were kept constant, namely the dose of nanocomposites (1 g L⁻¹), the lead (II) ion concentration (10 mg L⁻¹), the temperature (25 °C), and the contact time (30 min). The results of (Fig. 12a) show that the Pb²⁺ removal efficiency increases continuously with increasing pH from 3 to 9. This increase in efficiency is due to the formation of more stable complexes between Pb²⁺ and the adsorption sites of the nanocomposites. Moreover, the surface charge of Bi₁₂CoO₂₀/ZnO depends on its point of zero charge, which determines whether the surface is protonated (positively charged) or deprotonated (negatively charged) [33]. At pH < pHₚZC, the surface is positively charged, leading to electrostatic repulsion between Pb²⁺ ions (also positively charged) and the surface, thereby limiting thereby limiting adsorption efficiency. At pH > pHₚZC, the surface becomes negatively charged, promoting electrostatic attraction between Pb²⁺ ions and the nanocomposite. At pH 3, lead (II) is in the form of Pb²⁺ ions. These ions are positively charged. At acidic pH, the Bi₁₂CoO₂₀/ZnO surface is positively charged (pH < 7.32), and H⁺ ions can compete with adsorbate molecules for active sites on the adsorbent surface [53], generally leading to electrostatic repulsion and thus a decrease in adsorption efficiency. Under basic conditions, the nanocomposites surface is negatively charged (pH > 7.32), promoting electrostatic attraction between Pb²⁺ ions and the Bi₁₂CoO₂₀/ZnO surface. This contributes to the increase in adsorption capacity. Moreover, the speciation of Pb²⁺ ions in the solution varies with pH. At acidic pH (pH < 6), lead is primarily present as free Pb²⁺ cations. However, at pH ≥ 7, hydroxy-complexed species such as Pb(OH)⁺ or Pb(OH)₂ can form. These species may interact differently with the surface of the nanocomposites through electrostatic or chemical complexation mechanisms. It is important to note that Pb(OH)₂ precipitation can occur at high alkaline pH [54]. Indeed, these experiments showed that the maximum removal efficiency of Pb²⁺ ions is 92 % at pH 7 and 9. However, pH 7 is a more judicious choice as it allows for high adsorption efficiency while minimizing the adverse effects of pH on the

nanocomposites and to avoid lead precipitation at basic pH levels [55]. pH 7 was chosen as the optimal value for all subsequent experiments. These observations confirm the chemical stability of our heterosystem, as no dissolution of elements has been observed. This stability is attributed to our decision to work within a pH range of 3 to 9, preventing the dissolution of ZnO, especially at highly acidic pH levels, such as pH 2. Several authors have found that the adsorption capacity of lead (II) increases with increasing pH value [19,20,56].

### 3.3.2. Effect of catalyst dose

Fig. 12b shows a slight decrease in adsorption efficiency of around 5 % as a function of increasing the dose from 0.25 to 1 g L⁻¹. At high concentrations, inter-particle interactions trigger the formation of aggregates that significantly reduce the available active surface area, limiting the accessibility of adsorption sites [57]. This phenomenon is explained by a progressive saturation of active sites and a decrease in ion-surface interactions. The formed aggregates partially mask and block fixation sites, creating a physical barrier that impedes the efficient capture of Pb²⁺ ions. Despite this slight decrease, the nanocomposite maintains a remarkably high efficiency (90 %), demonstrating its exceptional potential for treating lead-contaminated water. A maximum adsorption of 95 % was recorded for a dose of 0.25 g L⁻¹, suggesting that this dose is optimal for lead (II) adsorption.

### 3.3.3. Effect of initial lead concentration

The effect of initial Pb(II) concentration on the adsorption process was studied for concentrations ranging from 10 to 100 mg L⁻¹, while the other parameters were maintained at their optimum values. The results are shown in Fig. 12c. The results of the study show that the adsorption efficiency of Pb²⁺ by the Bi₁₂CoO₂₀/ZnO nanocomposites decreases with increasing initial concentration. At high initial concentrations, the available adsorption sites on the surface of the nanocomposites are

