A Hybrid Inorganic–Organic Schiff Base-Functionalised Porous Platform for the Remediation of WEEE Polluted Effluents

Abstract

An inorganic–organic hybrid nano-adsorbent was prepared by chemical immobilisation of an organic Schiff base Cu (II) ion receptor, DHB ((E)-N-(1-(2-hydroxy-6-methyl-4-oxo-4H-pyran-3-yl) ethylidene) benzohydrazide), a selective dehydroacetic acid-based chemosensor, onto a mesoporous silica support. In order to prepare the sorbent, the silylating agent was anchored onto the silica. During this procedure, 3-Chloropropyl trimethoxy silane (CPTS) was attached to the surface, increasing hydrophobicity. By immobilising DHB onto the CPTS platform, the silica surface was activated, and as a result the coordination chemistry of the Schiff base generated a hybrid adsorbent with the capability to rapidly sequestrate Cu (II) ions from wastewater, as an answer to combat growing Waste Electrical and Electronic Equipment (WEEE) contamination in water supplies, in the wake of a prolonged consumerism mentality and boom in cryptocurrency mining. The produced hybrid materials were characterised by FTIR, proximate and ultimate analysis, nitrogen physisorption, PXRD, SEM, and TEM. The parameters influencing the removal efficiency of the sorbent, including pH, initial metal ion concentration, contact time, and adsorbent dosage, were optimised to achieve enhanced removal efficiency. Under optimal conditions (pH 7.0, adsorbent dosage 3 mg, contact time of 70 min, and 25 °C), Cu (II) ions were quantitatively sequestered from the sample solution; 93.1% of Cu (II) was removed under these conditions. The adsorption was found to follow pseudo-second-order kinetics, and Langmuir model fitting affirmed the monolayer adsorption.

1. Introduction

Globally, the contamination of water resources by metal ions via different routes such as industrial discharge, mining activities, or landfill leachates is a serious health hazard and an environmental threat [1,2]. Metal ions are non-biodegradable, toxic, and tend to accumulate in the vital human organs [3]. Heavy metal ions such as Cu, Cr, Ni, Zn, Cd, and Hg are amongst the most harmful and abundant heavy metals due to their numerous industrial and domestic applications. Their demand is further increasing with the global push towards Net Zero targets, particularly in the electrification of transport and the growing use of batteries for decarbonising road travel [4,5]. As a result, the increasing levels of such heavy metals in water resources are a serious health risk to living beings and ecological systems [6].

In 2022, global electronic waste (e-waste) reached a record 62 million tonnes (7.8 kg per capita), representing an 82% increase compared to 2010. Projections indicate that this figure will rise by a further 32%, reaching approximately 82 million tonnes by 2030. Among the Earth’s five continents, excluding Antarctica, Asia stands as the primary contributor to e-waste generation, producing 30 million tonnes, followed by the Americas with 14 million tonnes, Europe with 13 million tonnes, Africa with 3.5 million tonnes, and Oceania with 0.707 million tonnes. Nowadays, e-waste is commonly referred to as Waste Electrical and Electronic Equipment (WEEE), a growing environmental concern. Despite its hazardous composition, only 22.3% of global WEEE is recycled in an environmentally sound manner, while the remainder is often discarded in landfills or informally processed. This mismanagement leads to the leaching of toxic heavy metal ions, making WEEE a significant contributor to water pollution [7].

Among the metals mentioned above, copper, one of the most prevalent transition metals in nature, is widely used across various industrial processes. Its broad applicability and frequent discharge make it a major hazardous contaminant commonly found in industrial wastewater [8]. In WEEE, Integrated Drive Electronics cables contain nearly 4.4 g of Cu/dry kg [9]. A permissible limit for Cu of 1.5 mg/L has been set to be acceptable by the World Health Organisation (WHO) in drinking water [10]. However, levels of Cu in freshwater reach up to 5.1 mg/L and 133 mg/L in Delhi/India [11] and the United Kingdom [8], respectively.

