Sequestration of lead ion pollutants onto copper doped activated carbon nanoparticles derived from Phaseolus vulgaris L. (bean husk)

ABSTRACT

Lead is a hazardous heavy metal known for its severe health impacts, including its association with cancer. In this study, copper-doped activated carbon was synthesized using copper acetate and bean husk, activated chemically through potassium hydroxide (KOH). The data was fitted by the Langmuir isotherm model more accurately than by any other isotherm, and the adsorption capacity of Cu-AC nanoparticles was found to be 94.339 mg/g. For the removal of lead ions over Cu-AC nano-adsorbent, when comparing the values of qe calculated and qe experimental. Activated copper doped carbon has the capacity to operate as an adsorbent in the treatment of lead metal ion pollution and other associated heavy metal ion pollutants. Surface chemistry analysis identified hydroxyl, amino, aromatic, and carbonyl functional groups. Field emission scanning electron microscopy revealed interconnected mesoporous structures with numerous open pores. Adsorption experiments demonstrated that the sorption process aligned. The maximum adsorption capacity was recorded at 94.339 mg/g, with a significant desorption efficiency using HCl as the desorbing agent. Thermodynamic analysis confirmed that the lead ion removal occurred primarily through a physisorption mechanism.

Keywords:
Adsorption; Pb (II) ion; Copper doped activated carbon nanoparticles; Kinetics Thermodynamics

1. INTRODUCTION

Heavy metals are persistent environmental contaminants that exhibit a high resistance to degradation, making them a significant concern for ecosystems and human health. These toxic elements include cadmium, arsenic, lead, nickel, chromium, and mercury, which are notorious for polluting air, water, and soil [¹]. Their atomic weights vary between 63.5 to 200.6 g/mol, and they possess atomic densities greater than 5 g/cm³, which contributes to their stability and persistence in the environment [²].

The primary sources of heavy metal contamination stem from various industrial processes, including mining, surface coating, paper manufacturing, fossil fuel combustion, and plastic production [³]. These activities release heavy metals into the environment, leading to bioaccumulation in living organisms. The accumulation of heavy metals in biological systems poses severe health risks, such as liver and kidney failure, neurological disorders, and developmental issues, particularly in children [⁴].

When industrial wastewater containing heavy metals is discharged into water bodies, it disrupts aquatic ecosystems, adversely affecting fish and other aquatic organisms. Furthermore, the presence of heavy metals in soil degrades its quality, which directly impacts agricultural productivity and food safety [⁵, ⁶]. Among heavy metals, lead is especially hazardous, being associated with various health conditions, including hepatitis, nephritic syndrome, anemia, and encephalopathy [⁷].

The Environmental Protection Agency (EPA) has established a permissible lead concentration of 0.05 mg/L in both drinking water and industrial wastewater to safeguard public health [⁸, ⁹]. Industries such as battery manufacturing, ceramics, tanneries, and electroplating are significant contributors to lead contamination [¹⁰]. Additionally, lead can leach into drinking water due to corrosion of lead pipes, posing risks not only to human health but also to aquatic life and overall environmental integrity. Addressing heavy metal contamination remains a critical challenge for environmental protection and public health initiatives [¹¹].

Several methods exist for sequestering heavy metal ions from wastewater, including neutralization, precipitation, membrane separation, solvent extraction, reverse osmosis, adsorption, and ion exchange [¹²]. Among these techniques, the adsorption method stands out as one of the most significant and cost-effective solutions for heavy metal removal. Adsorption is a highly effective purification process, particularly favored for its chemical stability, versatility, remarkable efficiency, and ease of implementation [¹³].

The process involves using various adsorbent materials, such as biosorbents, clays, activated carbon, zeolites, and metal oxides, to capture and remove heavy metal ions from contaminated water [¹⁴]. Activated carbon, in particular, is widely used due to its high surface area and adsorption capacity. Copper acetate and bean husk were used, with chemical activation by potassium hydroxide (KOH). Additionally, biosorption has gained attention as an environmentally friendly method for removing heavy metals, utilizing natural materials that are often agricultural byproducts [¹⁵].