<figure><img src="image_14.png" /><figcaption>**Fig. 12.** Parametric study on lead (II) adsorption of Bi₁₂CoO₂₀/ZnO; (a) Effect of pH (dose = 1 g L⁻¹, [Pb²⁺] = 10 g L⁻¹, t = 30 min, T = 25 °C), (b) Effect of catalyst dose (pH ~ 7, [Pb²⁺] = 10 g L⁻¹, t = 30 min, T = 25 °C), (c) Effect of lead (II) concentration (pH ~ 7, dose = 0.25 g L⁻¹, t = 30 min, T = 25 °C).</figcaption></figure>
quickly saturated by Pb²⁺ ions. As a result, the competition between Pb²⁺ ions for the available adsorption sites increases, which reduces the adsorption efficiency. At 10 mg L⁻¹, the initial concentration of Pb²⁺ is low enough that the competition between Pb²⁺ ions for adsorption sites is low. This allows for a large amount of Pb²⁺ ions to be adsorbed, resulting in a high yield of 95 %. At 100 mg L⁻¹, the competition is extremely strong, resulting in a significant decrease in the yield, which drops from 95 % to 84 %. This is mainly due to the reduction in the number of free active sites on the surface of nanocomposites. An optimal value is observed at 50 mg L⁻¹. This optimal value is explained by the fact that at this concentration, the competition between Pb²⁺ ions for adsorption sites is sufficient to maximize the number of Pb²⁺ ions adsorbed, but not too strong to prevent the adsorption of all Pb²⁺ ions. Similar results have been observed by several researchers [46,58,59].

### 3.3.4. Effect of temperature

The influence of solution temperature on the efficiency of Pb²⁺ ion removal by Bi₁₂CoO₂₀/ZnO nanocomposites was examined at four different temperatures (24, 31, 35, and 41 °C) following the previously mentioned adsorption protocol. The study was conducted with a contact time of 30 min, a pH of 7, an initial Pb²⁺ ion concentration of 50 mg L⁻¹, and a dosage of 1 g L⁻¹. Results (Fig. 8f) showed removal rates of 86 %, 89 %, 91 % and 89 % at temperatures of 24 °C, 31 °C, 35 °C and 41 °C, respectively (Fig. 13). These data indicate that adsorption efficiency increases with temperature from 24 °C to 35 °C, then decreases slightly at 41 °C. The increase in adsorption rate is mainly attributed to the increase in kinetic energy [60], thus facilitating the diffusion of adsorbate molecules to the nanoparticle surface. In addition, increasing temperature generally leads to a decrease in solution viscosity [61]. This means that Pb(II) molecules encounter less resistance as they move, facilitating their migration to the Bi₁₂CoO₂₀/ZnO surface. The reduced efficiency of the adsorption process at higher and lower temperatures is attributed to a disruption of the interactions between the adsorbate molecules and the adsorbent nanoparticles [62]. An optimum temperature of 35 °C was recorded.

### 3.4. Thermodynamic parameters

To better understand the equilibrium adsorption mechanism between lead ions and the prepared heterosystem, it is important to study adsorption equilibrium isotherms [63]. To study this equilibrium, several two-parameter adsorption isotherm models have been used, including the Temkin, Freundlich, and Langmuir models [13,64] (Eq. (7), 8, and 9). To identify the model that best describes the experimental

data of the lead (II) adsorption process, it is necessary to model the adsorption isotherms and determine the parameters of each model.

$$q_e = Bln(K_T C_e) \qquad (7)$$

$$q_e = K_f C_e^{1/n} \qquad (8)$$

$$q_e = \frac{q_{max} \times (K_L C_e)}{1 + (K_L C_e)} \qquad (9)$$

The Temkin isotherm describes adsorption as an indirect interaction between the adsorbate and the adsorbent, in which the adsorption energy varies linearly with the adsorbed amount. This variation is represented by the following linear equation [65]:

$$q_e = Bln(K_T) + Bln(C_e) \qquad (10)$$

With K_T (L mg⁻¹) being the adsorption equilibrium constant corresponding to the maximum binding energy, B = (RT/b_T) (J mol⁻¹) the Temkin parameter related to the heat of sorption, R = 8.314 J mol⁻¹ K⁻¹ the universal gas constant, T the absolute temperature in Kelvin (K) and q_e the maximum adsorption capacity (mg g⁻¹).