An efficient solution to this widespread water pollution problem requires capable decontamination and purification technologies, in addition to establishing a discharge limit on industrial authorities [12,13]. Several analytical separation techniques, such as membrane filtration [14,15], solvent extraction [16,17], coagulation [18], exchange resins [19], and adsorption and precipitation [20,21], have been reported by various researchers and are being employed for trace analytes in different matrices. Solid phase extraction (SPE) methods are most commonly used to tackle problems during trace analysis [22,23]. SPE applications are of great interest to scientists as adsorbents have high capacities. Amongst these, an inorganic matrix functionalised with metal ion chelating ligands serves as a low-cost adsorbent. For instance, the surface of silica gel has previously been chemically altered using a carbothioamide Schiff base; this was subsequently employed to remove Cr (III) ions from wastewater samples [24,25,26]. Zhang and co-authors orchestrated the fabrication of an innovative inorganic–organic chemosensing material, denoted by MS-NSP. This intricate material was synthesised through the strategic immobilisation of the bis-Schiff base fluorophore onto the intricate channel topography of an SBA-15 mesoporous silica matrix for the remediation of Pb (II) ions [25]. This coupling was achieved via the mediation of a quaternary ammonium linker, which served as the bridging entity, facilitating the connection between the molecular components [27]. Maqinana and co-authors have also immobilised chelating agents on mesoporous silicas (MCM-41, SBA-15) for heavy metal adsorption (Cd (II), Pb (II), and Cr (VI)); they confirmed pseudo-second-order kinetics and chemisorption behaviour [28].

Current adsorption materials are typically broad-spectrum, removing multiple metal ions simultaneously but with limited selectivity, essentially a “jack of all trades, master of none,” resulting in reduced efficiency for specific ions. To address this limitation, functionalised inorganic–organic hybrid materials have emerged as promising candidates, enabling the selective adsorption of specific metal ion species in aqueous solutions through tailored surface chemistry and affinity mechanisms. These hybrid materials are employed for their strong binding affinities and high adsorption capacities toward heavy metal ions [24,29]. In addition to high adsorption capabilities, they have (i) a large surface area; (ii) thermal, chemical and mechanical stabilities; (iii) high porosity; and (iv) ease of separation from aqueous solutions [30,31,32].

Silica gel (SG) is a relatively inexpensive and highly effective option to serve as an inorganic support in fields such as adsorbents and heterogeneous catalysis. SG is an inorganic amorphous material consisting of siloxane groups (Si-O-Si) with silanol groups (Si-OH) on the surface, widely used as an inorganic backing for the production of new materials [33,34]. The direct modification of organic molecules onto inert inorganic matrices is difficult. However, due to the presence of active hydrogen atoms of the silanol groups of SG, it can react with organosilyl groups to introduce an organic functionality to the porous silica support [26]. The immobilisation of chelating agents on SG with donor atoms can be achieved by chemical bonding between chloro-modified SG phases or by physisorption [35].

The present work aims to immobilise a Schiff base derivative, DHB ((E)-N-(1-(2-hydroxy-6-methyl-4-oxo-4H-pyran-3-yl) ethylidene) benzohydrazide) onto the silica surface for the production of a hybrid inorganic–organic chemosensor to recover Cu (II) ions from contaminated wastewater. The coordination chemistry of Schiff bases is well known; however, there is a limited number of reports on the use of Schiff base-functionalised hybrid silica materials for wastewater remediation [20,36]. The tendency of the functionalised hybrid material to extract metal ions is attributable to the coordination ability of the grafted organic ligands [29,37]. Mostly, the grafted ligands have donor atoms such as nitrogen, oxygen, or sulphur that impart the chelating effect to the adsorbent. The driving mechanism of binding is simply the complexation of the metal ion with donor heteroatoms that convey distinctive extraction properties to the hybrid adsorbent. The immobilisation of a Schiff base on SG offers an inexpensive and effective alternative sorbent, which has the capability to be reproduced at scale and augmented to uptake a variety of metal ions, dramatically diversifying its applications.

2. Materials and Methods

2.1. Chemicals

Ethyl benzoate, hydrazine hydrate, and dehydroacetic acid (DHA) were purchased from Sigma Aldrich (St Louis, MO, USA). Silica gel (SG) (0.060–0.2 mm, 70–230 mesh) and CuSO₄ (Copper(II) sulphate, anhydrous, Reagent Grade) was purchased from Alfa Aesar (Heysham, UK). The solvents dry toluene, ethanol, and acetone were purchased from Fisher Scientific, United Kingdom. The chemicals and reagents were used as supplied without any further purification.