Various biosorbents, including coconut shells, peanut shells, lemon peels, sawdust, palm shells, nutshells, and dry leaves, have demonstrated efficacy in the biosorption of heavy metals [¹⁶]. These natural adsorbents not only provide an effective means for contaminant removal but also promote sustainability by utilizing waste materials, thus contributing to waste management and reducing environmental impact. The Langmuir isotherm model provided the best fit, with an adsorption capacity of 94.339 mg/g. Overall, adsorption remains a promising approach to addressing heavy metal pollution in wastewater [¹⁷].

Activated carbon is a common adsorbent used in water purification systems for the removal of metal ions as it has high porosity, huge surface area, and notable adsorption capacity and cost effective [¹⁸]. Activated carbon is present in granular and powdery form and its surface possesses various functional groups like phenol, hydroxyl and carbonyl groups. Adsorption of metal ions by activated carbon occurs through electrostatic interaction [¹⁹]. Physical activation and chemical activation are the two main techniques for achieving carbon activation. Cu-AC showed a mesoporous structure with numerous interconnected open pores. In physical activation, the precursor material undergoes an initial carbonization process, followed by an activation reaction using various gases such as steam, carbon dioxide, or air to enhance the material’s surface area and porosity [²⁰].

This method focuses on removing volatile compounds and developing the pore structure through thermal treatment. HCl proved to be an effective desorbing agent, allowing for significant desorption of lead ions from Cu-AC. This efficiency indicates that Cu-AC can be reused for multiple cycles of lead ion adsorption, making it a practical option for wastewater treatment applications. The elimination of noncarbonated elements from the source materials and the porosity of the material is acquired through activation [²¹, ²²]. Chemical activation is a single-step process which involves chemical agents that could facilitate the activation reaction resulting in the formation of activated carbon [²³, ²⁴]. Chemical activation is more advantageous since it is done at shorter time period even at low activation temperature; moreover, the porosity is effectively achieved because of the action of the activating chemicals [²⁵, ²⁶]. Hydroxyl, amino, aromatic, and carbonyl groups were identified, enhancing the adsorption of lead ions. Therefore, the yield of activated carbon obtained out of chemical activation is greater than those by physical activation. In this study, activated carbon doped with copper has been prepared and used for the removal of lead from wastewater.

2. MATERIALS AND METHODS

2.1. Pretreatment process

The bean husk was thoroughly washed in clean water to eliminate any impurities and residual contaminants. After washing, the husk was sun-dried for a period of 24 hours to ensure that excess moisture was removed. To further reduce its moisture content, the dried husk was subjected to a temperature of 105°C for 20 minutes in a hot air oven. This heating process effectively evaporated any remaining moisture, enhancing the husk’s suitability for subsequent applications. Finally, the dried bean husk was ground into a fine powder and sieved using a mesh strainer to achieve a uniform particle size, which is essential for optimal performance in adsorption processes. Figure 1 shows the detailed flow of the entire study.

Figure 1
Methodology of the study.

2.2. Preparation of copper doped activated carbon nanoparticles

The preparation of activated carbon was conducted using a chemical activation method, which offers effective results in enhancing the adsorptive properties of the material. Initially, a 10 mmol/L copper acetate solution was prepared by dissolving 1.8 grams of copper acetate in one liter of ethanol, providing a suitable medium for copper incorporation. Subsequently, 5 grams of bean husk were added to 200 mL of the copper acetate solution, allowing for a 24-hour immersion period to ensure adequate uptake of copper ions. After this period, the mixture was dried using a magnetic stirrer set at 80°C to facilitate the removal of excess solvent. Copper acetate serves as the source of copper ions, which are incorporated into the activated carbon structure to enhance its adsorption properties. Bean husk acts as the carbonaceous precursor that is carbonized and activated with potassium hydroxide (KOH), providing a suitable matrix for the formation of copper-doped activated carbon.

Following drying, the material underwent carbonization at a high temperature of 500°C for 30 minutes in a muffle furnace, which ensures precise control over the carbonization environment. This carbonized material was then combined with potassium hydroxide (KOH) at a 1:1 mass ratio, serving as an activating agent to enhance the surface area and porosity of the resulting activated carbon. The mixture was subjected to further carbonization at 500°C for 2 hours. Once the process was complete, the copper-doped activated carbon nanoparticles were thoroughly washed to remove any residual chemicals, and the moisture content was eliminated by treating the samples at 105°C for 5 hours in a hot air oven, ensuring the final product was ready for application.

