Next Article in Journal
A Slope Dynamic Stability Evaluation Method Based on Variable Weight Theory and Trapezoidal Cloud Model
Next Article in Special Issue
Performance of a Zeolite-Filled Slow Filter for Dye Removal and Turbidity Reduction
Previous Article in Journal
Research on the Influence of Groundwater Level Dynamic Rising Process on Buildings Based on Numerical Simulation
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Water
Volume 17
Issue 20
10.3390/w17203015
water-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effective Treatment of Wastewater Containing Ni (II) and Pb (II) Using Modified Kaolin: Experimental and Simulation Study

by
Zhengtian Yin
1,
Yuxuan Yang
2,*,
Guanjie Wang
2 and
Renzhi Qi
3
1
Faculty of Architecture, The University of Hong Kong, Hong Kong 999077, China
2
Taizhou Institute of Zhejiang University, Zhejiang University, Taizhou 318000, China
3
Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China
*
Author to whom correspondence should be addressed.
Water 2025, 17(20), 3015; https://doi.org/10.3390/w17203015
Submission received: 26 September 2025 / Revised: 16 October 2025 / Accepted: 17 October 2025 / Published: 20 October 2025
(This article belongs to the Special Issue Research on Adsorption Technologies in Water Treatment)
Browse Figures
Versions Notes

Abstract

With the expansion of industrial production capacity, a substantial volume of hazardous wastewater containing Pb (II) and Ni (II) requires treatment. Kaolin, a low-cost adsorbent with strong adsorption properties, was modified through thermal activation at 750 °C, 850 °C, and 950 °C to enhance its adsorption capacity. Following the optimization of pH, reaction time, temperature, heavy metal concentrations, and adsorbent amount, the 850-K was found to have the best removal efficiency, achieving removal rates > 90% for both PbCl2 and NiCl2, and the removal efficiency of PbCl2 was higher compared to NiCl2. The pseudo-second-order kinetics and Langmuir model could reasonably match the adsorption processes of PbCl2/NiCl2. The experimental findings were corroborated through simulations of adsorption distance, variations in bond length/bond angle, adsorption energy, frontier molecular orbital, charge density, and differential charge density. The differences in reactions between adsorbents and PbCl2/NiCl2 were primarily due to the electron transfer direction and bonding mechanisms. The O atoms were the main reactive atoms of the adsorbents, capable of forming covalent bonds with both PbCl2 and NiCl2, and the Cl atoms could form either ionic or covalent bonds with the adsorbent. Pb could form covalent bonds with the adsorbent, while Ni might be adsorbed through electrostatic interactions.

1. Introduction

With the rapid advancement of artificial intelligence and robotics worldwide, modern industrial capacity continues to expand. This has led to a persistent increase in heavy metal wastewater discharges from fields such as electroplating [1], metallurgy [2], battery manufacturing [3], and electronic component processing [4]. Heavy metals are harmful, making wastewater one of the key pollution sources threatening both the ecological environment and human health [5,6,7].
Heavy metals in water have long been a significant concern [8,9,10,11]. Pb (II) and Ni (II) are two typical highly toxic heavy metal ions widely present in various wastewaters [12]. Pb (II) is commonly found in wastewaters from battery production and non-ferrous metal smelting [13], while Ni (II), a core raw material in electroplating processes, is often discharged in large amounts via electroplating rinse water [14]. If the wastewater containing heavy metals is not promptly controlled, it will not only damage the nervous and reproductive systems of aquatic organisms, endangering the food chain, but also enter the human body through drinking water or soil permeation, leading to serious health issues [15,16,17]. Currently, Pb (II) and Ni (II) are widely detected both in industrial water [18,19] and even in natural water [20,21]. Therefore, controlling Pb (II) and Ni (II) in water is of paramount importance. The amount of Pb (II) and Ni (II) discharged in wastewater is substantial and demands greater attention. Furthermore, with increasingly stringent environmental standards, developing efficient, economical, and environmentally friendly treatment methods for Pb (II) and Ni (II)-containing wastewater has become a core requirement in the field of wastewater management.
Currently, technologies for treating heavy metal-containing wastewater mainly comprise chemical precipitation [22], ion exchange [23], membrane separation [24], and adsorption methods [25]. Chemical precipitation requires substantial chemical dosing and is prone to secondary pollution. Although ion exchange and membrane separation offer high removal efficiency, their maintenance costs are prohibitively high. The adsorption method, which is widely applied in heavy metal pollution treatment due to its simplicity, low cost, and stable performance, is considered to hold significant potential for treating heavy metal-contaminated wastewater [26,27]. Nevertheless, some adsorbent materials involve complex preparation processes or high costs. Although they achieve satisfactory adsorption results, they are not conducive to large-scale application. For example, Liu. et al. [28] prepared the humic acid (HA)-coated Fe3O4 nanoparticles (Fe3O4/HA) to remove the Cu (II), Hg (II), and Cd (II) in water, with the removal rate of these heavy metals reaching 95%, but its preparation process was complex with low potential for industrial application. The porous silica–graphene oxide nanocomposite (GO-SiO2) was prepared by Barik et al. [29], and its maximum adsorption capacities for Pb (II) and As (III) in water were 527 mg/g and 30 mg/g, respectively, and its performance was almost unaffected after being recycled for four times. However, the preparation cost of GO-SiO2 was high, and it did not have good application value. Therefore, it is of great significance to find a low-cost adsorbent that can efficiently treat heavy metal-containing wastewater and to explore simple and feasible modification methods to enhance its adsorption performance.
Kaolin, as an abundant and inexpensive natural clay mineral, demonstrates significant potential in the field of heavy metal treatment in water due to its unique layered structure and excellent adsorption properties [30,31,32]. However, current research on utilizing kaolin for treating Pb (II) and Ni (II) in water is not comprehensive enough, lacks in-depth elucidation of key mechanisms, and still has space for improvement. With the continuous advancement of computer science, various simulation techniques enable us to delve into the microscopic level and elucidate the interactions between substances. Among these, the application of density functional theory (DFT) [33] and molecular dynamics (MD) [33] can reveal numerous microscopic reaction mechanisms and grasp the laws of reactions. However, current studies on the adsorption of Pb (II) and Ni (II) in water by kaolin predominantly rely on experimental approaches [34,35,36], with relatively scarce and insufficiently detailed simulations, which lack extra explanations for key mechanisms. Therefore, simulating the adsorption behavior of Pb (II) and Ni (II) by kaolin and modified kaolin in water to reveal key reaction characteristics holds significant importance.
This study utilized kaolin as an adsorbent, and modified it through simple thermal activation to effectively enhance its adsorption performance, making it suitable for large-scale application. The effects of pH, temperature, heavy metal concentration, reaction time, and adsorbent amount on the adsorption of Pb (II) and Ni (II) were investigated, with continuous optimization of reaction conditions to understand the kinetic and thermodynamic adsorption characteristics. The reaction models for kaolin and modified kaolin with Pb (II)/Ni (II) in water were established. Moreover, DFT/MD simulations were applied to explore their reaction mechanisms in water, corroborating the experimental findings. This study can be of great significance for effectively controlling Pb (II)/Ni (II) pollution in water and for understanding the reaction mechanisms of Pb (II)/Ni (II) with kaolin in aqueous solutions.

2. Materials and Methods

2.1. Materials and Chemicals

The primary kaolin (PK) was procured from Shanlin Shiyu Mineral Products Co., Ltd., Xiangxi, China; PbCl2 and NiCl2 were both analytical, purchased from Nanjing Chemical Reagent Co., Ltd., Nangjing, China. The aqueous ammonia (25%) and hydrochloric acid (HCl, 36.5%) were purchased from Sinopharm Chemical Reagent Co., Ltd., Nanjing, China. The deionized water was prepared locally in the laboratory.

2.2. Method of Modification of PK

This study took a simple and straightforward way to modify PK, aiming to enhance its ability to remove PbCl2 and NiCl2 from water. Owing to the simplicity of the modification scheme and the absence of any additional superfluous substances, this method holds potential for large-scale application. The PK was sieved through a 200 μm mesh and calcined in a muffle furnace (MF-1200C, Beiyike, Hefei, China) for 1 h to achieve thermal activation. Subsequently, the samples were removed, washed three times with deionized water, and dried in an oven (at 105 °C). The resulting samples, thermally activated at 750 °C, 850 °C, and 950 °C were named 750-K, 850-K, and 950-K, respectively.