2.2. Characterisation

Ultimate analysis (CHN) of the silica gel before and after modification was carried out using ~20 mg of sample in a LECO 628 CHN Combustion analyser (Stockport, UK). Fourier Transform Infrared (FTIR) Spectroscopy spectra were acquired using a Thermo Scientific Nicolet iS5 spectrometer (Loughborough, UK) with a PIKE MIRacle Single reflection horizontal ATR accessory. A Micromeritics TriStar Porosimeter (Tewkesbury, UK) was used to perform nitrogen physisorption studies to assess the BET surface area of the samples. Prior to analysis, the samples were degassed via a nitrogen capillary feed placed into the centre of the quartz tube, where it was heated at a temperature of 110 °C in a thermal well for 3 h prior to nitrogen adsorption–desorption experiments. The optical characteristics of the metal ion solutions were measured using a Thermo Scientific Evolution 201 UV-vis spectrophotometer (Jenway, Staffordshire, UK, Model 7315). The pH measurements were carried out using a benchtop Cole Parmer Digital pH meter (St Neots, UK). Thermogravimetric analysis (TGA) was conducted using a LECO 701 instrument (Stockport, UK) at a scale of ~1 g, under parallel conditions. The shape, size, and morphology of the samples were determined using transmission electron microscopy (TEM) (Hitachi, Tokyo, Japan, Model H-7500). Scanning Electron Microscopy (SEM) was conducted using a Zeiss EVO 60 instrument (Cambridge, UK) under a vacuum of 10⁻² Pa and an electron acceleration voltage of 20 kV. Powder X-ray diffraction (PXRD) analysis was carried out using a PANalytical Empyrean series 2 diffractometer (Malvern, UK) equipped with monochromated Cu K_α radiation (λ = 0.1542 nm). The diffractograms were analysed using HighScore Plus software (version 2013, PANalytical B.V., Almelo, The Netherlands).

2.3. Synthesis of Schiff’s Base DHB

According to our previously reported procedure [9], the Cu (II) chemosensing Schiff base DHB ((E)-N-(1-(2-hydroxy-6-methyl-4-oxo-4H-pyran-3-yl) ethylidene) benzohydrazide) was prepared using a one-pot condensation reaction between benzohydrazide and DHA. After mixing the ethanolic solution of DHA with benzohydrazide at 300 rpm for 24 h at room temperature using a magnetic stirrer, the final product DHB was obtained. The product was collected, filtered, and dried overnight at room temperature in a vacuum desiccator, resulting in a yellow-hued material.

The immobilisation of the Schiff base DHB onto a silica surface can be achieved using two distinct methods. In the first method, a direct reaction of the SG with the Schiff base DHB was carried out without modifying the silica surface with CPTS. In the second method, the immobilisation of DHB was conducted by three steps: (1) activation of the silica gel; (2) functionalisation with CPTS; and (3) attachment with the Schiff base moiety. It was found that without initially activating the silica gel and functionalisation with CPTS, immobilisation does not occur.

2.4. Preparation of CPTS Modified Silica Gel (SG-Cl)

The SG was activated by heating at 110 °C for 24 h under a nitrogen flow to remove the moisture from the pore network. SG-Cl was synthesised by mixing 4.0 mL of CPTS and 4.0 g of dried SG in 50 mL of dry toluene, followed by stirring at 300 rpm and refluxing at 110 °C under a nitrogen atmosphere for 72 h. The subsequent SG-Cl was filtered, washed thrice with dry toluene and dried under vacuo at room temperature for several hours in a desiccator. Elemental analysis showed a carbon content of 7.00 wt.% and a hydrogen content of 1.00 wt.%, suggesting that the CPTS organic species had successfully impregnated the SG (

Table 1. Physicochemical properties of bare and modified silica gels.