2.3. Sample characterization

FTIR analysis of the synthesized copper nanoparticles was performed using the PerkinElmer Spectrum 2 instrument, with measurements taken over a wavelength range of 400 to 4000 cm⁻¹. This technique enables the identification of functional groups and chemical bonds present in the nanoparticles, providing insights into their molecular structure. To characterize the crystal structure of the nanoparticles, X-ray diffraction (XRD) analysis was conducted using a Miniflex 6G diffractometer. The XRD utilized Cu Kα radiation (λ = 0.15406 nm) and was carried out at a voltage of 40 kV and a current of 15 mA. The scanning rate was set to 5°/min, and the two-theta values were recorded between 10° and 90°, allowing for a comprehensive assessment of the crystallinity and phase composition of the synthesized nanoparticles.

The morphology of the copper oxide (CuO) nanoparticles was investigated using FESEM. This technique provided high-resolution images that revealed the size, shape, and surface characteristics of the nanoparticles. Additionally, EDX was employed to confirm the presence of metal ions and analyze the elemental composition of the synthesized nanoparticles, ensuring the successful incorporation of copper and providing valuable data on the purity of the product. Together, these characterization techniques offered a thorough understanding of the structural and compositional properties of the synthesized copper nanoparticles.

2.4. Preparation of stock solution

To prepare a stock solution of lead ions, 1.593 g of lead(II) nitrate [Pb(NO₃)₂] was accurately weighed and dissolved in 100 mL of deionized water in a standard 250 mL volumetric flask. This resulted in a concentrated stock solution that allows for precise preparation of working standards. The flask was carefully swirled to ensure complete dissolution of the lead salt, forming a clear solution that served as a reliable source of lead ions for subsequent experiments. The hydroxyl, amino, aromatic, and carbonyl functional groups on the surface of Cu-AC provide reactive sites that can form interactions with lead ions, enhancing the adsorption process. These groups can facilitate binding through electrostatic attraction, complexation, or hydrogen bonding, which improves the material’s overall efficacy as an adsorbent.

From this stock solution, working standards with concentrations ranging from 1 to 10 ppm were prepared to facilitate various experimental investigations. This involved diluting the stock solution in specific volumes to achieve the desired concentrations, ensuring that the lead ion levels could be accurately measured and controlled during the experimental processes. The prepared working standards are essential for evaluating the adsorption capacity and efficiency of the synthesized adsorbents in removing lead ions from aqueous solutions.

2.5. Optimization of contact time

A batch solution containing lead ions was meticulously prepared by dissolving the necessary amount of lead salt in 100 mL of deionized water. To initiate the adsorption process, 0.2 g of activated carbon was added to the prepared lead ion solution. To monitor the progress of adsorption over time, samples were collected at 20-minute intervals for a total duration of 120 minutes. This systematic sampling allowed for a detailed observation of the adsorption kinetics and the efficiency of the activated carbon in removing lead ions from the solution.

Following each sampling, the mixture was filtered using Whatman filter paper to separate the solid activated carbon from the liquid phase. The resulting filtrate was then subjected to analysis using Atomic Absorption Spectrophotometry (AAS). This technique was employed to accurately determine the concentration of lead ions remaining in the solution after the adsorption process. By comparing the initial and final concentrations, the adsorption capacity of the activated carbon could be evaluated, providing insight into its effectiveness as an adsorbent for lead ion removal.

2.6. Optimization of pH

The influence of pH on the ability of the adsorbent to remove lead ions was investigated across a range of pH values from 2 to 10. In each experimental trial, 100 mL of lead solution with a consistent initial concentration of 10 mg/L was prepared. To assess the effectiveness of the adsorbent, 0.2 g was added to the solution, ensuring thorough mixing to promote interaction between the adsorbent and lead ions.

After allowing the mixture to react for a specified period, samples were extracted from the batch solution at regular intervals. These samples were then filtered to separate the solid adsorbent from the liquid phase, utilizing Whatman filter paper for effective filtration.