The Freundlich isotherm describes the adsorption of a gas or liquid onto a solid surface. It assumes that the adsorption is physical and reversible and that it occurs in multiple layers. The linear form of the Freundlich isotherm equation is given by the following equation [66]:

$$lnq_e = ln(K_f) + \frac{1}{n}ln(C_e) \qquad (11)$$

With K_f, the Freundlich isotherm constant, n the heterogeneity factor, and C_e (mg L⁻¹) the equilibrium substrate concentration in the adsorbent. n provides information on the favorability of the adsorption process.

The Langmuir isotherm is a model of adsorption that describes the equilibrium between the adsorption and desorption of a solute on a solid surface. This model assumes that the adsorption takes place on a single layer of adsorbent, the Langmuir isotherm equation (Eq. (12) can be rewritten in the following form [67]:

$$\frac{C_e}{q_e} = \frac{C_e}{q_{max}} + \frac{1}{K_L q_{max}} \qquad (12)$$

The graphical representation of the Langmuir isotherm equation allows for the determination of two key parameters of the model: the maximum adsorption capacity, q_max, and the equilibrium constant, K_L. In addition to these two parameters, the separation factor, R_L, can also be used to characterize the adsorption process. The separation factor is defined as follows [68]:

$$R_L = \frac{1}{1 + K_L C_0} \qquad (13)$$

The separation factor is an indicator of the favorability of the adsorption process. If R_L > 1, the adsorption is unfavorable. If R_L = 1, the adsorption is linear. If 0 < R_L < 1, the adsorption is favorable. If R_L = 0, the adsorption is irreversible.

To select the model that best fits the experimental data, the Chi-square statistical test (χ²) is calculated in addition to the correlation coefficient (R²) [69].

$$\chi^2 = \sum_{i=1}^{n} \frac{(q_{e,exp} - q_{e,cal})^2}{q_{e,cal}} \qquad (14)$$

Where n indicates the number of measurement points, q_{e,exp} refers to the observed experimental results, and q_{e,cal} corresponds to the values calculated using the models.

The results of the application of two-parameter isotherm models are presented in Table 4 and graphically represented in Fig. 14.

Based on the comparison of R² regression coefficients, the Temkin isotherm model (R² = 0.961) provides the best fit for Pb(II) adsorption

<figure><img src="image_15.png" /><figcaption>Fig. 13. Effect of temperature on lead removal by Bi₁₂CoO₂₀/ZnO (pH ~ 7, dose = 1 g L⁻¹, [Pb²⁺] = 50 g L⁻¹, t = 30 min).</figcaption></figure>
<caption>**Table 4**</caption>

The Langmuir, Freundlich and Temkin parameters of the Pb²⁺ adsorption isotherms.

<table><thead><tr><th>Isotherms</th><th>Langmuir</th><th>Freundlich</th><th>Temkin</th></tr></thead><tbody><tr><td>Parameters</td><td>q<sub>max</sub> = 204.081 mg g<sup>-1</sup><br>K<sub>L</sub> = 0.7 L mg<sup>-1</sup><br>χ<sup>2</sup> = 11.276</td><td>1/n =<br>1.972<br>K<sub>f</sub> =<br>65.3854<br>χ<sup>2</sup> =<br>3650.05</td><td>B = 49.83<br>J mol<sup>-1</sup><br>K<sub>T</sub> = 4.243<br>L mg<sup>-1</sup><br>χ<sup>2</sup> = 4.855</td></tr><tr><td>p-values</td><td>0.00908</td><td>0.0516</td><td>0.01972</td></tr><tr><td>R<sup>2</sup></td><td>0.924</td><td>0.899</td><td>0.961</td></tr><tr><td>R<sub>L</sub></td><td>10<br>ppm<br>0.125</td><td>25<br>ppm<br>0.054</td><td>50<br>ppm<br>0.0277</td><td>100<br>ppm<br>0.0141</td></tr></tbody></table>

on Bi₁₂CoO₂₀/ZnO nanocomposites, outperforming both the Langmuir (R² = 0.92) and Freundlich (R² = 0.899) models. The Temkin model stands out for its ability to characterize the specific interactions between Pb²⁺ ions and the nanocomposite surface, accounting for the energetic heterogeneity of adsorption sites. The positive B value [19,63] indicates an exothermic process of a physical nature, with relatively weak interactions between Pb²⁺ ions and the surface. Furthermore, the exothermic nature of adsorption suggests that its efficiency decreases at higher temperatures, aligning with experimental observations. Therefore, the Temkin model effectively captures the adsorption behavior by considering both the heat of adsorption and the nature of the interactions between Pb²⁺ ions and the material surface [70].