Sample	C (wt.%)	H (wt.%)	N (wt.%)	Surface Area (m2 g−1) **	Pore vol. (cm3 g−1)	Pore Diameter (nm)
Bare SG *	0.13	-	-	463.88	0.70	4.96
SG-Cl	7.00	1.00	-	311.52	0.40	4.60
SG-DHB	21.44	1.72	2.68	262.76	0.34	4.72

Notes: * The silica gel was activated through drying at 110 °C. ** Surface area data was acquired by applying the BET isotherm.

).

2.5. Immobilisation of DHB on the Silica Gel (SG-DHB)

A sample of 1.0 g SG-Cl was reacted with 0.5 g of DHB in 10 mL of dry toluene. The reaction mixture was stirred under reflux and a nitrogen atmosphere for 72 h (Figure 1). Following the reaction, a yellow solid was recovered, filtered, and washed with toluene and ethanol (50 mL), then dried under vacuo at room temperature for 4 h. Elemental analysis showed that the resulting material contains 21.44 wt.% C, 1.72 wt.% H, and 2.68 wt.% N, confirming the presence of DHB on the silica surface (Table 1).

2.6. Adsorption Study Methodology

The preliminary adsorption investigation involved adding a specific amount of SG-DHB adsorbent to 10 mL of a specific initial concentration of Cu (II) solution prepared in deionised water. The mixture was shaken in a temperature-controlled shaker (Remi RS-12) at 25 ± 2 °C, followed by stirring at 300 rpm. A total of 0.2 M H₂SO₄ and 0.2 M NaOH was used to adjust the pH of the solutions between 2.0 and 12.0. During the adsorption experiment, samples were collected every 5 min over the total duration of 80 min and filtered by centrifugation using a Thermo Kendro Megafuge X1 (Staffordshire, UK) at 6000 rpm for 5 min. The Cu (II) concentration in the supernatant was measured in triplicate using a UV-Vis spectrophotometer (Jenway, Model 7315) at 625 nm. Concentrations were determined from a calibration curve prepared with CuSO₄ standard solutions of 5, 10, 20, 40, and 80 mg/L. The adsorption capacity (in mg/g) and percentage removal of Cu (II) was calculated using Equation (1) and Equation (2), respectively:

$$q={\displaystyle \frac{\left(C_0-C_e\right)V}{m}}$$

(1)

$$\%Removal={\displaystyle \frac{C_0-C_e}{C_0}}\times 100\%$$

(2)

where $C_0$ and $C_e$ are the initial and equilibrium concentrations of the Cu (II) ions (in mg/L), respectively, $V$ is the volume of aqueous solutions (in L), and $m$ is the mass of the adsorbent (in g). To optimise the adsorption performance, various operational parameters such as pH, adsorbent dosage, and contact time were investigated.

The effect of solution pH on adsorption was examined across a pH range of 2–12 while maintaining constant parameters: contact time of 80 min, adsorbent dosage of 0.3 g/L, and initial Cu (II) concentration of 6.36 mg/L. To assess the influence of initial concentration, Cu (II) solutions of 5, 10, 20, 40, and 80 mg L⁻¹ were tested under controlled conditions (pH 7, adsorbent dosage 0.3 g/L, contact time 80 min). The effect of adsorbent dosage was evaluated in the range of 0.1–0.6 g/L using a Cu (II) solution of 20 mg/L at pH 7 and 80 min contact time. Kinetic studies were performed by varying contact time (up to 80 min) for 5 mg of adsorbent in 10 mL of 20 mg/L Cu (II) solution at pH 7.

3. Results and Discussion

3.1. Characterisation of Adsorbent SG-DHB

Figure 2 shows FTIR spectra of the parent silica support and subsequent functionalized species. The bare silica was found to readily uptake the primary amine moieties and Schiff base derivatives. The bands around 1102 cm⁻¹ and 807 cm⁻¹ are attributed to the different vibration modes of silanol and siloxane groups in the SG matrix. The FT-IR spectrum of bare silica gel (SG) has typical Si-O-Si, siloxane, stretching vibrations of about 800 cm⁻¹ and 1090 cm⁻¹. After CPTS modification (SG-Cl), the bands of the silica frameworks still exist, but there are new bond responses in the 2850–2950 cm⁻¹ region that represent aliphatic C-H stretching. The free DHB chemosensor has characteristic organic characteristics, with azomethine (C=N) being prominent at about 1610–1630 cm⁻¹, aromatic C=C to confirm the formation of a Schiff base, and C-O bonds between 1250 and 1280 cm⁻¹. The presence of these bands is related to the presence of the Schiff base, together with the typical Si-O-Si vibrations in the DHB-modified silica gel (SG-DHB), confirming the immobilisation of DHB onto the silica surface without any perturbation of the silica structure. It should be pointed out that the stretching bands due to various organic groups in the functionalised SG were quite weak, and hence not very clear, due to the influence from the strong background vibrations of the SG support [20].