The filtrate underwent analysis using Atomic Absorption Spectrophotometry (AAS) to accurately determine the concentration of lead ions remaining in the solution. By evaluating the data obtained from different pH levels, insights into how pH influences the adsorption capacity of the adsorbent could be established, aiding in optimizing conditions for effective lead removal from wastewater.

2.7. Optimization of adsorbent dosage

In this experiment, different quantities of adsorbents—specifically 0.05, 0.1, 0.15, 0.2, and 0.25 g—were added to 100 mL of lead solution with a fixed concentration of 10 mg/L. Each mixture was thoroughly shaken for 40 minutes to ensure adequate contact between the adsorbent and the lead ions, promoting effective adsorption. After the designated shaking period, the samples were filtered to separate the solid adsorbent from the liquid phase, utilizing appropriate filtration techniques to obtain a clear solution. The filtered samples were then analyzed using an Atomic Absorption Spectrophotometer (AAS) to quantify the concentration of lead ions remaining in the solution, thereby assessing the efficiency of each adsorbent dosage in removing lead from the aqueous environment. This investigation aimed to determine the optimal amount of adsorbent required for effective lead ion removal.

2.8. Optimization of initial concentration

In this experiment, 0.25 g of activated carbon was introduced into 100 mL of a lead ion solution, with concentrations varying from 1 to 10 ppm. To facilitate effective adsorption, the mixture was agitated continuously for a duration of 40 minutes using an orbital shaker. This ensured uniform dispersion of the adsorbent and maximized the interaction between the activated carbon and the lead ions in the solution. After the adsorption period, the mixture was filtered to separate the solid activated carbon from the liquid phase, yielding a clear filtrate. This filtrate was then analyzed using Atomic Absorption Spectrophotometry (AAS) to measure the remaining concentration of lead ions. The results of this analysis provided insights into the efficiency of the activated carbon in adsorbing lead ions at different initial concentrations, contributing to a better understanding of the material’s adsorption capabilities. HCl showed significant desorption efficiency, suggesting that Cu-AC can potentially be reused for multiple adsorption cycles.

2.9. Optimization of temperature

In this investigation, the optimal adsorption performance was achieved by dispersing 0.25 g of activated carbon in 100 mL of lead solution with a concentration of 10 mg/L. To evaluate the influence of temperature on lead removal efficiency, batch adsorption experiments were conducted at four distinct temperatures: 30°C, 40°C, 50°C, and 60°C. At each temperature setting, samples were periodically taken from the mixture and subsequently filtered to separate the activated carbon from the lead solution. The filtered samples, now devoid of solid particles, were analyzed using Atomic Absorption Spectrophotometry (AAS) to determine the residual concentration of lead ions in the solution. This approach allowed for a comprehensive assessment of how varying temperatures affected the adsorption capacity of the activated carbon, providing valuable insights into the optimal conditions for lead ion removal from aqueous media. The data obtained from this analysis could inform future applications and improve strategies for treating lead-contaminated water.

(1)$${\text{q}}_{\text{e}}=\frac{(C_i-C_e)V}{m}$$

2.10. Adsorption isotherm studies

Isotherm studies provide a fundamental understanding of how the amount of adsorbate interacts with the adsorbent as a function of concentration, under constant temperature conditions. These studies are applicable to both gaseous and liquid states, making them vital for a wide range of applications, including wastewater treatment and air purification. In this research, two prominent adsorption isotherm models—the Langmuir and Freundlich models—were evaluated using the experimental data obtained from the adsorption processes. The analysis confirmed that lead ion removal occurs primarily through physisorption, indicating a physical rather than chemical bond.

The Langmuir model assumes that adsorption occurs on a homogenous surface with a finite number of identical sites, leading to monolayer coverage of the adsorbate. This model is particularly useful for understanding scenarios where adsorbate-adsorbent interactions are strong and specific. Conversely, the Freundlich model addresses heterogeneous surfaces and allows for multi-layer adsorption, making it suitable for more complex systems. The Langmuir isotherm model is typically more accurate for systems where adsorption occurs at specific sites within a homogenous surface, indicating that each adsorption site can hold only one lead ion. Its better fit suggests that the adsorption process is monolayer and that there are limited available sites for lead ion binding on the Cu-AC surface.