2.3. Method of Batch Experiments

Accurately weigh 100 mg of PbCl2 and NiCl2 each, placing them separately into 500 mL beakers. Subsequently, dissolve them in deionized water until all powder is completely dissolved. Before transferring them to a 1000 mL volumetric flask, dilute to volume and shake thoroughly. Thus, two waste solutions containing PbCl2 and NiCl2 at 100 mg/L are successfully prepared. During the experiment, the concentrations of the wastewater are diluted as required. The experiments were performed by placing centrifuge tubes in a reciprocating shaker (Cab B300, Hetian, Shanghai, China), which could control the reaction temperature, and stirring at 300 rpm. The pH was measured using an ion analyzer (PXSJ-216, Leici, Shanghai, China) and adjusted with aqueous ammonia and hydrochloric acid.
Transfer specific volumes of the PbCl2/NiCl2 solution into separate centrifuge tubes to investigate the influence of variables. This study sequentially investigated factors including pH values (4 to 9), adsorption time (0.5 to 10 h), dosage (0.025 to 0.200 g), heavy metal concentrations (10 to 60 mg/L), and reaction temperatures (5 to 30 °C), and continuously optimized the adsorption experimental conditions. Setting the pH between 4 and 9 essentially covers all suitable ranges. The adsorption time (0.5 to 10 h) and dosage (0.025–0.200 g) were set based on experience and will be adjusted according to experimental results. The heavy metal concentrations (10 to 60 mg/L) and experimental temperatures (5 to 30 °C) selected are more representative of the concentrations and temperatures at which heavy metals are typically found in realistic wastewater conditions. Following each experiment, the metal ion concentrations in solution was diluted and tested using atomic absorption spectroscopy, with three parallel samples per experimental group.
The initial experiment investigated the effect of pH on adsorption, with the following experimental parameters: reaction temperature of 25 °C, heavy metal concentration of 50 mg/L, addition amount of 0.1 g, and reaction time of 8 h. After determining the best pH parameters for PbCl2 and NiCl2 adsorption, the next experiment was performed by altering the other parameters until the final optimization of all experimental parameters was achieved.
This study employed the pseudo-first-order (shown in Equation (1)) [37] and pseudo-second-order (shown in Equation (2)) [38] kinetic models to fit experimental data, investigating the kinetic processes of adsorption. Furthermore, the Langmuir (shown in Equation (3)) [39] and Freundlich (shown in Equation (4)) [40] models were utilized to fit the thermodynamic processes of adsorption.
ln q e − q t = ln q e − K 1 × t
t q t = 1 K 2 × q e 2 + t q e
where q t (mg·g−1) is amount for adsorption at a certain time; t (min) means the reaction time; K 1 (min−1) and K 2 (g·mg−1·min−1) are the observed rate constant of pseudo-first order and pseudo-second order, respectively; q e (mg·g−1) is the amount of adsorption at equilibrium.
1 q e = 1 q m × K A ∗ C e + 1 q m
l o g q e = l o g K f + n × l o g C e
where C e (mg·L−1) denotes the concentration of heavy metal ions in solution at adsorption equilibrium; q m (mg·g−1) denotes the saturated adsorption capacity; q e denotes the equilibrium adsorption capacity (mg·g−1); K A (L·mg−1) denotes the Langmuir constant; K f denotes the adsorption capacity constant; n denotes the constant representing the magnitude of adsorption tendency.

2.4. Method of Simulations

The models for PK [41,42] and thermally activated PK [43] (850-K) were constructed by referencing existing studies, and the models for H2O, PbCl2, and NiCl2 were established. The MD-based method incorporates H2O into the PK/modified kaolin models. Using the Amorphous Cell Tools program to fill PK/modified kaolin with H2O, and the main parameters were designed as follows: the proportion of the filling agent of H2O was set to 100%, the task was set as Packing, the calculation accuracy was Ultra-fine, the force field was Universal, and when the density of H2O was set to 1.2 g/cm3, all H2O could be uniformly filled into the PK/modified kaolin models. Subsequently, the optimized PbCl2 and NiCl2 were appropriately positioned within the model after H2O filling, and geometric structure optimization was performed.
Geometric structure optimization of these models was performed using the CASTEP program [44], and the adsorption energy ( Δ E ), charge density (CD), and differential charge density (DCD) were calculated. Key parameters were set as follows: the calculation accuracy was Fine, the functional was GGA-PBE [45], the Ultrasoft Pseudo-Potential was employed [46], the energy cutoff was 700 eV, and the self-consistent field was 300. The method for calculating the Δ E is shown in Equation (5) [47]:
Δ E = E p r o d u c t   −   ( E a d s o r b e n t +   E a d s o r b a t e )
where E a d s o r b e n t and E a d s o r b a t e represent the self-energy of the adsorption materials (after H2O has been filled) and heavy metals, respectively. E p r o d u c t denotes the total energy of the adsorption product after stable adsorption is achieved. When the values of Δ E is positive, no adsorption occurs between the two components, whereas a negative Δ E indicates adsorption within the system. The more negative the adsorption energy value, the stronger the adsorption effect and the more stable the structure of the adsorption product.
Calculations of the frontier molecular orbital (FMO) can reveal the reactivity between substances, providing crucial evidence for assessing the strength of reactions between them [48,49,50]. FMO consists of LUMO (lower unoccupied molecular orbital) and HOMO (highest occupied molecular orbital) [51]. The smaller the energy gap ( Δ E G ) of the two substances, the greater the likelihood of a reaction occurring between the two substances. The value of Δ E G is the smaller one of Δ E 1 and Δ E 2 , and the methods to calculate Δ E 1 and Δ E 2 are shown in Equations (6) and (7):
Δ E 1 = | Δ E i − Δ E j |
Δ E 2 = | Δ E m − Δ E n |
where Δ E i represents the HOMO of the adsorbates, and Δ E j represents the LUMO of the adsorbents; Δ E m represents the LUMO of the adsorbates, and Δ E n represents the LUMO of the adsorbents. The schematic diagram of the FMO is shown in Figure 1 [52].
The FMO calculations were performed using the Dmol3 program [53] and the accuracy was Fine.

2.5. Characterization

The X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FT-IR) were used to analyze the structure, composition, morphology and functional groups of the materials, respectively. The Brunauer–Emmett–Teller (BET) and Barrett–Joyner–Halenda (BJH) methods were used to test the texture characteristics. The test methods and parameters were referenced from an article we have published [54].

3. Results of Material Characterization

3.1. XRD and FT-IR Results

Figure 2a shows the XRD results for the four adsorbents, and all four raw materials had distinct characteristic peaks for kaolin, quartz, and Al2O3. After thermal activation, the intensity of the kaolin characteristic peaks diminished. When the thermal activation temperature reached 950 °C, the majority of the kaolin characteristic peaks at 950 K disappeared. The characteristic peak of the kaolin-(001) crystal surface was the most prominent, and even after calcination, the relevant material retained its distinct peak. This phenomenon indicated that the kaolin-(001) crystal surface was the primary active reaction surface for all materials, which was also consistent with the conclusion of previous study [55].
Figure 2b shows the FT-IR results for PK and other modified kaolin. The peaks at 460, 562, 740, 902, and 1106 cm−1 were the characteristic vibrations of Si-O-Si, Al-O-Si, Si-O-Si, Al-OH, and Si-O/Al-O-Al, respectively [47]. The above characteristic peaks had little changes after thermal activation modification of the materials, but the peak at 3499 cm−1 (characteristic peak for the stretching vibration of -OH) [56] showed some slight changes. When the thermal activation temperature increased to 850 °C and 950 °C, nearly all characteristic peaks of -OH disappeared, indicating that the -OH of the samples had been basically removed.

3.2. XRF Results

Table 1 shows the XRF results for PK and modified kaolin. The Al2O3 and SiO2 constituted the primary components of PK and the three modified kaolins, accounting for nearly 90% of the total composition. Following thermal activation, the proportion of Al2O3 and SiO2 in all modified kaolins increased further. Moreover, the loss on ignition of 750-K (1.06%), 850-K (0.47%), and 950 K (0.24%) decreased significantly compared to PK (11.32%) after calcination, with the degree of reduction increasing as the thermal activation temperature rose. This phenomenon illustrated that high temperature had successfully removed the majority of water molecules/-OH groups from the structure.