3.2. Elemental Analyses

As confirmed by the CHN analysis (Table 1), DHB was successfully immobilised onto the SG-Cl to produce SG-DHB material. The surface silanol groups readily react with CPTS to yield a 3-chloropropyl-modified silica (SG-Cl) surface. The wt.% of carbon, hydrogen, and nitrogen for bare SG, SG-Cl, and SG-DHB are listed in Table 1 and reflect the progressive functionalisation of the silica support. Bare SG showed negligible levels of carbon, nitrogen, or hydrogen. However, considerable amounts were observed for the SG-Cl and SG-DHB, which confirmed the successful covalent attachment of CPTS and DHB, respectively. CHN analysis proves that the nitrogen-containing functional groups have been incorporated into the porous network after the DHB grafting process. Table 1 shows that after functionalization there is a reduction in available surface area compared with the bare SG (463.88 m² g⁻¹ vs. 262.76 m² g⁻¹), as well as a reduction in available pore volume (0.70 cm³ g⁻¹ vs. 0.34 cm³ g⁻¹), which can be explained by pore blockage by bulky organic molecules. Overall, the physical pore diameter does not vary widely between the bare SG and SG-DHB, meaning that only a chemical grafting has taken place, and no alteration to the silica support has occurred.

3.3. Porous Structure Analysis

The changes in surface area, pore volume, and pore size of SG-Cl and SG-DHB by the introduction of CPTS and DHB are shown in Table 1. Nitrogen adsorption–desorption isotherms for SG and its functionalised derivatives are displayed in Figure 3. According to IUPAC classification, all samples illustrated type IV isotherms with a hysteresis loop at P/P₀ > 0.86, representative of a mesoporous structure. The functionalisation and subsequent immobilisation process filled the pores of the SG matrix, as can be seen by reduced pore volumes for SG-Cl and SG-DHB.

3.4. TGA Analyses

The FTIR and elemental analysis results are supported by TGA curves (Figure 4). Bare activated SG showed a single mass loss of 6.63% from 32 °C to 87 °C, which is accredited to the loss of physically adsorbed water. However, SG-Cl exhibited a first mass loss stage of 4.65% from 32 °C to 100 °C assigned to physisorbed water, followed by a 7.04% loss from 283 to 337 °C due to the decomposition of grafted organic groups. For SG-DHB, a mass loss of 0.79% is evident from 32 °C to 350 °C, followed by second mass loss stage of 91.90% from 350 °C to 500 °C due to the decomposition of Schiff base DHB immobilised on the surface.

Additional weight loss is attributed to the condensation of silanol groups into siloxane bonds [38]. At 516 °C, approximately 94% SG-DHB degraded, leaving 6% residual mass corresponding to the silica support. Based on residual weights, the estimated loading of CPTS and DHB onto the silica was approximately 87% and 95%, respectively.

3.5. PXRD Analyses

The PXRD diffractograms of bare SG, SG-Cl, and SG-DHB are shown in Figure 5. All samples show a broad diffraction peak ~23°, which indicates the amorphous structure of the silica support. In the case of SG-DHB, the appearance of sharper, well-defined peaks suggests the successful incorporation of DHB, both on the surface and potentially within the pore network, as indicated by the reduced pore volume [36,39]. These peaks reduce in intensity substantially following the Cu uptake experiment and subsequent drying; the structure appears to be similar to the bare SG. This observation indicates that during adsorption, the Cu remained in its ionic form without forming crystalline aggregates, as no additional peaks at higher 2θ values were detected.