In addition, the maximum adsorption capacity calculated from the Langmuir model (q<sub>e</sub> = 204.081 mg g<sup>-1</sup>) is close to that determined experimentally (q<sub>e</sub> = 175.62 mg g<sup>-1</sup>). The values of the dimensionless factor R<sub>L</sub> are between 0 and 1 for the different initial concentrations, indicating that the Langmuir model presents the experimental results well, suggesting that the adsorption process is favorable and takes place in a single homogeneous layer of the adsorbent. On the other hand, the Freundlich model is not suitable for describing the experimental results

of the Pb²⁺ ion adsorption equilibrium due to the high value of its parameter 1/n (= 1.922).

At this stage, it is pertinent to compare the capacity of our synthesized nanocomposites Bi₁₂CoO₂₀/ZnO with the previously reported results in the literature for Pb²⁺ adsorption as shown in Table 5 [71–77]. Comparing our study with the literature, we conclude that the synthesized nano-composites rank among the best adsorbents for Pb²⁺ metal ion removal, due to their excellent adsorption capacity and their fast kinetics. This makes them highly competitive compared to other commonly used adsorbents such as ZnO and TiO₂. Consequently, we can affirm that the use of nanomaterials as adsorbents represents a relevant and innovative option.

However, several recent studies have reported higher adsorption capacities for lead removal. Archana Gupta et al. [78], demonstrated that lignin, as a natural adsorbent, is particularly effective, achieving an

<caption>**Table 5**</caption>

Comparison with previous studies reported for Lead removal.

<table><thead><tr><th>Adsorbents</th><th>Maximum capacity<br>q<sub>max</sub> (mg g<sup>-1</sup>)</th><th>Conditions</th><th>References</th></tr></thead><tbody><tr><td>Fe₂O₃</td><td>68.9</td><td>pH ~ 5, T = 45 °C,<br>dose = 0.2 g L<sup>-1</sup></td><td>[64]</td></tr><tr><td>Commercial<br>activated carbon</td><td>20.3</td><td>pH ~ 7, T = 25 °C, t<br>= 180 min</td><td>[65]</td></tr><tr><td>CuO/ZnO-T</td><td>41.753</td><td>pH ~ 10, dose = 1 g</td><td>[66]</td></tr><tr><td>ZnO-T</td><td>20.759</td><td>L<sup>-1</sup>, t = 6h</td><td></td></tr><tr><td>LaFeO₃: CoFe₂O₄</td><td>105.96</td><td>pH ~ 6.5, t = 60 min,<br>dose = 2 g L<sup>-1</sup></td><td>[67]</td></tr><tr><td>NiTiO₃</td><td>72</td><td>pH ~ 5, t = 20 min,</td><td>[68]</td></tr><tr><td>ZIF/NiTiO₃</td><td>155</td><td>T = 25 °C</td><td></td></tr><tr><td>GO/ZnO/CS</td><td>110.88</td><td>pH ~ 5, t = 120 min</td><td>[69]</td></tr><tr><td>ZnO</td><td>58.88</td><td>pH ~ 7, dose = 2 g L<sup>-1</sup></td><td>[70]</td></tr><tr><td>TiO₂</td><td>55.04</td><td>T = 41 °C,<br>t = 120 min</td><td></td></tr><tr><td>Bi₁₂CoO₂₀/ZnO</td><td>204.08</td><td>pH ~ 7, dose = 0.25<br>g L<sup>-1</sup>,<br>T = 25 °C, t = 30 min</td><td>This study</td></tr></tbody></table>