3.3. SEM and BET Results

Figure 3 shows the SEM results of PK and the three modified kaolins. The surface of PK exhibited small flake-like structures (according to Figure 3a), and these flakes became more numerous after calcination at 750 °C (according to Figure 3b). Interestingly, when the heat activation temperature was 850 °C, the small flakes on the 850-K (according to Figure 3c) surface became more crushed and more dispersed. However, the number of small flakes on the surface of the 950-K (according to Figure 3d) had significantly decreased, and even large interconnected flakes had appeared. This might be due to excessive temperatures causing sintering of the material surface.
Table 2 shows the BET test results for PK and modified kaolin. Following modification, the textural characteristics of PK showed obvious improvement. For instance, while PK’s specific surface area was only 18 m2/g, those of 750-K, 850-K, and 950-K could reach 27, 36, and 31 m2/g respectively, indicating that thermal activation could enhance the material’s textural properties. The specific surface area, pore size, and pore volume of the 850-K were all higher than those of the 950-K, illustrating that higher calcination temperatures did not necessarily lead to improved pore characteristics in the material. Based on the SEM results, this might be attributed to structural changes in the material at 950 °C, resulting in sintering on the material surface.

4. Results of Batch Adsorption Experiments

4.1. Effect of pH

Figure 4 shows the results of adsorption capacity and removal rate for Pb (II) and Ni (II) with the effect of pH. On the whole, pH showed a great influence on the adsorption capacity and removal efficiency of Pb (II) and Ni (II). As pH rose from 4 to 6, both the adsorption capacity and removal efficiency of Pb (II) and Ni (II) progressively increased. The adsorption performance was poor at low pH, which could be attributed to the fact that more H+ ions were present at low pH, competing with Pb (II) and Ni (II) for adsorption sites [57]. The maximum adsorption capacity/removal efficiency for Pb (II) and Ni (II) were reached at pH 6 and 7, respectively. However, further increase in pH was not favorable for improving heavy metal adsorption performance. This might be due to excessively high pH potentially causing heavy metal precipitation, thus reducing the material’s adsorption capacity. Therefore, subsequent experiments would take place at pH = 6 for Pb (II) adsorption and at pH = 7 for Ni (II) adsorption.
Thermal activation modification of PK significantly enhanced its adsorption capacity for Pb (II) and Ni (II), and 850-K was the most effective adsorption material. At pH = 6, the adsorption capacity and removal rate of 850-K for Pb (II) reached 44.16 mg/g and 88.32%, significantly exceeding that of PK (30.55 mg/g and 61.61%, respectively). The adsorption effect of Ni (II) appeared to be generally slightly lower than that of Pb (II), and the best adsorption capacity for Ni (II) by 850-K was 39.76 mg/g, with the maximum removal rate of 79.49%. Overall, the adsorption capacities of materials for Pb (II) and Ni (II) were ranked as follows—850-K > 950-K > 750-K > PK—demonstrating that thermal activation modification indeed enhanced the reactivity of PK towards Pb (II)/Ni (II). Furthermore, the adsorption capacity ranking of the materials aligned with their specific surface area order, suggesting that the specific surface area might play a significant role in the adsorption capacity for Pb (II)/Ni (II).
Therefore, the next adsorption experiments on the effect of temperature for Pb (II) will be conducted at pH = 6, and those for Ni (II) at pH = 7.

4.2. Effect of Temperature

Based on the best parameters from Section 4.1, Figure 5 shows the results of adsorption capacity and removal rate for Pb (II) and Ni (II) under the effect of temperature. All adsorbents exhibited enhanced adsorption capacity for Pb (II) and Ni (II) following thermal activation modification, with the most favorable adsorption performance for 850-K. As the experimental temperature increased, both the adsorption capacity and removal efficiency of Pb (II) and Ni (II) continued to rise. However, when the experimental temperature reached 25 °C, the adsorption capacity and removal efficiency of both heavy metals showed little change compared to that at 30 °C. Furthermore, 25 °C was closer to the ambient temperature of the experiment. Across all temperatures studied, Pb (II) was better adsorbed than Ni (II). 850-K has achieved adsorption capacities of 44.16 mg/g for Pb (II) and 39.74 mg/g for Ni (II) at 25 °C, with removal rates of 88.32% and 79.49%, respectively.
Therefore, subsequent experiments will be conducted at 25 °C.

4.3. Effect of Additive Dosage of Adsorbents

Based on the best parameters from Section 4.1 and Section 4.2, Figure 6 shows the results of adsorption capacity and removal rate for Pb (II) and Ni (II) under the effect of additive dosage of adsorbents. From Figure 6a,b, with the gradual increase in the amounts of additives, the adsorption capacity of heavy metals per unit mass of all materials continuously decreased. Interestingly, according to Figure 6c,d, the removal efficiency of heavy metals by the four adsorbents generally increased with higher dosage. This might be because as the dosage of adsorbent was added, the sites available for adsorption increased, increasing the removal rates of Pb (II) and Ni (II). However, when the dosage reached a certain amount, the quantity of Pb (II) and Ni (II) enclosed per unit mass of adsorbent decreased, reducing the adsorption mass transfer driving force, leading to a decrease in the equilibrium adsorption capacity.
In general, 850-K was still the most effective modified kaolin for adsorption under comparable conditions, with Pb2+ continuing to be adsorbed more readily than Ni2+. From the perspective of removal rate, PK/750-K exhibited small differences compared to 0.15 g (for Pb (II)/Ni (II) of an average of 58.89% and 69.84% for PK and 750-K, respectively) and 0.20 g (on average for Pb (II)/Ni (II) of 60.18% and 70.66% for PK and 750-K, respectively) when added at 0.1 g (on average for Pb (II)/Ni (II) of 58.24% and 68.96% for PK and 750-K, respectively). However, 850-K and 950-K still showed some difference compared to 0.15 g at an addition amount of 0.1 g (average gap exceeds 7.15%), with the gap to 0.20 g only narrowing significantly once reaching 0.15 g (the average gap is not more than 1.7%). This indicated that PK/750K achieved almost maximum removal efficiency at the addition of 0.1 g, whereas 850-K/950-K was at 0.15 g. This also reflected the better contact capacity of 850-K/950-K with heavy metals, demonstrating superior adsorption potential, consistent with the experimental results.
Therefore, in the following experiment, the addition amount of PK/750-K is set to 0.1 g, while the addition amount of 850-K/950-K is set to 0.15 g.

4.4. Effect of Reaction Time

Based on the best parameters from Section 4.1, Section 4.2 and Section 4.3, Figure 7 shows the results of adsorption capacity and removal rate for Pb (II) and Ni (II) under the effect of reaction time. As a whole, the adsorption capacity/removal rate of all adsorbents for Pb (II)/Ni (II) continuously increased within the reaction time of 6 h. When the reaction time reached 7 h, the adsorption for Pb (II) was basically in equilibrium, while the adsorption of Ni (II) reached equilibrium at the reaction time of 8 h. This phenomenon illustrated that Pb (II) could reach adsorption equilibrium earlier than Ni (II). Considering that the adsorption amount of Pb (II) at equilibrium was also greater than that of Ni (II), this further demonstrated that Pb (II) exhibited superior adsorption properties.
It should be noted that the adsorption capacity of PK and 750-K appeared to be superior to that of 850-K and 950-K (as shown in Figure 7a,b), but this did not imply that PK/750-K exhibited better heavy metal adsorption performance than 850-K/950-K. According to the experimental patterns and optimal parameters in Section 4.2, the adsorption capacity per unit mass of all adsorbents decreased with increasing dosage. The dosage of 850-K/950-K was 0.15 g, while that of PK/750-K was 0.1 g, resulting in the superior unit adsorption capacity of PK/750-K compared to 850-K/950-K in this part. According to Figure 7c,d, 850-K was still the most effective adsorbent among all materials, achieving removal rates of 92.74% for Pb (II) and 90.72% for Ni (II) after reaching adsorption equilibrium.
As a result of this section, it could be determined that the time required for Pb (II) to reach adsorption equilibrium was 7 h, whereas it was 8 h for Ni (II), and 850-K was the most effective adsorbent.