3.6. Electron Microscopy

SEM and TEM were performed on all samples to examine the surface morphology and particle size of the functionalised chemosensor, respectively. The SEM image of bare SG (Figure 6a) shows a smooth and uniform surface. Following the modification of SG with CPTS and subsequent immobilisation of DHB, the silica surface becomes notably rougher (Figure 6b,c). The CPTS- and DHB-modified SG illustrate the presence of organic components on the surface, making the overall surface appear disturbed due to pore openings of the mesoporous structure [32,36]. Furthermore, the EDX data for SG, SG-Cl, and SG-DHB, shown in the Supplementary Materials, Figures S1–S4, further confirms elemental changes associated with each functionalisation step.

The EDX data shown in Figure S1 confirms the presence of Si, S, N, C, and O, supporting the successful functionalisation of the silica surface with organic moieties. It should be noted that a portion of the carbon signal originates from a thin (~10 nm) graphite coating applied to enhance SEM image contrast. The EDX data, along with curves and mapping of samples SG, SG-Cl, SG-DHB, SG-DHB after Cu (II) adsorption, and SG after uptake, are shown in Figures S1–S5. SEM analysis of the SG-DHB after adsorption of Cu (II) ions has also been depicted in Figure 6d. The accompanying EDX pattern of SG-DHB after adsorption shows evidence of Cu (II) on the surface (Figure S1).

Adsorption experiments using unmodified SG showed no evidence of Cu (II) uptake or surface impregnation (Figure S5), highlighting the essential role of DHB functionalisation in metal ion capture. The particle size analysis of the inorganic–organic hybrid material was carried out using both TEM and Dynamic Light Scattering (DLS), as shown in Figure 7. The TEM images (Figure 6e,f) revealed the size of particles to be ~35 nm, as indicated by a yellow double-headed arrow in Figure 6e. However, for DLS measurements, the particles were found to be of a much lower size, with the mean particle size closer to 13.96 ± 2.27 nm (Figure 7). There were a number of outliers, which were closer to 21 nm, suggesting that larger particles, coalesced single particles, were present. For the TEM images, the larger particle sizing is due to the method of sample preparation for a TEM grid, as after particles are agitated into a suspension they are drop cast onto a grid. The solvent is then evaporated, which leads to the coalescence of the functionalized silica particles, which has produced ensembles (Figure 6e). However, for DLS measurements, the sample is mixed before analysis, which provides a shearing force that disperses the silica particles into the solution. It is reasonable to assume that the DLS measurements map more closely to the true size of the particles that would operate the Cu (II) uptake process, due to the mixing.

4. Adsorption Studies

4.1. pH Optimisation

The solution pH is a critical parameter in adsorption processes, as it influences both the speciation of metal ions and the surface charge of the adsorbent. The effect of the pH of the solution on adsorption was investigated for a pH range of 2 to 12 (Figure 8A). At low pH, the adsorption capacity decreased due to the increased competition of hydronium ions with Cu (II) ions for active sites. However, the adsorption capacity increased with increased pH and decreased concentration of hydronium ions until reaching a neutral range, i.e., pH = 6 to 7, where the adsorption maximum of 85.9% was achieved, using a 3 mg dose over a 1 h period. At a higher pH, the Cu (II) reacted with hydroxide ions to form blue precipitates of copper hydroxide, which hindered the adsorption. Therefore, a neutral pH was selected as the optimal condition for all subsequent experiments.

4.2. Effect of Initial Concentration

Figure 8B shows the dependence of adsorption performance on the initial concentration of Cu (II). As metal ion concentration increased, the adsorption rate increase, followed by a subsequent drop, indicating saturation of the adsorbent’s active sites. At lower concentrations, a higher proportion of adsorption sites remained available relative to the number of Cu (II) ions, leading to more efficient uptake. A maximum removal efficiency of 71% was obtained at 20 mg/L Cu (II), using a dose of 2 mg at pH 7.

4.3. Effect of Adsorbent Dosage

The optimum amount of adsorbent was investigated in the range of 1–6 mg against 20 mg/L of Cu (II) ions at pH 7, room temperature, and a contact time of 80 min. The results, shown in Figure 8C, indicate a sharp increase in removal efficiency from 69.99% to 87.99% as the dosage increased from 1 mg to 3 mg, attributed to the increased availability of active adsorption sites. After 3 mg, the removal efficiency was found to be constant. Hence, a 3 mg adsorbent dosage was fixed as the optimum dosage for the extraction process.