2.10.1. Langmuir isotherm

The Langmuir isotherm model is based on the premise that adsorption takes place as a monolayer on a surface with a limited number of specific sites on the adsorbent. The mathematical representation of the Langmuir isotherm is as follows:

(2)$$\frac{C_e}{\frac{X}{M}}=\frac{C_e}{q_{max}}+\frac{1}{b{q}_{max}}$$

2.10.2. Freundlich isotherm

The Freundlich adsorption isotherm usually describes a heterogenous system given by an empirical equation represented as

(3)$$\ln {\text{q}}_{\text{e}}=\frac{1}{n}\text{}1\text{nC}\text{+}\text{lnK}$$

n is the Freundlich coefficient which describes the heterogeneity property explaining the deviation from the linearity of sorption mechanism. The plot showing log q_e versus log C_e, the Freundlich coefficients can be elucidated by linear regression models.

(4)$$\log {\text{q}}_{\text{e}}=\log \text{K}+\frac{1}{n}\text{}\log \text{Ce}$$

2.10.3. Temkin isotherm

The Temkin isotherm model describes the effective interactions that typically occur between the adsorbent and the sorbate molecules. It is based on two main assumptions: (a) within a monolayer, the heat of adsorption decreases progressively as more molecules accommodate on the surface of the adsorbent, and (b) the adsorption process.

(5)$${\text{q}}_{\text{e}}=\frac{RT}{b_T}\ln ({\text{K}}_{\text{T}}{\text{C}}_{\text{e}})$$

From the slope and intercept of the plot of q_e against lnC_e, the isotherm constants such as B_T, and K_T can be calculated.

(6)$$B_{\text{T}}=\frac{RT}{b_T}$$

Where, B_T and b_T are Temkin constants and K_T is Temkin adsorption potential (L/g).

2.11. Adsorption kinetics study

Adsorption kinetics is an important phenomenon that focuses on the rate of the sorption reaction in relation to residence time. In this study, the experimental data were analyzed using both pseudo-first-order and pseudo-second-order kinetic models to examine how lead ions are adsorbed onto copper-doped activated carbon.

(7)$$\log ({\text{q}}_{\text{e}}-{\text{q}}_{\text{t}})=\text{}\log {\text{q}}_{\text{e}}-({\text{k}}_{\text{1}}/2.303)\text{t}$$

(8)$$\frac{t}{q_t}=\frac{1}{k_2{q}_e^2}+\frac{1}{q_e}\text{t}$$

2.12. Thermodynamics of sorption

Thermodynamic studies help determine whether the sorption mechanism is endothermic or exothermic and provide insights into the degree of freedom of the metal ions involved. Key thermodynamic parameters, including the changes in Gibbs free energy (∆H°), enthalpy (∆G°), and entropy (∆s°), associated with the sorption process can be calculated using the following equations:

(9)$$\Delta \text{G}\text{}=-\text{RTlnK}$$

(10)$$\ln \text{k}\text{=}\frac{\Delta S}{R}-\frac{\Delta H}{RT}$$

(11)$$\Delta \text{G}\text{=}\Delta \text{H}-\text{TΔS}$$

3. RESULTS AND DISCUSSION

3.1. FTIR characterization

The surface functional groups of Cu-AC prior to and after adsorption were determined by FTIR, as shown in Figure 2 and Figure 3. The copper nanoparticles produced have distinct peaks in the FTIR spectra at 3328.92 cm^–1, 2430.95 cm^–1, 1357.23 cm^–1, 880.49 cm^–1, and 706.80 cm^–1. An adsorption capacity of 94.339 mg/g indicates that Cu-AC is highly effective at removing lead ions from solution, suggesting that it can effectively reduce lead contamination in wastewater at significant concentrations. The vibrational intrinsic stretching of copper oxide bond vibrations (here CuO) resulted in the development of well-defined peaks at 706.80 cm^–1, indicating that the produced nanoparticles were copper. The peaks observed at 1459.40 cm^–1 is due to the asymmetric bend of –CH₂ and aromatic C-C stretching. Group C-C indicates the increasing content of carbon. Peak seen at 880.49 cm^–1 correlates to the stretching vibration of C-H bend. There were still traces of broadband adsorption peaks at 3328.92 cm^–1, 2430 cm^–1 and 1459.40 cm^–1 due to the traces of adsorbed or atmospheric OH, C≡C and NO₂ stretching vibration, thereby indicating the surface activation of carbon present in activated charcoal. The mesoporous structure provides a large surface area and facilitates greater accessibility for lead ions to adsorb onto the carbon surface. This structural feature enhances the adsorption capacity and kinetics, allowing for efficient uptake of lead ions from the aqueous phase.