<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /><figcaption>**Fig. 14.** Adsorption isotherm modeling; Langmuir (a), Freundlich (b), and Temkin isotherms (c); (t<sub>eq</sub> = 30 min, pH ~ 7, Bi₁₂CoO₂₀/ZnO) = 0,25 g L⁻¹, T = 20 °C).</figcaption></figure>
adsorption capacity of 1865 mg g⁻¹ for Pb²⁺ ions. They also observed that a synthetic polymer exhibited a notable adsorption capacity of 584.4 mg g⁻¹. Similarly, Khezami L. et al. concluded that KOH-activated carbon could reach an adsorption capacity of 355 mg g⁻¹. Furthermore, A. Modwi et al. [79], reported that Cu/ZnO nanocomposites displayed a maximum adsorption capacity of 1111 mg g⁻¹ for lead removal. These variations in performance can be attributed to several factors, including the chemical nature of the functional groups present in each adsorbent, their porous structure, the complexity of their chemical architecture, and the synthesis method used. Although the adsorption capacity of our Bi₁₂CoO₂₀/ZnO nanocomposites (204.081 mg g⁻¹) is lower than that of some other materials, they remain a competitive solution for Pb²⁺ removal due to their enhanced selectivity, fast adsorption kinetics, excellent thermal and chemical stability, and strong affinity for other types of pollutants, particularly organic contaminants.

After the adsorption experiments, the recovered Bi₁₂CoO₂₀/ZnO nanocomposites were characterized by X-ray diffraction and energy-dispersive X-ray spectroscopy. The results are presented in Fig. 15. The diffractogram shows that the Bi₁₂CoO₂₀/ZnO retained their

crystalline structure after the adsorption experiments, with no significant peak shifts or deformations, suggesting stability in both composition and crystalline phase. The EDX analysis further confirms the presence of the main elements (Bi, Co, Zn, and O) without the appearance of new impurity peaks. These results demonstrate the stability of nanocomposites after adsorption, thereby reinforcing their potential for reuse. This structural stability serves as an initial qualitative indication of their ability to be regenerated and reused in successive adsorption cycles.

### 3.5. Photocatalytic degradation of organic pollutants using Bi₁₂CoO₂₀/ZnO nanocomposites under solar irradiation

According to the results of our study, the synthesized nanocomposite proves to be one of the most effective adsorbents to eliminate Pb(II) due to its exceptional adsorption properties. Photocatalytic degradation experiments under solar irradiation of two organic pollutants were conducted using the Bi₁₂CoO₂₀/ZnO nanocomposites to confirm its dual functionality. Two dyes were chosen: Basic Blue 41 (λmax = 610 nm) and

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /><figcaption>Fig. 15. X-ray diffractogram (a) and EDX spectrum (b) of Bi₁₂CoO₂₀/ZnO before and after recycling.</figcaption></figure>
Sunset Yellow ($\lambda_{max}$ = 480 nm). The photocatalytic experiments were carried out in an open system in batch mode using a simple setup. The experiments were conducted on sunny days, where the reactors, initially subjected to adsorption for 1 h, were then exposed to solar irradiation for 4 h. The average light intensity of the solar source was approximately 910 W.m$^{-2}$. The solution was continuously stirred to maintain the homogeneity. At regular time intervals, 5 mL aliquots were taken, protected from light using opaque wrapping, and then centrifuged at a speed of 4500 rpm for 15 min before being analyzed by UV-visible spectrophotometry (Specord 200 plus) Adsorption and photocatalysis experiments were conducted under the following operational conditions (unadjusted pH; [pollutant] = 10 mg L$^{-1}$; dose of Bi$_{12}$CoO$_{20}$/ZnO = 1 g L$^{-1}$; t (adsorption) = 1 h; t (photocatalysis) = 4 h). The results are shown in Fig. 16.

The results indicate that a maximum removal rate of 99 % was achieved for Basic Blue 41 within just 120 min of treatment, while an optimal degradation of 97 % was recorded for Sunset yellow after 240 min of treatment. The photocatalytic performance of the nanocomposites varies between compounds due to differences in the structure, behavior, and molecular complexity of each dye. These findings clearly demonstrate that the Bi$_{12}$CoO$_{20}$/ZnO nanocomposites exhibit remarkable photocatalytic activity under solar irradiation, providing an effective solution for the degradation of organic pollutants. Moreover, the observed dual functionality of these nanocomposites, serving as both efficient adsorbents and photocatalysts, highlights their potential for practical applications in sustainable water treatment technologies. This dual capability sets them apart from other materials, offering a more versatile and efficient approach to tackling environmental pollution.