4.4. Effect of Contact Time

The adsorption of Cu (II) as a function of contact time is illustrated in Figure 8D. The results reveal rapid adsorption kinetics. The initial yellow adsorbent turned greenish shortly after contact with the Cu (II) solution. The adsorption rate increased significantly during the first 40 min and then reached equilibrium between 70 and 80 min. Based on this equilibrium plateau, a contact time of 70 min was selected as the optimal duration for all subsequent adsorption experiments.

4.5. Kinetic Studies

As adsorption is a physicochemical process that involves mass transfer from the liquid to the surface of a solid adsorbent, the kinetics of Cu (II) uptake were studied to understand the adsorption mechanisms. The initial concentration of the Cu (II) solution was maintained at 20 mg/L. The experimental data was fitted to pseudo-first-order and pseudo-second-order models, as described in Equations (3) and (4), respectively.

$$q_t=q_e\left(1-e^{-k_{1}t}\right)$$

(3)

$$q_t={\displaystyle \frac{{q_e}^2{k}_{2}t}{1+k_2{q}_{eq}t}}$$

(4)

where $k_1$ and $k_2$ are the adsorption rate constants of the first (min⁻¹) and the second-order kinetic models (mg g⁻¹.min⁻¹), respectively, and $q_t$ and $q_e$ are the adsorption capacity, time = t and time = ∞ (mg/L), respectively. The best-fitted results of the kinetics models are shown in Figure 9, while the corresponding parameters are listed in

Table 2. The parameters of the kinetic models.

First Order Kinetics			Second Order Kinetics			Experimental Equilibrium Adsorption Capacity
${\mathit{q}}_{\mathit{e}}$ (mg g−1)	k1 (min−1)	R2	${\mathit{q}}_{\mathit{e}}$ (mg g−1)	k2 (g mg−1 min−1)	R2	${\mathit{q}}_{\mathit{e},\mathit{e}\mathit{x}\mathit{p}}$ (mg g−1)
18.5	0.075	0.9245	21.7	0.004	0.9829	16.14

. The experimentally determined equilibrium adsorption capacity was q_e,exp = 19.14 mg g⁻¹ This value was compared with the equilibrium capacities predicted by the kinetic models (Table 2), where q_e,PFO = 18.5 mg g⁻¹ for the PFO model and q_e,PSO = 21.7 mg g⁻¹ for the PSO model. The data show that the adsorption process follows the pseudo-second-order kinetics model, as confirmed by the high R² value of 0.9829. This suggests chemisorption or strong interactions between the Cu (II) ions and the functional groups on the SG-DHB adsorbent surface [40,41].

To identify the rate-limiting step governing the adsorption process, a multi-mechanism adsorption kinetic model was applied, as described by Equation (5) [42].

$${\displaystyle \frac{1}{\alpha +\frac{\alpha m{q}_e^2}{V{C}_0{q}_m}-2}}\left\{\left[1-\alpha +{\displaystyle \frac{\alpha m{q}_e}{V{C}_0}}\left(1-{\displaystyle \frac{q_e}{q_m}}\right)\right]\ln \left(1-{\displaystyle \frac{q}{q_e}}\right)+\left(1-{\displaystyle \frac{\alpha m{q}_e}{V{C}_0}}\right)\mathrm{l}\mathrm{n}\left[1+\left(1-\alpha -{\displaystyle \frac{\alpha m{q}_e^2}{V{C}_0{q}_m}}\right){\displaystyle \frac{q}{q_e}}\right]\right\}=kt$$

(5)

Here, $\alpha$ is a dimensionless parameter, and $k$ is the apparent rate constant. The value of $\alpha$ indicates the rate-limiting step: values near 0 suggest intraparticle diffusion control, values near 1 indicate film diffusion dominance, and values around 0.5 imply that either chemisorption or physisorption governs the process [42]. For kinetic data ($q_t\mathrm{v}\mathrm{s}.\mathrm{t}$), $\alpha$ and $k$ were estimated using the “Solver” add-in in Microsoft Excel. The results showed that the values of $\alpha$ and $k$ for the Cu (II) adsorption onto SG-DHB were 0.019 and 0.014 min⁻¹, respectively. The relatively low α values indicate that intraparticle diffusion is the rate-limiting step, with mass transfer resistance within the biochar pores controlling the adsorption process. This could be due to bulky hydration and strong interaction of Cu with water, which makes its hydration radius large, hence giving a small intraparticle diffusion coefficient [43].