Figure 2
FTIR spectra of Cu-AC before adsorption.

Figure 3
FTIR spectra of Cu-AC after adsorption.

3.2. FESEM and EDX characterization

FESEM images of the activated carbon at various magnifications, depicted in Figures 4 and 5, provide crucial insights into the structural characteristics of the synthesized materials. The FESEM analysis reveals that the copper nanoparticles, along with some oxide nanoparticles, predominantly exhibit a spherical shape, which is often associated with enhanced catalytic and adsorption properties. The process of chemical activation of the precursors at a temperature of 500°C significantly contributed to the reduction of volatile matter, promoting the formation of micro and mesopores on the surface of the adsorbent. These porous structures are essential for improving the adsorption capacity of the activated carbon by providing more surface area for interaction with adsorbate molecules. Physisorption indicates that the adsorption of lead ions onto Cu-AC occurs through weak physical interactions, such as van der Waals forces or electrostatic attraction, rather than strong chemical bonds. This suggests that the adsorption process is reversible, allowing for easier desorption and potential reuse of the adsorbent.

Figure 4
SEM image of the AC at X200.

Figure 5
SEM image of the AC at X200.

The size of the synthesized copper nanoparticles was determined to range from 50 to 100 nm, a size range that is favorable for various applications, including environmental remediation and catalysis. EDX analysis was performed to ascertain the elemental composition of the synthesized nanoparticles. The results, summarized in Table 1, indicated that copper comprised 34.13% of the total mass of the sample. The elemental composition from the EDX, illustrated in Figure 6, shows that while copper constituted a significant portion, oxygen accounted for approximately 46%, with trace amounts of other elements present. This comprehensive characterization underscores the effectiveness of the synthesis process and highlights the potential of the developed material for various applications, particularly in adsorptive removal of heavy metals from aqueous solutions.

Table 1
Elemental analysis.

ELEMENT	WEIGHT %	ATOMIC %
O K	46.20	71.69
Mg K	5.00	5.11
Si K	2.44	2.16
K K	8.45	5.37
Ca K	3.78	2.34
Cu K	34.13	13.34
Total	100.00	100.00

Figure 6
Elemental composition shown by the EDX.

3.3. X-Ray diffraction analysis

The XRD crystallography was used to assess arrangement of molecules and crystalline property of the synthesized copper doped activated carbon nanoparticles. The incident X-rays had a monochromatic wavelength of 0.154 nm. Several well-defined diffraction patterns are seen from the observed XRD spectrum with calculated (h,k,l) indices of (110), (113) and (202) which are well matched with the monoclinic-CuO structures with the lattice constants of a = 4.2960 and c = 16.100Å. Figures 7 and 8 XRD spectra of Cu-AC before adsorption and XRD spectra of Cu-AC after adsorption.

Figure 7
XRD spectra of Cu-AC before adsorption.

Figure 8
XRD spectra of Cu-AC after adsorption.

(12)$$\text{Scherrer equation: D}=\frac{K\lambda }{\beta cos\theta }$$

In this context, D represents the average crystalline size, while K (0.94) is the Debye-Scherrer constant. The wavelength λ corresponds to the Cu Kα radiation (0.154 nm), and refers to the FWHM of the diffraction peak, with θ\thetaθ being the Bragg’s angle. The particle size, calculated using the Scherrer equation, falls within the range of 40–60 nm.

3.4. Batch adsorption experiments

3.4.1. Effect of contact time

The plots showing lead ions adsorbed onto the prepared material (0.2 g) in 100 mL solutions analyzed at different time intervals 20 to 120 minutes is shown in Figure 9. The plot showcased a rapid rate of adsorption of lead ions onto copper doped activated carbon within 40 minutes, while the maximum adsorption could be 4.2986 mg/g at 40 minutes of contact time. The maximum lead ions sequestration efficiency was found to be 85.97% at 40 minutes.

Figure 09
Effect of contact time on lead ions adsorption onto AC.

3.4.2. Effect of pH

Both aqueous chemistry and external binding characteristics of the sorbent are influenced by pH of the batch solution. The optimum pH was obtained by varying the pH from 2–10 pH. The experiment was conducted at an optimized contact time of 40 minutes with a dose of 0.2 g and the speed of the agitation at 121 rpm. It is seen in Figure 10, the removal efficiency was declined at the acidic conditions. When pH is increased from 2–10 resulted in an increased removal of lead ions. The percentage removal was 87.92% at pH 6. Beyond pH 7, hydroxyl precipitation takes place so it cannot be concluded whether the removal of ions is due to adsorption or precipitation.

Figure 10
Effect of pH.

3.4.3. Effect of adsorbent dosage

For any assigned concentration of initial metal ions, the capacity of the adsorbent should be determined which in turn relates to the adsorbent dosage that should be used in the batch experiments. The adsorbent dose is a notable parameter which determines the adsorbent capacity for the initial concentration of lead solution loaded. The effect of the adsorbent dose was examined in the range of 0.05 g–0.25 g with a pH-6 at contact time of 40 minutes. As adsorbent dosage increases the removal efficiency initially heightened and it subsequently reaches maximum. As adsorbent dosage increases lead uptake decrease as shown in Figure 11. It was noted that there were subtle variations throughout the range 0.05 g– 0.25 g. The maximum removal efficiency was found to be 99.87% at 0.25 g.

Figure 11
Effect of Adsorbent dosage.

3.4.4. Effect of initial concentration

The optimal initial concentration of metal ions was established by varying the concentration between 2 to 10 ppm in batch experiments. The experiments were carried out with a contact time of 40 minutes using a dosage of 0.25 g in 100 mL solutions, as depicted in Figure 12. The percentage of removal was notably higher at the maximum concentration of lead ions examined.

Figure 12
Effect of initial concentration.

3.4.5 Effect of temperature

The optimal temperature was determined by varying the temperature from 303 K to 333 K, while maintaining an optimized contact time of 40 minutes and a dosage of 0.25 g. For activated carbon, the adsorption capacity tends to increase with rising temperatures due to reduced viscosity and enhanced molecular motion. However, an exothermic reaction was observed, indicating that the adsorption capacity decreases with increasing temperature. Typically, physisorption is characterized by changes in free energy ranging from –20 to 0 kJ/mol, whereas chemisorption falls within the range of –80 to –400 kJ/mol. The impact of temperature on the adsorption of lead ions is illustrated in Figure 13.

Figure 13
Effect of temperature.

3.5. Adsorption isotherm

The relationship between the concentration of the sorbate in the bulk solution and the quantity of lead ions adsorbed at the interface at equilibrium can be characterized by adsorption isotherms.

3.5.1. Langmuir model

The results of the Langmuir isotherm model are presented in Figure 14. The equilibrium parameter RL was calculated to be 0.08382, which falls within the range of 0 to 1. Additionally, the maximum adsorption capacity (qmax) was determined to be 94.339 mg/g, indicating that the adsorption process is consistent with the Langmuir isotherm model, characteristic of monolayer adsorption.

Figure 14
Langmuir adsorption isotherm model.

3.5.2. Freundlich model

The findings from the Freundlich isotherm model are illustrated in Figure 15. The value of n falls between 0 and 1, leading to an n value of 1.052. Since n is greater than one, this indicates that the adsorption process is favorable, suggesting a physical adsorption or biosorption mechanism.

Figure 15
Freundlich adsorption isotherm model.

3.5.3. Temkin model

As b_T value is related to the heat of adsorption. The calculated b_T value was 0.00014 which points out that the adsorption process is exothermic. The b_T value equal to 8.960 × 10^–5 kcal/mol is the heat of sorption. The heat of sorption less than 1.0 kcal/mol indicates that adsorption is of physical route. The result of the Temkin isotherm model was shown in Figure 16.

Figure 16
Temkin adsorption isotherm model.

3.6. Results of adsorption kinetics study

From Table 2 it can deduced that the adsorption kinetic model.

Table 2
Adsorption kinetics model.

KINETIC MODELS	PARAMETERS	VALUES
Pseudo first order	K1	–0.01224
	qe-calculated	0.0923
	R2	0.138
Pseudo second order	K2	–2.7186
	qe-calculated	4.1684
	R2	0.99967
Experimental data	qe-experimental	4.2987

3.6.1. Pseudo-first order kinetics

The experimental qe values derived from linear plots were not consistent with the computed q_e values. This disparity implies that the lead ion adsorption kinetics onto copper-doped activated carbon, as seen in Figure 17, do not follow the pseudo-first-order kinetic model and are not controlled by a diffusion-mediated mechanism.

Figure 17
Pseudo-first order kinetics.

3.6.2. Pseudo-second order kinetics

The experimental and estimated qe values were in good agreement which is clearly noted from the linear plot. Figure 18 reveals good correlation coefficient (R²) for the pseudo-second order kinetic model which well described the lead ions adsorption on copper doped activated carbon adsorbent.

Figure 18
Pseudo-second order kinetics.

3.7. Results of Thermodynamic study

The optimum temperature was obtained by modulating the temperature from 303 K to 333 K with an optimized contact time 40 minutes at sorbent dose of 0.25 g. For physisorption reaction, the change in free energy lies between –20 and 0 kJmol^–1 and for chemisorptions it generally ranges from –80 to –400 kJ mol^–1. The result was shown in Table 3. The negative enthalpy change (–1.096 kJ mol^–1) designated that the adsorption is of physisorption in nature which engages weak forces of bonding and the reaction must be exothermic, and hence stable energetic process would be demonstrated. A negative entropy value revealed decreased randomness.

Table 3
Thermodynamic study.

TEMPERATURE (K)	Kd (L/g)	∆G°	∆H°	∆S°
303	0.3984	–2318.10	–1096.72	–11.284
313	0.3901	–2449.46
323	0.3890	–2534.88
333	0.3818	–2665.66

3.7. Desorption study

Desorption studies was used to identify the reusability and reproducibility of the adsorbent. The lead solution containing 0.25 g of activated carbon was shaken in an orbital shaker at 130 rpm for 40 minutes at a room temperature (30°C), then filtered and the filtrate was dried in a hot air oven at 105°C. The desorbing agent HCl solution (0.1 M) was added to the dried sample and desorption was carried out in a same way of adsorption process. The removal percentage of lead ions in an adsorption process was 95.32% and the desorption efficiency was 92.50%. The desorption efficiency (DE) (%) was calculated by:

(13)$$\text{DE}\text{}=\frac{Quantityofmetaliondesorbed}{Quantityofmetalionadsorbed}\times 100$$

4. CONCLUSION

Copper-doped activated carbon nanoparticles were synthesized by the chemical method of nanoparticle synthesis using bean husk and the chemical precursor used was copper acetate. The produced copper-doped activated carbon was examined using a number of methods, including FTIR, EDX, FESEM, and XRD. The calculated size of the synthesized Cu-AC was in the nanoscale, according to data retrieved from XRD and FESEM instruments. The bands at 706.80 cm^–1 in the Cu-FTIR spectra are associated with the CuO vibration modes within the Cu-AC lattice. Oxygen, copper, and carbon are present according to the FESEM-EDX spectra. Activated carbon nanoparticles doped with copper and utilized as an adsorbent to remove lead metal ions (Pb2⁺) from aqueous media under optimal circumstances (pH 6, 40 minutes, and 0.25 g of produced Cu-AC nanoparticle adsorbent) as determined by batch studies. The Langmuir isotherm model fits data better than any other isotherm, and it was discovered that Cu-AC nanoparticles had an adsorption capacity of 94.339 mg/g. When comparing the values of q_e computed and q_e experimental, model for the removal of lead ions over Cu-AC nano-adsorbent. When it comes to dealing with lead metal ion pollution and other related heavy metal ion pollutants, activated copper doped carbon has the ability to function as an adsorbent.

6. ACKNOWLEDGMENTS

The authors declare that no funds, grants, or other support were received for the preparation and submitting of this manuscript.

7. BIBLIOGRAFIA

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Publication Dates

• Publication in this collection
  17 Feb 2025
• Date of issue
  2025

History

• Received
  14 Oct 2024
• Accepted
  02 Dec 2024