### 3.6. Economic analysis

The coprecipitation synthesis process demonstrated substantial energy consumption, primarily attributed to thermal requirements during various reaction stages. A quantitative analysis of this energy expenditure was conducted by evaluating each step outlined in Table 6. Through precise monitoring of laboratory-scale equipment power ratings and their respective operational durations, we determined a total energy consumption of 38.7 kWh g$^{-1}$ of nanocomposite for a 10 g batch. The energy consumption was calculated using the following equation [80]:

$$E = \frac{\sum_{i=1}^{n} (P_i t_i)}{10^3 m} \quad (15)$$

<figure><img src="image_21.png" /><figcaption>Fig. 16. Evaluation of the photocatalytic efficiency of Bi$_{12}$CoO$_{20}$/ZnO nanocomposites on the removal of Basic Blue 41 and Sunset yellow under solar irradiation (unadjusted pH; [pollutant] = 10 mg L$^{-1}$; dose of Bi$_{12}$CoO$_{20}$/ZnO = 1 g L$^{-1}$). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

<table><caption>Table 6
Energy Consumption of Each step.</caption><thead><tr><th>Synthesis steps</th><th>P (W)</th><th>t (h)</th><th>energy consumption (KWh)</th></tr></thead><tbody><tr><td>Stirring</td><td>100</td><td>1</td><td>0.1</td></tr><tr><td>Heating</td><td>415</td><td>3</td><td>1.245</td></tr><tr><td>Drying</td><td>1600</td><td>24</td><td>384</td></tr><tr><td>Calcination</td><td>3000</td><td>4</td><td>12</td></tr></tbody></table>

where $P_i$ represents the rated power (W) of equipment used in processing stage i, $t_i$ denotes the total operational duration (h) for each stage, and m corresponds to the final dry mass (g) of the synthesized nanocomposite.

Based on the current industrial electricity rate in France (0.12 €/kWh), this translates to an energy cost of 4.64 €/g. Future optimization efforts could focus on: low-temperature precipitation pathways, continuous flow reactors to minimize thermal energy losses, and integration of renewable energy sources for heating stages.

### 4. Conclusion

Bi$_{12}$CoO$_{20}$/ZnO nanocomposites were developed by combining Bi$_{12}$CoO$_{20}$ nanomaterials, synthesized by the co-precipitation method, with commercially sourced ZnO nanomaterials. These nanocomposites were used as adsorbents for the removal of Pb$^{2+}$ ions. Analysis of structural, morphological, optical and physico-chemical properties has shown that the formation of these nano-composites contributes to a significant improvement in performance and adsorption capacity for Pb$^{2+}$ ions. Experimental results showed that lead (II) adsorption on Bi$_{12}$CoO$_{20}$/ZnO nanocomposites is very rapid, reaching equilibrium in just 30 min. A maximum yield of 99 % was obtained for a pH ~ 7, a dose of 0.25 g L$^{-1}$, and an initial concentration of 50 mg L$^{-1}$. The pseudo-second-order kinetic model proved to be the most appropriate for describing the experimental data on Pb (II) adsorption. The equilibrium adsorption data showed that the Temkin and Langmuir isotherm models proved to be the most suitable for fitting the experimental data, suggesting a monolayer adsorption of metal ions on a homogeneous surface of the nanocomposites with an adsorption capacity of 204.081 mg g$^{-1}$.

An important consideration in the development of Bi$_{12}$CoO$_{20}$/ZnO nanocomposites is their potential environmental impact and scalability for industrial applications. The synthesis method employed (coprecipitation) is relatively simple, cost-effective, and avoids the use of hazardous reagents, making it eco-friendly. Moreover, the use of commercially sourced ZnO aligns with the principles of green chemistry by leveraging readily available materials. From an environmental perspective, the high adsorption capacity (204.081 mg g$^{-1}$) and rapid adsorption kinetics (30 min) indicate that these nanocomposites could effectively reduce the amount of adsorbate required, thus minimizing waste generation. Furthermore, the absence of significant dissolution of ZnO and Bi$_{12}$CoO$_{20}$ components in the pH range studied suggests good chemical stability, which reduces the risk of secondary pollution. In terms of practical applications, Bi$_{12}$CoO$_{20}$/ZnO nanocomposites show great promise in specific industries, particularly in wastewater treatment and environmental remediation. Due to their excellent adsorption capacity for Pb$^{2+}$ ions, they could be employed in the removal of heavy metals from industrial effluents, such as those generated in mining, electroplating, and battery manufacturing. For future research, it would be valuable to explore the desorption and regeneration of the adsorbent to assess its long-term applicability. In this regard, future work will focus on conducting reusability tests. Further studies will also evaluate the adsorption performance of Bi$_{12}$CoO$_{20}$/ZnO nanocomposites across multiple heavy metal ions, such as cadmium, chromium, and mercury, to assess their broader applicability in wastewater treatment. Optimizing the synthesis process to enhance scalability and reduce production costs is another critical step toward facilitating large-scale implementation. This could involve refining the coprecipitation method
or integrating green chemistry principles to improve efficiency and sustainability. In addition, future research could focus on improving the adsorption capacity and selectivity of the nanocomposite, potentially through surface modifications or hybridization with other materials to enhance performance for specific pollutants. Exploring novel modification strategies, such as doping with metal or non-metal elements or functionalizing with organic ligands, could further improve the material's effectiveness. Finally, incorporating the adsorbent into a continuous-flow water treatment system would be a critical step for real-world applications, facilitating more efficient and scalable deployment for industrial wastewater treatment. This would enhance the practical applicability of the study and pave the way for large-scale implementation.

## 5. Perspectives and industrial applicability

The scalability and industrialization of Bi₁₂CoO₂₀/ZnO nanocomposites for industrial wastewater treatment pose certain challenges, including large-scale reproducibility and integration into existing treatment systems. To address these challenges, strategies such as optimizing synthesis protocols to reduce energy consumption and adopting fixed-bed or membrane-based systems to minimize material losses can be implemented. The regeneration and reusability of Bi₁₂CoO₂₀/ZnO nanocomposites represent a critical research avenue for their sustainable environmental application potential. Future studies should systematically evaluate the material's performance after multiple adsorption cycles, quantifying the efficiency loss at each cycle. The objective would be to determine the structural stability of the nanocomposite, its ability to maintain adsorption properties after regeneration, and to develop an optimal protocol for metal ion recovery and restoration of active sites [81]. Additionally, the toxicity of the material, particularly the leaching of Bi, Co and Zn into the solution, will be assessed to ensure its environmental safety and suitability for real-world applications. These efforts, combined with strict regulatory compliance and cost-benefit analyses, will demonstrate their potential as a scalable and efficient solution for industrial wastewater treatment.

### CRediT authorship contribution statement

**Serine Madji:** Writing – original draft, Methodology, Investigation.
**Elhadj Mekatel:** Validation, Investigation. **Mohamed Belmedani:** Supervision, Resources.
**Julie Cosme:** Methodology, Investigation. **Sarra Zouaoui:** Investigation.
**Julien Vieillard:** Writing – review & editing, Writing – original draft, Supervision, Funding acquisition.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgment

I would like to emphasize that this work benefited from the funding provided by the University of Sciences and Technology Houari Boumediene in Algiers within the framework of a short-term internship carried out at the University of Rouen Normandy. These research activities were conducted through a scientific collaboration between the Laboratory of Transfer Phenomena at the Faculty of Mechanical Engineering and Process Engineering of USTHB under the guidance of Mr. M. Belmedani and Mr. M. El Hadj, and the COBRA laboratory under the direction of Mr. J. Vieillard. Additionally, I would like to express my gratitude to the following organizations for their financial support during my internship in France: the University of Rouen Normandy, INSA Rouen Normandy, the Centre National de la Recherche Scientifique (CNRS), European Regional Development Fund (ERDF), Labex SynOrg (ANR-11-LABX-

0029), Carnot Institut I2C, the graduate school for research XI-Chem (ANR-18-EURE-0020 XL CHEM), the PHC program Protea (48919XL) supported by and by Region Normandie and the Grand Evreux Agglomeration.

### Data availability

Data will be made available on request.

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