4.6. Adsorption Isotherms

The adsorption isotherms are crucial for understanding solute–adsorbent interactions, evaluating adsorption efficiency, and examining the adsorption mechanism. The adsorption isotherms for Cu (II) onto SG-DHB are shown in Figure 10, indicating the material’s high affinity for Cu (II) across a broad concentration range. To examine the adsorption behaviour, the experimental data were fitted to two widely used adsorption isotherm models: Langmuir and the Freundlich models. The Langmuir model assumes monolayer adsorption onto a homogeneous surface, while the Freundlich model describes adsorption on heterogeneous surfaces, where sites have varying affinities for the adsorbate, and multilayer adsorption is possible [44]. The Langmuir isotherm model is presented by Equation (6) [45]:

$$q_e={\displaystyle \frac{q_{max}{K}_L{C}_e}{1+K_L{C}_e}}$$

(6)

The Freundlich isotherm model is illustrated by Equation (7) [46].

$$q_e=K_F{C}_e^n$$

(7)

where q_e is the amount of solute adsorbed at equilibrium (mg/g), $q_{max}$ is the maximum adsorption capacity corresponding to monolayer coverage (mg/g), C_e is the equilibrium concentration of metal ions in solution (mg/L), ${\mathrm{K}}_{\mathrm{L}}$ is the Langmuir adsorption constant (L/mg), $K_F$ is the Freundlich adsorption constant (L/mg), and n is the Freundlich exponent related to adsorption intensity (dimensionless).

The Langmuir and Freundlich isotherm parameters for Cu (II) adsorption on SG-DHB are shown in

Table 3. The Langmuir and Freundlich isotherm parameters for Cu (II) adsorption on SG-DHB.

Langmuir			Freundlich
qmax (mg g−1)	kL (L/mg)	R2	n	kF (L/mg)	R2
422.24	0.0184	0.9603	1.065	7.394	0.9433

. In this study, the adsorption curve did not reach a clear plateau within the investigated equilibrium concentration range, indicating that saturation was not achieved. Therefore, the experimental data do not allow for a direct determination of Langmuir q_max, and should be interpreted as a model-extrapolated maximum capacity rather than an experimentally attained saturation value.

5. Conclusions

In this study, a Schiff base-functionalised silica gel (SG-DHB) was successfully synthesised and applied for the adsorption of Cu (II) ions from aqueous solutions. Elemental analysis (CHN) and thermogravimetric measurements confirmed the effective grafting of organic functionalities onto the silica surface. TEM analysis revealed the shape of particles and the tendency for the modified silica particles to coalesce, exhibiting as a result a slightly higher particle size than a comparative DLS study. Due to a mixing process prior to analysis, the dispersion of the particles in solution demonstrated that the particles have a hydrodynamic diameter of 13.96 ± 2.27 nm. Batch adsorption experiments demonstrated that the adsorption kinetics followed a pseudo-second-order model, indicating that chemisorption governs the uptake process. Equilibrium data were well-described by the Langmuir isotherm model, confirming monolayer adsorption behaviour on a homogeneous surface. The maximum adsorption capacity (q_m) of SG-DHB toward Cu (II) ions was determined to be 21.45 mg g⁻¹, accompanied by a high percentage removal efficiency at neutral pH, even in the presence of competing metal ions.

Overall, the results indicate that SG-DHB is a highly efficient inorganic–organic hybrid nanomaterial with strong potential for practical wastewater treatment applications, particularly for the rapid removal of Cu (II) ions originating from industrial effluents and WEEE leachates. The findings also support the feasibility of employing this material in immobilised configurations, such as coatings on pipes or tanks, for continuous heavy-metal remediation.