4.5. Effect of Metal Concentration

Based on the best parameters from Section 4.1, Section 4.2, Section 4.3 and Section 4.4, Figure 8 shows the results of adsorption capacity and removal rate for Pb (II) and Ni (II) under the effect of metal concentration. Generally, as heavy metal concentrations increased, the adsorption capacity per unit mass of the adsorbent also increased progressively. This occurs because the number of metal ions available for adsorption increases, while the competitive effect of H+ diminishes, consequently leading to a continuous increase in adsorption capacity. Although Figure 8a,b suggest that the PK/750-K exhibited better adsorption capacity per unit mass than the 850-K/950-K due to differing material addition amounts, Figure 8c,d indicate that the 850-K remained the most effective adsorbent for heavy metal removal.
It is to be noted that as the metal concentration increased from 10 to 50 mg/L, the removal efficiency of all adsorbents for heavy metals steadily increased. However, when the metal concentration reached 60 mg/L, there was almost no additional improvement in removal efficiency and even exhibited a slight decline. Since the volume of the experimental solution was finite, this might be attributable to the fact that elevated heavy metal concentrations to some extent hindered their mobility in water, thereby diminishing mass transfer efficiency between the metals and the adsorbent, resulting in a corresponding reduction in removal efficiency.
Therefore, the subsequent experiments would be performed with of Pb (II) and Ni (II) concentrations of 50 mg/L.

4.6. Results of Adsorption Kinetics Experiments

Table 3 shows the kinetic model parameters for Pb (II) and Ni (II) for the four materials. The results of kinetic models fitting indicated that the pseudo-second-order kinetic model provided a better fit for the adsorption of all materials with Pb (II)/Ni (II), and the R2 values all exceeded 0.95. This phenomenon indicated that the adsorption of heavy metals by PK and modified kaolin might involve ion exchange, complexation, and precipitation mechanisms, and the adsorption process was mainly a chemisorption reaction [58,59]. Furthermore, the fitting results from pseudo-second-order kinetics showed that the qe values for Pb (II) and Ni (II) adsorbed by 850-K were 75.372 and 72.046 mg/g, respectively, which were the highest among all adsorbents. This once again demonstrated that 850-K was the most effective modified kaolin.

4.7. Results of Adsorption Thermodynamics Experiments

Table 4 shows the kinetic model parameters for Pb (II) and Ni (II) for the four materials. On the whole, both thermodynamic models provided good fits for the adsorption process of Pb (II)/Ni (II) by the materials, with all the R2 values exceeding 0.96. Kf denotes the strength of affinity between the adsorbent and adsorbate, with a higher value indicating greater affinity. It could be observed that the Kf value for Pb (II) was higher than that for Ni (II), indicating superior adsorption performance for Pb (II). Furthermore, the Kf values for 850-K were maximal at 850 K, with values of 8.322 for Pb (II) and 3.674 for Ni (II), further confirming the best adsorption performance of 850-K. The Langmuir model (R2 = 0.982 on average) fitted the adsorption data better than the Freundlich model (R2 = 0.962 on average), and the results of qe values indicated that 850-K was the optimal adsorbent, and 850-K showed superior adsorption capacity for Pb (II) (57.278 mg/g) compared to Ni (II) (55.141 mg/g). Moreover, the Langmuir model exhibited superior fitting performance, indicating that adsorption predominantly occurred as monolayer adsorption [60].

5. Simulation Results

5.1. Models Establishment and Optimization Results

The final optimized results for the PK, 850-K, PbCl2, and NiCl2 models are shown in Figure 9. The PK structure primarily comprises Si-O tetrahedra and Al-O octahedra. Following thermal activation, all -OH groups within the 850-K structure were removed, exposing a greater number of active O atoms. After geometry optimization, the bond length of PbCl2 was found to be 2.488 Å, with a bond angle of 99.82°, while NiCl2 exhibited bond length and angle of 2.031 Å and 179.90°, respectively. The establishment and optimization of these models provide the foundation for subsequent simulations.

5.2. Simulation of the Reaction Between PbCl2/NiCl2, and PK/850-K in Water

Figure 10 shows the final adsorption configurations of PbCl2 and NiCl2 on PK and 850-K in water. The distance between different adsorbates and the same adsorbent can, to some extent, indicate the strength of the reaction between these adsorbates and the adsorbent [61]. From the reaction results of PbCl2/NiCl2 and PK, it can be seen that the distance between PbCl2 and PK was closer than that between NiCl2 and PK, indicating that PbCl2 (2.78 Å on average) was more easily adsorbed by PK than NiCl2 (3.16 Å on average). After thermal activation modification, the average distances between 850-K and individual PbCl2 and NiCl2 atoms were 2.45 Å and 2.57 Å, respectively, demonstrating obvious adsorption advantages compared to PK. This finding is generally consistent with experimental conclusions.
Table 5 summarizes the changes in bond lengths and bond angles for PbCl2/NiCl2 before and after reacting with PK/850-K in water. Following their reaction with PK/850-K in water, both the bond lengths and bond angles of PbCl2/NiCl2 showed some changes, indicating that the reaction had certainly influenced them to some extent. Similarly, following the reaction, their bond lengths all increased slightly, while the bond angles decreased to varying degrees. Interestingly, the angles and bond lengths of PbCl2 (−6.94° and +0.194 Å on average)/NiCl2 (−5.13° and +0.099 Å on average) changed more significantly after reacting with 850-K than the reaction of PK with PbCl2 (−4.40° and +0.070 Å on average)/NiCl2 (−2.55° and +0.051 Å on average). PbCl2 exhibited greater changes in both bond length and bond angle after reaction compared to NiCl2. This phenomenon might illustrate that the interaction between 850-K and heavy metals was more powerful than that between PK and heavy metals, and that PbCl2 was more reactive than NiCl2.

5.3. Results of FMO

Figure 11 shows the simulated FMO electron cloud contours for PK, 850-K, PbCl2, and NiCl2. The different shapes in the figure represent electron cloud contours, with varying colors indicating opposite electron directions. The LUMO orbital electron cloud in PK was predominantly concentrated near the Al-O atoms, whereas the HOMO electron cloud was situated around the Si-O atoms. For 850-K, both the LUMO and HOMO electron cloud contours were larger than those of PK, with richer colors, suggesting that 850-K exhibited superior reactivity. Moreover, the electron cloud of the LUMO orbital of NiCl2 was predominantly concentrated around the Ni atom, while it was virtually absent around the Cl atom. The electron cloud distribution profiles for HOMO of NiCl2 and HOMO/LUMO for PbCl2 were present around all atoms. However, it was not possible to quantitatively assess the strength of reaction induction between substances solely through FMO electronic clouds, and further evaluation via Δ E G of FMO was required.
As shown in Figure 12, the Δ E G of FMO for PK/850-K and PbCl2/NiCl2 are presented. It could be observed that PK exhibited lower ΔE2 values with both heavy metals, whereas 850-K showed lower ΔE1 values with PbCl2/NiCl2. This meant that the reaction between PK and PbCl2/NiCl2 primarily involved electrons flowing from PK’s HOMO to the LUMO of the heavy metals, whereas the reaction between 850-K and PbCl2/NiCl2 involved electrons flowing from the HOMO of the heavy metals to the LUMO of 850-K.
Lower Δ E G of FMO between substances indicate stronger inductive tendencies in their reactions. The minimum Δ E G of FMO for PK and PbCl2/NiCl2 were 2.182/2.257 eV, whereas those for 850-K and PbCl2/NiCl2 were merely 0.301/358 eV. On the one hand, this illustrated that PK/850-K showed greater reactivity with PbCl2 than NiCl2, while on the other hand, it meant that 850-K had superior reactivity compared to PK. These phenomena were more consistent with the experimental conclusions, proving their reliability.

5.4. Results of Δ E

To further compare the reactivity of PK/850-K and PbCl2/NiCl2, Δ E was calculated for judgment, with the results illustrated in Figure 13. The Δ E between PbCl2/NiCl2 and PK/850-K were all <0, indicating that adsorption can occur between them. The Δ E between PK and PbCl2/NiCl2 were −204.56/−174.25 kcal/mol, respectively, while those between 850-K and PbCl2/NiCl2 were −252.82 and −236.35 kcal/mol, respectively. This further demonstrated that 850-K exhibited greater reactivity than PK, and that PbCl2 could be adsorbed more effectively than NiCl2. However, although Δ E can determine the strength of adsorption between two substances, it cannot yet reveal the bonding mechanism between them in depth. Therefore, CD and DCD simulations will be employed next to further investigate the key mechanism.

5.5. Results of CD and DCD

Previous results show that 850-K showed greater reactivity than PK. Therefore, 850-K was selected for CD/DCD calculations with PbCl2/NiCl2. Figure 14 illustrates the CD and DCD simulation results for the reaction between 850-K and PbCl2/NiCl2. It has been reported that when CD overlap exists between two atoms and DCD transfer occurs, the atoms are primarily bonded by covalent bonds, whereas when CD overlap is absent but DCD transfer is present, they are predominantly bonded by ionic bonds [62,63]. As shown in Figure 14a, the Pb atoms in PbCl2 exhibited distinct CD overlap, with O atoms on the 850-K surface. Furthermore, as depicted in Figure 14c, charge transfer also occurred between the O atoms on the 850-K surface and the Pb atoms. This means that Pb can form covalent bonds with the O atoms on the 850-K surface. Although the Cl atoms of PbCl2 did not form CD overlap with 850-K, they exhibited distinct DCD transfer with Al atoms, indicating that their interaction was likely dominated by ionic bonding. Moreover, the two Cl atoms of NiCl2 had CD and DCD overlap with O atoms at 850-K, proving that they also mainly combined by covalent bonds. The Ni atom depicted no discernible overlap with either CD or DCD with 850-K, indicating that NiCl2 primarily bonded with 850-K via the Cl atoms, while the Ni atom likely interacted with 850-K predominantly through electrostatic attraction. Al atoms showed negligible DCD transfer and no CD overlap with NiCl2, indicating that Al atoms formed virtually no bonds with NiCl2 and had relatively weak reactivity. In summary, 850-K could react with PbCl2/NiCl2 in water, and the bonding mechanisms between them were different, with the O atoms being the main atoms involved in the reaction between 850-K and PbCl2/NiCl2.

6. Conclusions

This study thermally activated PK at 750 °C, 850 °C,s and 950 °C, enhancing its adsorption capacity for Pb (II) and Ni (II) in wastewater. The best reaction parameters were continuously established by varying pH, reaction time, temperature, adsorbent dosage and heavy metal concentration. Adsorption behavior was modeled using pseudo-first/pseudo-second-order kinetics and Langmuir/Freundlich thermodynamic models. DFT/MD simulations were also used to reveal the reaction mechanisms between PbCl2 and NiCl2 with PK/850-K. The main conclusions are as follows:
(1) Through calcination, 750-K, 850-K, and 950-K were successfully prepared. All the modified kaolins were characterized using XRD, FT-IR, XRF, SEM, and BET analyses. The kaolin-(001) surface was the dominant surface of the materials, mainly consisting of Al/Si element, and 850-K was the material with the most favorable textural properties.
(2) Following batch experiments, 25 °C and 50 mg/L were both the best reaction temperature and initial heavy metal concentration for PbCl2 and NiCl2. The optimal pH and reaction times for PbCl2/NiCl2 were 6/7 and 7/8 h, respectively. The optimum addition amounts for PK/750-K and 850-K/950-K were 0.1 and 0.15 g, respectively. 850-K was the most effective adsorbent, achieving removal rates >90% for both PbCl2 and NiCl2 under optimal conditions, and the removal efficiency for PbCl2 was better than that for NiCl2. The pseudo-second-order kinetic model and Langmuir model could better fit the adsorption process of PbCl2/NiCl2.
(3) Quantum chemical models for PK, 850-K, PbCl2, and NiCl2 were established and optimized. Through simulating the nearest atomic distances, Δ E G , Δ E , and variations in bond lengths and angles of PbCl2/NiCl2 during reactions with PK and 850-K in water, it was found that 850-K exhibited greater reactivity and PbCl2 was more readily adsorbed. These findings are consistent with experimental conclusions, demonstrating the reliability of the data.
(4) The FMO electronic flow simulation results indicate that PK reacted with PbCl2/NiCl2 mainly via electron flow from PK’s HOMO to the heavy metals’ LUMO, whereas 850-K reacted with them via electron flow from the heavy metals’ HOMO to 850-K’s LUMO. CD and DCD simulation results indicate that the O atoms were the main reacting atoms in the reaction between 850-K and PbCl2/NiCl2 in water. The O atoms can form covalent bonds with both Pb and the Cl atoms of NiCl2. The Cl atoms of PbCl2 primarily form ionic bonds with the Al atoms of 850-K, whereas Ni atoms may interact with 850-K via electrostatic forces.
The preparation process for the adsorbent developed in this study was simple and low cost, as well as exhibiting favorable adsorption performance towards Pb (II) and Ni (II), demonstrating potential for large-scale application. Furthermore, experimental data were mutually validated with simulation results, whilst the critical reaction mechanisms between PbCl2/NiCl2 and the adsorbent in water were revealed in depth through modeling. This study provides significant reference value for the treatment of heavy metals in wastewater. Future research can be further developed to conduct in-depth experimental and simulation studies on more types of heavy metals.

Author Contributions

Conceptualization, Z.Y. and Y.Y.; Data curation, G.W. and R.Q.; Formal analysis, G.W. and R.Q.; Funding acquisition, Y.Y.; Investigation, G.W. and R.Q.; Methodology, Z.Y. and Y.Y.; Project administration, Y.Y.; Resources, G.W. and R.Q.; Software, Z.Y.; Supervision, Y.Y.; Validation, R.Q.; Visualization, Z.Y.; Writing—original draft, Z.Y.; Writing—review and editing, Z.Y. and Y.Y. All authors have read and agreed to the published version of the manuscript.

Funding

Start-up Funding for Postdoctoral Research Projects from Taizhou, 2015AAS0326.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

I would like to thank the funding and anonymous reviewers who have helped to improve the paper.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Ergene, B.; Balkaya, N. Heavy Metal (Cr, Cu, Ni, and Zn) Removal from Electroplating Wastewater Using an Agro-İndustrial Byproduct. Int. J. Environ. Res. 2025, 19, 219. [Google Scholar] [CrossRef]
  2. Piotrowicz, A.; Noga, P.; Skrzekut, T.; Kozub-Budzyn, G.A.; Wedrychowicz, M.; Skarupska, D. Microscopic and quantitative characterization of germanium-indium bearing by-product from heavy metal metallurgy. Sci. Rep. 2025, 15, 1885. [Google Scholar] [CrossRef] [PubMed]
  3. Zhang, J.; Jiao, Q.; Wu, Y.; Liu, H.; Yu, P.; Liu, D.; Hua, D.; Song, J. Evaluation of Heavy Metal Contamination and Associated Human Health Risk in Soils around a Battery Industrial Zone in Henan Province, Central China. Agriculture 2024, 14, 804. [Google Scholar] [CrossRef]
  4. Fang, J.; Xu, M.; Tan, Z.; Guo, J.; Tao, H.; Ruan, J. Bioaccessibility and health risk assessment of heavy metals in dust from electronic waste recycling in China. Process Saf. Environ. Prot. 2025, 201, 107550. [Google Scholar] [CrossRef]
  5. Yang, R.; Lu, H.; Zhou, J.; Qi, L.; Wu, X.; Rezakazemi, M.; Ge, S. Next-generation biomass nanocomposites for heavy metal ion adsorption: Innovations and environmental impact. Sep. Purif. Technol. 2025, 370, 133157. [Google Scholar] [CrossRef]
  6. Jawad, N.H.; Darwesh, T.M.; Abbas, A.F.; Yahya, A.A.; Kamel, A.H.; Rashid, K.T.; Abood, T.W.; Al-Juboori, R.A.; Meskher, H.; Al-Saadi, S.; et al. MXene Synthesis, Surface Functionalization, and Membrane Integration for Photocatalytic Removal of Heavy Metals from Wastewater: A Comprehensive Review. Mater. Today Sustain. 2025, 32, 101208. [Google Scholar] [CrossRef]
  7. da Costa, L.S.; Teixeira, D.S.; Bovendorp, R.S. Heavy metal accumulation in non-human primates: A global systematic review. Environ. Pollut. 2025, 385, 127042. [Google Scholar] [CrossRef]
  8. Anaqi Zaimee, M.Z.; Sani Sarjadi, M.; Lutfor Rahman, M. Heavy metals removal from water by efficient adsorbents. Water 2021, 13, 2659. [Google Scholar] [CrossRef]
  9. Kromah, V.; Zhang, G. Aqueous Adsorption of Heavy Metals on Metal Sulfide Nanomaterials: Synthesis and Application. Water 2021, 13, 1843. [Google Scholar] [CrossRef]
  10. Kuldeyev, E.; Seitzhanova, M.; Tanirbergenova, S.; Tazhu, K.; Doszhanov, E.; Mansurov, Z.; Azat, S.; Nurlybaev, R.; Berndtsson, R. Modifying Natural Zeolites to Improve Heavy Metal Adsorption. Water 2023, 15, 2215. [Google Scholar] [CrossRef]
  11. Simeonidis, K.; Mitrakas, M. Technologies Developing in Heavy Metals’ Removal from Water. Water 2021, 13, 860. [Google Scholar] [CrossRef]
  12. Nthwane, Y.B.; Fouda-Mbanga, B.G.; Thwala, M.; Pillay, K. A comprehensive review of heavy metals (Pb2+, Cd2+, Ni2+) removal from wastewater using low-cost adsorbents and possible revalorisation of spent adsorbents in blood fingerprint application. Environ. Technol. 2025, 46, 414–430. [Google Scholar] [CrossRef]
  13. Fan, D.; Peng, Y.; He, X.; Ouyang, J.; Fu, L.; Yang, H. Recent Progress on the Adsorption of Heavy Metal Ions Pb(II) and Cu(II) from Wastewater. Nanomaterials 2024, 14, 1037. [Google Scholar] [CrossRef]
  14. Ahmed, A.; Huo, A.; Ibrahim, M. Progressive Approaches in Ni(II) Contaminated Water Treatment: A Review of Adsorbent Strategies. Water Air Soil Pollut. 2025, 236, 5. [Google Scholar] [CrossRef]
  15. Järup, L. Hazards of heavy metal contamination. Br. Med. Bull. 2003, 68, 167–182. [Google Scholar] [CrossRef]
  16. Chowdhury, S.; Mazumder, M.A.J.; Al-Attas, O.; Husain, T. Heavy metals in drinking water: Occurrences, implications, and future needs in developing countries. Sci. Total Environ. 2016, 569, 476–488. [Google Scholar] [CrossRef] [PubMed]
  17. Li, Z.; Ma, Z.; van der Kuijp, T.J.; Yuan, Z.; Huang, L. A review of soil heavy metal pollution from mines in China: Pollution and health risk assessment. Sci. Total Environ. 2014, 468, 843–853. [Google Scholar] [CrossRef]
  18. Kafadar, F.N.; Saygideger, S. Determination of Lead (Pb) content in some agricultural plants irrigated with industrial waste water around Gaziantep province. Ekoloji 2010, 19, 41–48. [Google Scholar] [CrossRef]
  19. Ferancova, A.; Hattuniemi, M.K.; Sesay, A.M.; Raty, J.P.; Virtanen, V.T. Rapid and direct electrochemical determination of Ni(II) in industrial discharge water. J. Hazard. Mater. 2016, 306, 50–57. [Google Scholar] [CrossRef] [PubMed]
  20. Jiann, K.-T.; Wen, L.-S.; Gong, G.-C. Distribution and Behaviors of Cd, Cu, and Ni in the East China Sea Surface Water off the Changjiang Estuary. Terr. Atmos. Ocean. Sci. 2009, 20, 433–443. [Google Scholar] [CrossRef]
  21. Triantafyllidou, S.; Le, T.; Gallagher, D.; Edwards, M. Reduced risk estimations after remediation of lead (Pb) in drinking water at two US school districts. Sci. Total Environ. 2014, 466, 1011–1021. [Google Scholar] [CrossRef]
  22. Matlock, M.M.; Howerton, B.S.; Atwood, D.A. Chemical precipitation of heavy metals from acid mine drainage. Water Res. 2002, 36, 4757–4764. [Google Scholar] [CrossRef]
  23. Dabrowski, A.; Hubicki, Z.; Podkoscielny, P.; Robens, E. Selective removal of the heavy metal ions from waters and industrial wastewaters by ion-exchange method. Chemosphere 2004, 56, 91–106. [Google Scholar] [CrossRef]
  24. Janjhi, F.A.; Janwery, D.; Chandio, I.; Ullah, S.; Rehman, F.; Memon, A.A.; Hakami, J.; Khan, F.; Boczkaj, G.; Thebo, K.H. Recent Advances in Graphene Oxide-Based Membranes for Heavy Metal Ions Separation. Chembioeng Rev. 2022, 9, 574–590. [Google Scholar] [CrossRef]
  25. Zheng, X.; Alam, O.; Zhou, Y.; Du, D.; Li, G.; Zhu, W. Heavy metals detection and removal from contaminated water: A critical review of adsorption methods. J. Environ. Chem. Eng. 2024, 12, 114366. [Google Scholar] [CrossRef]
  26. Zhang, X.-S.; Chen, Y.-G.; Wang, Q.-Y.; Sun, Y.-L. Advances in heavy metal wastewater treatment with biochar adsorption. Biofuels Bioprod. Biorefining 2025. [Google Scholar] [CrossRef]
  27. Reta, Y.D.; Desissa, T.D.; Desalegn, Y.M. Adsorption of heavy metal ions from wastewater: A critical review. Desalination Water Treat. 2023, 315, 413–431. [Google Scholar] [CrossRef]
  28. Liu, J.-F.; Zhao, Z.-S.; Jiang, G.-B. Coating Fe3O4 magnetic nanoparticles with humic acid for high efficient removal of heavy metals in water. Environ. Sci. Technol. 2008, 42, 6949–6954. [Google Scholar] [CrossRef]
  29. Barik, B.; Kumar, A.; Nayak, P.S.; Achary, L.S.K.; Rout, L.; Dash, P. Ionic liquid assisted mesoporous silica-graphene oxide nanocomposite synthesis and its application for removal of heavy metal ions from water. Mater. Chem. Phys. 2020, 239, 122028. [Google Scholar] [CrossRef]
  30. Hosseini, M.R.; Ahmadi, A. Biological beneficiation of kaolin: A review on iron removal. Appl. Clay Sci. 2015, 107, 238–245. [Google Scholar] [CrossRef]
  31. Dill, H.G. Kaolin: Soil, rock and ore From the mineral to the magmatic, sedimentary and metamorphic environments. Earth-Sci. Rev. 2016, 161, 16–129. [Google Scholar] [CrossRef]
  32. Nandi, B.K.; Goswami, A.; Purkait, M.K. Adsorption characteristics of brilliant green dye on kaolin. J. Hazard. Mater. 2009, 161, 387–395. [Google Scholar] [CrossRef] [PubMed]
  33. Geerlings, P.; De Proft, F.; Langenaeker, W. Conceptual density functional theory. Chem. Rev. 2003, 103, 1793–1873. [Google Scholar] [CrossRef] [PubMed]
  34. Zhang, X.; Lin, S.; Lu, X.-Q.; Chen, Z.-L. Removal of Pb(II) from water using synthesized kaolin supported nanoscale zero-valent iron. Chem. Eng. J. 2010, 163, 243–248. [Google Scholar] [CrossRef]
  35. Tang, Q.; Tang, X.; Li, Z.; Chen, Y.; Kou, N.; Sun, Z. Adsorption and desorption behaviour of Pb(II) on a natural kaolin: Equilibrium, kinetic and thermodynamic studies. J. Chem. Technol. Biotechnol. 2009, 84, 1371–1380. [Google Scholar] [CrossRef]
  36. Quintelas, C.; Rocha, Z.; Silva, B.; Fonseca, B.; Figueiredo, H.; Tavares, T. Removal of Cd(II), Cr(VI), Fe(III) and Ni(II) from aqueous solutions by an E. coli biofilm supported on kaolin. Chem. Eng. J. 2009, 149, 319–324. [Google Scholar] [CrossRef]
  37. Ezzati, R.; Ezzati, S.; Azizi, M. Exact solution of the Langmuir rate equation: New Insights into pseudo-first-order and pseudo-second-order kinetics models for adsorption. Vacuum 2024, 220, 112790. [Google Scholar] [CrossRef]
  38. Ho, Y.-S. Review of second-order models for adsorption systems. J. Hazard. Mater. 2006, 136, 681–689. [Google Scholar] [CrossRef]
  39. Gunjal, A. Study of Langmuir kinetics for removal of heavy metals by the fungal biomass. Proc. Indian Natl. Sci. Acad. 2021, 87, 107–109. [Google Scholar] [CrossRef]
  40. Thiele, S.; Leinweber, P. Parameterization of Freundlich adsorption isotherms for heavy metals in soils from an area with intensive livestock production. J. Plant Nutr. Soil Sci. 2001, 164, 623–629. [Google Scholar] [CrossRef]
  41. Zhang, X.; Liu, H.; Xing, H.; Li, H.; Hu, H.; Li, A.; Yao, H. Improved sodium adsorption by modified kaolinite at high temperature using intercalation-exfoliation method. Fuel 2017, 191, 198–203. [Google Scholar] [CrossRef]
  42. Li, J.; Zhong, Z.; Ma, Y.; Lai, X.; Li, Z. Adsorption Mechanism of PbO/PbCl2 on Kaolinite Surfaces during Coal Combustion Based on Frontier Orbital Theory. Energy Fuels 2020, 34, 11258–11269. [Google Scholar] [CrossRef]
  43. Yang, Y.; Zhong, Z.; Li, J.; Du, H.; Li, Q.; Zheng, X.; Qi, R.; Zhang, S.; Li, Z. Low-consumption with efficient capture and characteristics of heavy metals from coal combustion by modified kaolin: Experimental and simulation studies. Fuel 2022, 332, 126094. [Google Scholar] [CrossRef]
  44. Clark, S.J.; Segall, M.D.; Pickard, C.J.; Hasnip, P.J.; Probert, M.J.; Refson, K.; Payne, M.C. First principles methods using CASTEP. Z. Fur Krist. 2005, 220, 567–570. [Google Scholar] [CrossRef]
  45. Perdew, J.P.; Burke, K.; Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 1996, 77, 3865, Erratum in Phys. Rev. Lett. 1997, 78, 1396. [Google Scholar] [CrossRef]
  46. Tóbik, J.; Dal Corso, A. Electric fields with ultrasoft pseudo-potentials:: Applications to benzene and anthracene. J. Chem. Phys. 2004, 120, 9934–9941. [Google Scholar] [CrossRef]
  47. Yang, Y.; Zhong, Z.; Li, J.; Du, H.; Li, Z. Efficient with low-cost removal and adsorption mechanisms of norfloxacin, ciprofloxacin and ofloxacin on modified thermal kaolin: Experimental and theoretical studies. J. Hazard. Mater. 2022, 430, 128500. [Google Scholar] [CrossRef]
  48. Guo, L.; Kaya, S.; Obot, I.B.; Zheng, X.; Qiang, Y. Toward understanding the anticorrosive mechanism of some thiourea derivatives for carbon steel corrosion: A combined DFT and molecular dynamics investigation. J. Colloid Interface Sci. 2017, 506, 478–485. [Google Scholar] [CrossRef]
  49. Wang, H.; Guo, W.; Yin, R.; Du, J.; Wu, Q.; Luo, H.; Liu, B.; Sseguya, F.; Ren, N. Biochar-induced Fe(III) reduction for persulfate activation in sulfamethoxazole degradation: Insight into the electron transfer, radical oxidation and degradation pathways. Chem. Eng. J. 2019, 362, 561–569. [Google Scholar] [CrossRef]
  50. Sun, C.; Qin, S.; Wang, R.; Chen, S.; Pan, F.; Qiu, B.; Shang, Z.; Meng, L.; Zhang, C.; Xiao, M.; et al. High Efficiency Polymer Solar Cells with Efficient Hole Transfer at Zero Highest Occupied Molecular Orbital Offset between Methylated Polymer Donor and Brominated Acceptor. J. Am. Chem. Soc. 2020, 142, 1465–1474. [Google Scholar] [CrossRef] [PubMed]
  51. Fukui, K.; Koga, N.; Fujimoto, H. Interaction frontier orbitals. J. Am. Chem. Soc. 1981, 103, 196–197. [Google Scholar] [CrossRef]
  52. Yang, Y.; Zhong, Z.; Jin, B.; Zhang, B.; Du, H.; Li, Q.; Zheng, X.; Qi, R.; Ren, P. Stabilization of heavy metals in solid waste and sludge pyrolysis by intercalation-exfoliation modified vermiculite. J. Environ. Manag. 2024, 356, 120747. [Google Scholar] [CrossRef]
  53. Delley, B. From molecules to solids with the DMol3 approach. J. Chem. Phys. 2000, 113, 7756–7764. [Google Scholar] [CrossRef]
  54. Yang, Y.; Zhong, Z.; Zhen, Z.; Jin, B.; Zhang, B.; Du, H.; Li, Q.; Zheng, X.; Qi, R.; Ye, Q.; et al. Hazard reduction of heavy metals by co-pyrolysis of modified vermiculite with paper mill sludge/municipal solid waste: Characterization, risk and reaction mechanism study in pyrolytic environment. J. Anal. Appl. Pyrolysis 2024, 182, 106725. [Google Scholar] [CrossRef]
  55. Li, J.F.; Zhong, Z.P.; Du, H.R.; Li, Q.; Wang, N.B.; Zhao, H.; Huang, J.W. Theoretical study on the adsorption mechanism of PbCl2/CdCl2 by kaolinite during municipal solid waste pyrolysis. Chemosphere 2021, 267, 129184. [Google Scholar] [CrossRef]
  56. Yu, M.; Huang, Y.; Xia, W.; Zhu, Z.; Fan, C.; Liu, C.; Dong, L.; Xu, L.; Liu, L.; Zha, J.; et al. PbCl2 Capture by Kaolin and Metakaolin under Different Influencing Factors of Thermal Treatment. Energy Fuels 2020, 34, 2284–2292. [Google Scholar] [CrossRef]
  57. Rusova, N.V.; Astashkina, O.V.; Lysenko, A.A. Adsorption of Heavy Metals by Activated Carbon Fibres. Fibre Chem. 2015, 47, 320–323. [Google Scholar] [CrossRef]
  58. Ahmad, Z.; Gao, B.; Mosa, A.; Yu, H.; Yin, X.; Bashir, A.; Ghoveisi, H.; Wang, S. Removal of Cu(II), Cd(II) and Pb(II) ions from aqueous solutions by biochars derived from potassium-rich biomass. J. Clean. Prod. 2018, 180, 437–449. [Google Scholar] [CrossRef]
  59. Lin, K.-Y.A.; Liu, Y.-T.; Chen, S.-Y. Adsorption of fluoride to UiO-66-NH2 in water: Stability, kinetic, isotherm and thermodynamic studies. J. Colloid Interface Sci. 2016, 461, 79–87. [Google Scholar] [CrossRef]
  60. Yuan, W.; Kuang, J.; Yu, M.; Huang, Z.; Zou, Z.; Zhu, L. Facile preparation of MoS2@Kaolin composite by one-step hydrothermal method for efficient removal of Pb(II). J. Hazard. Mater. 2021, 405, 124261. [Google Scholar] [CrossRef] [PubMed]
  61. Yang, Y.; Zhong, Z.; Zhang, H.; Qiao, M.; Zhen, Z.; Xu, Y.; Jin, B.; Zhang, B.; Du, H.; Li, Q.; et al. Heavy metal stabilization via copyrolysis of comodified vermiculite with municipal sludge/aged refuse: Comprehensive analysis of hazards and characteristics of multiple coexisting heavy metals. J. Hazard. Mater. 2024, 480, 136325. [Google Scholar] [CrossRef] [PubMed]
  62. Lee, S.G.; Choi, J.I.; Koh, W.; Jang, S.S. Adsorption of β-D-glucose and cellobiose on kaolinite surfaces: Density functional theory (DFT) approach. Appl. Clay Sci. 2013, 71, 73–81. [Google Scholar] [CrossRef]
  63. Ma, L.-C.; Zhao, H.-S.; Yan, W.-J. Structural, electronic and magnetic properties of linear monoatomic chains adsorption on beryllium oxide nanotube: First-principle study. J. Magn. Magn. Mater. 2013, 330, 174–180. [Google Scholar] [CrossRef]
Water 17 03015 g001
Figure 1. Schematic diagram of the FMO.
Figure 1. Schematic diagram of the FMO.
Water 17 03015 g001
Water 17 03015 g002
Figure 2. XRD (a) and FT-IR (b) results of PK and modified kaolin.
Figure 2. XRD (a) and FT-IR (b) results of PK and modified kaolin.
Water 17 03015 g002
Water 17 03015 g003
Figure 3. SEM results of PK (a), 750-K (b), 850-K (c) and 950-K (d).
Figure 3. SEM results of PK (a), 750-K (b), 850-K (c) and 950-K (d).
Water 17 03015 g003
Water 17 03015 g004
Figure 4. Adsorption capacity (a) and removal rate (c) of Pb (II) for four materials under influence of pH. Adsorption capacity (b) and removal rate (d) of Ni (II) for four materials under influence of pH.
Figure 4. Adsorption capacity (a) and removal rate (c) of Pb (II) for four materials under influence of pH. Adsorption capacity (b) and removal rate (d) of Ni (II) for four materials under influence of pH.
Water 17 03015 g004
Water 17 03015 g005
Figure 5. Adsorption capacity (a) and removal rate (c) of Pb (II) for four materials under influence of temperature. Adsorption capacity (b) and removal rate (d) of Ni (II) for four materials under influence of temperature.
Figure 5. Adsorption capacity (a) and removal rate (c) of Pb (II) for four materials under influence of temperature. Adsorption capacity (b) and removal rate (d) of Ni (II) for four materials under influence of temperature.
Water 17 03015 g005
Water 17 03015 g006
Figure 6. Adsorption capacity (a) and removal rate (c) of Pb (II) for four materials under influence of additive amount. Adsorption capacity (b) and removal rate (d) of Ni (II) for four materials under influence of additive amount.
Figure 6. Adsorption capacity (a) and removal rate (c) of Pb (II) for four materials under influence of additive amount. Adsorption capacity (b) and removal rate (d) of Ni (II) for four materials under influence of additive amount.
Water 17 03015 g006
Water 17 03015 g007
Figure 7. Adsorption capacity (a) and removal rate (c) of Pb (II) for four materials under influence of time for reaction. Adsorption capacity (b) and removal rate (d) of Ni (II) for four materials under influence of time for reaction.
Figure 7. Adsorption capacity (a) and removal rate (c) of Pb (II) for four materials under influence of time for reaction. Adsorption capacity (b) and removal rate (d) of Ni (II) for four materials under influence of time for reaction.
Water 17 03015 g007
Water 17 03015 g008
Figure 8. Adsorption capacity (a) and removal rate (c) of Pb (II) for four materials under influence of metal concentration. Adsorption capacity (b) and removal rate (d) of Ni (II) for four materials under influence of metal concentration.
Figure 8. Adsorption capacity (a) and removal rate (c) of Pb (II) for four materials under influence of metal concentration. Adsorption capacity (b) and removal rate (d) of Ni (II) for four materials under influence of metal concentration.
Water 17 03015 g008
Water 17 03015 g009
Figure 9. Model establishment and optimization results for PK, 850-K, PbCl2, and NiCl2.
Figure 9. Model establishment and optimization results for PK, 850-K, PbCl2, and NiCl2.
Water 17 03015 g009
Water 17 03015 g010
Figure 10. Final adsorption configurations of PbCl2and NiCl2 on PK and 850-K in water (the black lines represent the closest atomic distances from PbCl2/NiCl2 to PK/850-K).
Figure 10. Final adsorption configurations of PbCl2and NiCl2 on PK and 850-K in water (the black lines represent the closest atomic distances from PbCl2/NiCl2 to PK/850-K).
Water 17 03015 g010
Water 17 03015 g011
Figure 11. LUMO and HOMO simulated electron density clouds for PK, 850-K, PbCl2 and NiCl2.
Figure 11. LUMO and HOMO simulated electron density clouds for PK, 850-K, PbCl2 and NiCl2.
Water 17 03015 g011
Water 17 03015 g012
Figure 12. Simulation results for the Δ E G of FMO between PK/850-K and PbCl2/NiCl2.
Figure 12. Simulation results for the Δ E G of FMO between PK/850-K and PbCl2/NiCl2.
Water 17 03015 g012
Water 17 03015 g013
Figure 13. The Δ E results between PK/850-K and PbCl2/NiCl2.
Figure 13. The Δ E results between PK/850-K and PbCl2/NiCl2.
Water 17 03015 g013
Water 17 03015 g014
Figure 14. Charge density results between 850-K and PbCl2 (a) and NiCl2 (b). Differential charge density results between 850-K and PbCl2 (c) and NiCl2 (d).
Figure 14. Charge density results between 850-K and PbCl2 (a) and NiCl2 (b). Differential charge density results between 850-K and PbCl2 (c) and NiCl2 (d).
Water 17 03015 g014
Table 1. XRF results of PK and modified kaolin (weight %).
Table 1. XRF results of PK and modified kaolin (weight %).
NameAl2O3SiO2TiO2K2OCaOFe2O3Loss on Ignition
PK38.4049.350.550.050.130.2011.32
750-K41.3249.562.241.392.052.381.06
850-K41.4849.882.451.042.142.540.47
950-K42.1250.062.321.341.462.460.24
Table 2. BET results of PK and modified kaolins.
Table 2. BET results of PK and modified kaolins.
NameSurface Area (m2/g)Pore Sizes (nm)Pore Volume (cm3/g)
PK1819.50.155
750-K2725.30.178
850-K3622.60.201
950-K3124.70.192
Table 3. Kinetic model parameters for Pb (II) and Ni (II) for four materials.
Table 3. Kinetic model parameters for Pb (II) and Ni (II) for four materials.
Pseudo-First-OrderPseudo-Second-Order
Heavy MetalSamplesK1/min−1qe/mg·g−1R2K2/(g·mg−1·min−1)qe/mg·g−1R2
Pb (II)PK0.38137.4840.8880.35950.3270.957
750-K0.36838.8470.9260.31952.7700.971
850-K0.63765.3390.9140.11775.3720.974
950-K0.54357.0780.8700.22052.8260.954
Ni (II)PK0.31431.7970.8460.36750.0590.959
750-K0.34836.9110.9010.33151.9160.965
850-K0.54360.6030.9040.14472.0460.974
950-K0.48153.3950.8510.25151.3070.959
Table 4. Isotherm model parameters for Pb (II) and Ni (II) for four materials.
Table 4. Isotherm model parameters for Pb (II) and Ni (II) for four materials.
LangmuirFreundlich
Heavy MetalSamplesKA/(L·mg−1)qe/mg·g−1R2KfnR2
Pb (II)PK0.02944.5260.9873.3791.8000.961
750-K0.03050.8250.9913.9091.8940.965
850-K0.07657.2780.9648.3223.0580.974
950-K0.05953.1040.9805.8892.5110.969
Ni (II)PK0.02643.5460.9861.7181.3800.967
750-K0.02849.6760.9892.6611.5470.952
850-K0.04755.1410.9943.6741.9020.969
950-K0.03851.3320.9702.6611.6790.939
Table 5. Changes in bond lengths and angles after the reaction between PbCl2/NiCl2 and PK/850-K in water.
Table 5. Changes in bond lengths and angles after the reaction between PbCl2/NiCl2 and PK/850-K in water.
Bond Length (Å)Change (Å)Change (Å)Bond Angle (°)Change (°)
Pb-Cl-1Pb-Cl-2Pb-Cl-1Pb-Cl-2--
PbCl2
(before reaction)		2.4882.488--99.82-
PbCl2
(after reaction with PK)		2.5422.574+0.054+0.08695.42−4.40
PbCl2
(after reaction with 850-K)		2.6752.688+0.187+0.20092.88−6.94
Ni-Cl−1Ni-Cl-2----
NiCl2
(before reaction)		2.0312.031--179.90-
NiCl2
(after reaction with PK)		2.0792.095+0.048+0.064177.35−2.55
NiCl2
(after reaction with 850-K)		2.1282.133+0.097+0.102174.77−5.13
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Yin, Z.; Yang, Y.; Wang, G.; Qi, R. Effective Treatment of Wastewater Containing Ni (II) and Pb (II) Using Modified Kaolin: Experimental and Simulation Study. Water 2025, 17, 3015. https://doi.org/10.3390/w17203015

AMA Style

Yin Z, Yang Y, Wang G, Qi R. Effective Treatment of Wastewater Containing Ni (II) and Pb (II) Using Modified Kaolin: Experimental and Simulation Study. Water. 2025; 17(20):3015. https://doi.org/10.3390/w17203015

Chicago/Turabian Style

Yin, Zhengtian, Yuxuan Yang, Guanjie Wang, and Renzhi Qi. 2025. "Effective Treatment of Wastewater Containing Ni (II) and Pb (II) Using Modified Kaolin: Experimental and Simulation Study" Water 17, no. 20: 3015. https://doi.org/10.3390/w17203015

APA Style

Yin, Z., Yang, Y., Wang, G., & Qi, R. (2025). Effective Treatment of Wastewater Containing Ni (II) and Pb (II) Using Modified Kaolin: Experimental and Simulation Study. Water, 17(20), 3015. https://doi.org/10.3390/w17203015

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop