Application of DFT and Experimental Tests for the Study of Compost Formation Between Chitosan-1,3-dichloroketone with Uses for the Removal of Heavy Metals in Wastewater

Abstract

The environment presently contains greater amounts of heavy metals due to human activities, causing toxicity, mutagenicity, and carcinogenicity. This study evaluated a chitosan (CS) composite material combined with 1,3-dichlorocetone to extract heavy metals from affected waters, integrating experimental and computational analyses. The synthesis of chitosan, obtained from shrimp waste chitin, reached a yield of 85%. FTIR analysis confirmed key functional groups (NH₂ and OH), and XRD showed high crystallinity with peaks at 2θ = 8° and 20°. The physicochemical properties evaluated included a moisture content of 7.3%, ash content of 2.4%, and a deacetylation degree of 73%, consistent with commercial standards. Chitosan exhibited significant solubility in 1.5% acetic acid, moderate solubility in water, and insolubility in NaOH, demonstrating its versatility for environmental applications. In adsorption tests, heavy metal concentrations were reduced by CS derivatives, with Cr and Pb dropping to 0.03 mg/L, and Cu and Zn to less than 0.05 mg/L. CS cross-linked with 1,3-dichlorocetone proved the most efficient, outperforming other derivatives such as glutaraldehyde and epichlorohydrin. Computational analysis evaluated key molecular interactions using DFT and the B3LYP/LANLD2Z method. The band gap energies (HOMO–LUMO) decreased to 0.09753 eV for Zn and 0.01485 eV for Pb, indicating high affinity, while Cd showed lower interaction (0.11076 eV). The total dipole moment increased remarkably for Zn (14.693 Debye) and Pb (7.449 Debye), in contrast to Cd (4.515 Debye). Other descriptors, such as chemical hardness (η), reflected a higher reactivity for Zn (0.04877 eV) and Pb (0.00743 eV), which favors adsorption. The correlation between experimental and computational results validates the efficiency and selectivity of CS/1,3-dichlorocetone for removing heavy metals, especially Pb and Zn. This material stands out for its adsorbent capacity, sustainability, and economic viability, positioning it as a promising solution for wastewater remediation.

1. Introduction

Increasing industrialization and the careless release of heavy metals alongside pollutants have made environmental pollution a serious public health concern. In recent years, this problem has been significantly aggravated by the discharge of inorganic and organic waste into water bodies, which has resulted in a significant amount of water contamination. The increasing spread of pollution in aquatic ecosystems poses a serious threat to human health and the diversity of life forms [1]. Pollutants represent significant sources of toxicity and have an elevated likelihood of food chain bioaccumulation; as heavy metals and other pollutants enter water bodies and are distributed throughout ecosystems, they are absorbed by aquatic organisms and subsequently transmitted to different levels of the food chain. This gradual accumulation of toxins in organisms along the food chain can harm the health of animals and humans who consume these contaminated products [2,3]. Multiple methods and techniques have been developed to facilitate the elimination of metals from wastewater, encompassing membrane filtration [4], reverse osmosis [5], electrochemical separation [6], pulsed laser deposition (PLD) [7,8,9], coagulation [10], ion exchange [11], electrochemical deposition [12], and pulsed laser ablation [13,14]. Nevertheless, these methods frequently have cost and efficiency constraints, especially when dealing with low concentrations of pollutant effluents. In this scenario, adsorption shines as an innovative and high-impact alternative, consolidating itself as one of the most efficient, economical, and preferred methods to free aquatic ecosystems from toxic metals [15,16,17].

Chitosan (CS) has attracted considerable attention in the field of heavy metal removal due to its outstanding ability to bind heavy metals and its cost-effectiveness, which makes it a highly promising option [18]. Chitin, a biopolymer that is abundant in nature, may be partially deacetylated to produce the polymer CS. Chitin, the second most abundant natural polymer after cellulose, is found mainly in the shells of crustaceans such as shrimp and crabs, as well as in certain species of fungi, which act as its richest and most versatile sources [19]. CS stands out for being biocompatible and biodegradable, in addition to having a molecular structure enriched with numerous hydroxyl (OH) and amino (NH2) functional groups, which enhance its versatility and applications. These properties allow it to form coordination bonds with heavy metals, giving it an outstanding adsorption capacity [20,21]. Due to these characteristics, CS has been investigated as a substitute adsorbent compound for treating wastewater. Its unique qualities, include a high adsorption capacity, low level of toxicity, biodegradable properties, and biological compatibility [22], have made it possible for it to be widely applied in different areas, such as chemistry [23], pharmacy [24], medicine, and environmental science [25,26]. In addition, successful attempts have been reported to treat various common wastewater heavy metal ions employing CS and their derivatives. However, CS faces some challenges that limit its usage in various applications, such as low mechanical strength, low acid stability, and low thermal stability. In order to overcome the existing limitations and improve their effectiveness in wastewater treatment, researchers have carried out physical and chemical modifications. These adaptations have significantly increased the adsorption capacity of metal ions such as As(III), As(V) [27,28], Pb(II) [29,30], Cu(II) [31,32], and Cd(II) [33,34], achieving superior performance in environmental applications.

Quantum mechanical methods have proven to be successful in their application. A robust and efficient approach to describing metallic systems is DFT. In order to examine the adsorption process and the interactions between heavy metals, recent research has integrated DFT techniques with experimental methods, as demonstrated in the study by Vieira et al. (2019), which explored the synthesis of chitosan-N-lauroyl (CL) and its adsorption capacity for Pb(II) and Cu(II) ions in aqueous solutions [35,36]. Applying an experimental and DFT approach, Adsorption was revealed as an endothermic and spontaneous process, in which the carbonyl, hydroxyl, and amide groups acted as key players, facilitating the stabilization of the complexes between the metal and the adsorbent, highlighting their importance in the molecular interaction [37]. In another study, Ezzat et al. (2020) demonstrated significant selectivity and binding affinity toward Pb and Cu when using DFT to evaluate the correlation between CS with heavy metals such as Pb, Cd, As, Cu, Ni, and Fe. The energy gap values revealed that CS had a higher selectivity toward these metals [38]. Using DFT, Menazea et al. (2020) investigated the relationship between chitosan/graphene oxide (CS/GO) and heavy metals and found that the CS/GO–heavy metal contact was more selective than the CS–heavy metal interaction [39]. Finally, Mardani et al. (2020) studied four Schiff base-modified CS composites for copper and nickel ion adsorption. The modification of CS significantly increased its adsorption capacity, with the CS-A compound standing out as the most efficient for adsorbing Cu²⁺ and Ni²⁺ [40].

The present investigation aimed to create and analyze molecular models and experimental tests of CS and the CS/1,3-dichlorocetone system about heavy hydrated metals, namely zinc (Zn), cadmium (Cd), and lead (Pb) (see Figure 1), and to correlate them with experiments. The investigation was carried out using the DFT level B3LYP/LANL2DZ. This methodology facilitates an exact description of the electronic and geometrical characteristics of the examined systems. The evaluation of the geometrical stability of the complexes consisting of CS and metals in their hydrated state and a thorough characterization of the system’s electronic properties, such as charge distribution, binding energies, and density, were carried out by email. In this context, the interactions between the functional groups present in CS and the metal ions were analyzed in depth. Aspects including the type of coordination bonds and the impact of 1,3-dichlorocetone on the overall structure of the system were given special consideration. The conclusions of the analysis offer a strong foundation for future developments in the creation of CS-based materials, seeking to improve their properties and expand their potential in both industrial and environmental applications.

In the field of computational chemistry, the search for the most reliable and efficient predictive method is essential for the study of molecular properties and chemical processes. Theoretical approaches such as B3LYP/LANLD2Z, M06-2x/LANLD2Z, and M05-2x/LANLD2Z have been employed to balance accuracy and computational expense. These density functional theory (DFT)-based methods were carefully chosen to produce precise findings when describing the electrical characteristics of molecules. Notably, the B3LYP/LANLD2Z method offers a good balance between the reliability of the results and the computational resources required, a common choice for studying electronic structures.

2. Materials and Methods

2.1. Computational Details

CS is presented as an efficient instrument for removing heavy metals from aquatic mediums, and its combination with 1,3-dichlorocetone offers even more advantages in terms of heavy metal adsorption. Calculations were performed using GAUSSIAN 16 software [41], employing DFT theory at the B3LYP level [42,43] along the LANLD2Z basis set to optimize the structures and calculate the electronic properties. Simulated structures of CS and CS/1,3-dichlorocetone adsorption interactions with hydrated heavy metals composed of Pb, Cd, and Zn have been analyzed, determining local minimum energy values. The computational simulations allowed the calculation of HOMO–LUMO band gap energies and the analyzed structures’ total dipole moment (TDM). In addition, the boundary molecular electrostatic potential (MPEM) was calculated for all structures, providing a complete view of the charge distribution in the molecules.

2.2. Experimental Part

2.2.1. Synthesis of Shrimp Chitosan

CS was produced from chitin obtained from shrimp waste. For this purpose, 3 g of chitin was dissolved in 150 mL of a 1.5% acetic acid solution, using a round bottom flask. The mixture was kept under constant agitation at room temperature for 30 h, resulting in a viscous solution. Subsequently, a 2.5% sodium hydroxide solution was gradually added to neutralize the acidity of the medium. The resulting material was filtered, washed with distilled water, and air dried at room temperature, reaching a final yield of 85% [44].

The physicochemical parameters of the white product (shrimp-derived chitosan) were analyzed, covering aspects such as solubility, moisture and ash levels, yield, and the degree of deacetylation, as shown in

Table 1. Physicochemical properties of shrimp-derived chitosan.

Parameters	Percentages
Performance	85
Solubility	Soluble in acetic acid (1.5%) Medium soluble in H2O Insoluble in NaOH
Ash content	2.4
Moisture content	7.3
Degree of deacetylation	73

. Additionally, FT-IR methods and X-ray diffraction (XRD) investigations were used to describe it.

2.2.2. Determination and Characterization of the Physicochemical Properties of Chitosan

Once synthesized, CS was characterized by determining several physicochemical properties.

2.2.3. Chitosan Solubility

The solubility of CS has been evaluated in several solvents. A known amount of CS was dissolved in 10 mL of 1.5% acetic acid, and its behavior was examined. This method was repeated using distilled water and a 0.2 M NaOH solution. The results were recorded to determine the solubility of CS in each solvent (Table 1).

2.2.4. Moisture Content

The moisture content of CS was measured using a gravimetric technique [45,46]. A known quantity of CS was weighed and dried in an oven at 105 degrees Celsius until it attained a steady weight. The weight loss was used to calculate the moisture content.

$$\% \mathrm{Moisture} \mathrm{content}={\displaystyle \frac{\mathrm{Wet} \mathrm{weight} \left(\mathrm{g}\right)-\mathrm{Dry} \mathrm{weight} \left(\mathrm{g}\right)}{\mathrm{Wet} \mathrm{weight} \left(\mathrm{g}\right)}}\times 100$$

2.2.5. Ash Content

A porcelain crucible was used to determine the ash content. The empty crucible was weighed, and a known amount of CS was added. The crucible was placed in a muffle oven at 550 degrees Celsius for 10 h [45,46]. After cooling in a dehydrator, it was weighed again to calculate the ash content using the following formula, and the results are shown in Table 1.

$$\% \mathrm{Ashes}={\displaystyle \frac{\mathrm{Weight} \mathrm{of} \mathrm{residue} \left(\mathrm{g}\right)}{\mathrm{Sample} \mathrm{weight} \left(\mathrm{g}\right)}}\times 100$$

2.2.6. Degree of Deacetylation (DDA)

The degree of deacetylation of CS was analyzed by FTIR at frequencies between 4000 and 500 cm⁻¹ [47]. A sample of CS was prepared and FTIR analysis was used to determine the characteristic absorption bands of the functional groups present (see Figure 2). The DDA was calculated as the ratio between the intensity of the absorption bands of the acetyl and amino groups, which provides information on the purity and functionality of the CS (Table 1).

$$\mathrm{DDA}={\displaystyle \frac{{\mathrm{A}}_{1600.72}}{{\mathrm{A}}_{3425.08}}}\times 115$$

$${\mathrm{Where} \mathrm{A}}_{1600.72}=-\log \left({\displaystyle \frac{{\mathrm{T}}_{1600.72}}{100}}\right)$$

$${\mathrm{Being} \mathrm{also} \mathrm{A}}_{3425.08}=-\log \left({\displaystyle \frac{{\mathrm{T}}_{3425.08}}{100}}\right)$$

T being the transmittance.

2.2.7. Development of Calibration Standards for AAS

For the preparation of the calibration standards, atomic absorption spectroscopy (AAS) was used using a 1200.0 μg/L multi-element standard stabilized in 5% (v/v) nitric acid, supplied by Merck (Darmstadt, Germany). The calibration standards were prepared using a Transferpette micropipette, generating solutions of 6, 12, 24, 36, and 48 μg/L. Before adding distilled water to the final volume, a solution of HNO3 (4.0 mL; 70%) was incorporated. Homogenization was then performed, and the mixture was kept until use.

2.2.8. Synthesis of Shrimp Chitosan Derivatives

Two solutions were prepared in individual glass beakers using shrimp CS powder (2.5 g, 0.150 mmol) and starch (1.2%) dissolved in acetic acid (100 mL, 1.5%). During a second step, additional compounds were incorporated into the previously prepared solution, including s-methyl-butylamine, glutaraldehyde, 1,3-dichloroacetone, epichlorohydrin, and p-benzoquinone. For 24 to 48 h, the resultant mixture was constantly agitated at room temperature [48].

In order to cause precipitation, the resulting viscous gel was gradually added to 450 mL of acetone. The resultant material was a white solid that was repeatedly cleaned with distilled water before being allowed to air dry at room temperature. Ultimately, as shown in Table 1, the yield was computed.

3. Results and Discussion

3.1. Method Selection

In order to determine the most effective and reliable predictive method for molecular property analysis, a simulation of CS and the CS/1,3-dichlorocetone system was carried out. Various levels of theory were used, specifically B3LYP/LANLD2Z, M06-2x/LANLD2Z, and M05-2x/LANLD2Z. This selection of methods was based on the need to attain the optimum possible equilibrium among the results’ accuracy and the computational cost associated with each calculation.

The key parameters considered for evaluating the suitability of the theoretical methods were the dipole moment and electronic energy, which are essential for characterizing the electronic and structural properties of the molecules studied. These results are presented in

Table 2. Parameters of theoretical levels.

Chitosan	Electronic Energy (Hartree)	Total Dipole Moment (TDM) (Debye)
B3LYP/LANLD2Z	−1849.47570	5.39787
M06-2X/LANLD2Z	−1848.96588	2.17032
M05-2X/LANLD2Z	−1849.17438	2.88629
Chitosan/1,3-dichlorocetone	Electronic Energy (Hartree)	Total Dipole Moment (TDM) (Debye)
B3LYP/LANLD2Z	−3049.37516	5.40473
M06-2X/LANLD2Z	−3048.12123	7.02216
M05-2X/LANLD2Z	−3048.89902	5.90192

, where it is evident that the B3LYP/LANLD2Z level of theory not only provides more excellent stability than the other theoretical levels analyzed but demonstrates a superior ability to predict molecular interactions and physical properties of the system under study.

3.2. Model Structure

Structural models were created to simulate the ability of CS to remove heavy metals. The three CS units that made up these models represented the fundamental structure. To replicate the conditions found in aqueous environments, each metal investigated was weakly correlated with five water molecules (H₂O). This resulted in a description denoted as M-5H₂O, where M refers to the metals Zn, Cd, and Pb. The interactions amongst CS and hydrated metals were considered an adsorption state. The configurations of CS and the hydrated metals mentioned above are shown in Figure 3.

In cases where a metal forms a bond with CS, this interaction could displace one water molecule; if it involves two bonds, it would be established across two water molecules. Applying the B3LYP level and the LANLD2Z basis set, all modeled structures were calculated employing DFT. Furthermore, the molecular electrostatic potential (MPEM) and the HOMO–LUMO band gap energy were computed using the same theoretical approach. Studies have shown that physical parameters, including dipole moment density (DMD), HOMO–LUMO band gap energy, and MPEM, are key indicators of the reactivity of a particular compound.

3.3. HOMO–LUMO Calculations

The HOMO–LUMO band gap energy was calculated along with the dipole moment (DMM) for the proposed structures of CS and CS/1,3-dichlorocetone with M-5H₂O, where M represents the metals Zn, Cd, and Pb; the calculations were performed using the same theoretical approach. Figure 4 depicts the computed HOMO–LUMO band gap, highlighting the orbital distribution within the molecule. For CS and CS/1,3-dichlorocetone, the orbitals were evenly distributed across the three units. In contrast, upon interaction with the metals, the orbital distribution became concentrated around the metal atoms.

The changes in the HOMO–LUMO gap energy and TDM are detailed in

Table 3. Calculated TDM (Debye) and HOMO–LUMO band gap energies ∆E (eV) using B3LYP/LANLD2Z for Chitosan, Chitosan/1,3-dichlorocetone, Chitosan/1,3-dichlorocetone + Zn, Chitosan/1,3-dichlorocetone + Cd, Chitosan/1,3-dichlorocetone + Pb.

Structure	Total Dipole Moment (TDM) (Debye)	HOMO eV	LUMO eV	∆E eV
Chitosan	5.397866	−0.24324	−0.02965	0.21359
Chitosan/1,3-dichlorocetone	5.404731	−0.23983	−0.04618	0.19365
Chitosan/1,3-dichlorocetone + Zn	14.693271	−0.16098	−0.06345	0.09753
Chitosan/1,3-dichlorocetone + Cd	4.515224	−0.17554	−0.06478	0.11076
Chitosan/1,3-dichlorocetone + Pb	7.448823	−0.05993	−0.04508	0.01485

. For the CS model, the band gap energy was 0.21359 eV and the TDM was 5.397866 Debye, and for CS/1,3-dichlorocetone, the band gap energy was 0.19365 eV and the TDM was 5.404731 Debye. In contrast, when CS/1,3-dichlorocetone was combined with M-5H₂O, significant variations in both parameters were recorded. For example, the HOMO–LUMO gap for CS/1,3-dichlorocetone + Zn decreased to 0.09753 eV, while the TDM increased to 14.693271 Debye, indicating a notable influence of zinc on CS/1,3-dichlorocetone. Similarly, for CS/1,3-dichlorocetone + Pb, the band gap energies and TDM values varied to 0.01485 eV and 7.448823 Debye, respectively, suggesting that lead also significantly affects CS/1,3-dichlorocetone.

Furthermore, CS/1,3-dichlorocetone + Cd showed a reduction in the band gap to 0.11076 eV, but also showed a decrease in the TDM to 4.515224 Debye. This indicates that cadmium does not significantly influence the structure or properties of CS/1,3-dichlorocetone. Compared to the other metals, the effects of cadmium on the reactivity, stability, or molecular interaction of this combination appear to be minimal. This lack of impact suggests that cadmium does not considerably alter the system’s electronic arrangement or energetic parameters, implying that the interaction between cadmium and CS/1,3-dichlorocetone is weak or less relevant than others.

An increase in the TDM and a decrease in the band gap energy suggests a higher probability of interaction between the molecules involved. From all the data analyzed, it is concluded that CS/1,3-dichlorocetone can interact with all the metals studied; however, it shows a higher capacity to interact with Zn and Pb due to its high TDM values and low band gap values.

3.4. Global Descriptors

Analyzing chemical compounds’ electronic and reactive properties is essential to understanding their behavior in different environments and applications [49]. In this context, global descriptors, derived from conceptual and computational chemistry, have emerged as fundamental tools to characterize molecules’ chemical stability and reactivity [50,51,52]. This work addresses the study of CS and CS/1,3-dichlorocetone, using advanced computational calculations to determine and compare their global descriptors (see

Table 4. Calculated energy of global descriptors (eV) using B3LYP/LANLD2Z for Chitosan, Chitosan/1,3-dichlorocetone, Chitosan/1,3-dichlorocetone + Zn, Chitosan/1,3-dichlorocetone + Cd, Chitosan/1,3-dichlorocetone + Pb.

Name	Chemical Potential (μ)	Ionization Potential (I)	Electronegativity (χ)	Electronic Affinity (A)	Electrophilicity (ω)	Hardness (η)
Chitosan	−0.21359	0.24324	0.13645	0.02965	0.00244	0.10680
Chitosan/1,3-dichlorocetone	−0.19365	0.23983	0.14301	0.04618	0.00182	0.09683
Chitosan/1,3-dichlorocetone + Zn	−0.09753	0.16098	0.11222	0.06345	0.00023	0.04877
Chitosan/1,3-dichlorocetone + Cd	−0.11076	0.17554	0.12016	0.06478	0.00034	0.05538
Chitosan/1,3-dichlorocetone + Pb	−0.01485	0.05993	0.05251	0.04508	0.00000	0.00743

).

The chemical potential (μ) reflects the inclination of molecules to gain or lose electrons. Pure CS has a chemical potential of −0.21359 eV, indicating a higher propensity to lose electrons than its derivatives. When CS is mixed with 1,3-dichlorocetone, μ increases to −0.19365 eV, suggesting a slight reduction in this tendency. Among the metal complexes, the system with lead (Pb) presents the highest value of μ (−0.01485 eV), indicating a lower electronic reactivity, followed by the complex with Zn (−0.09753 eV) and Cd (−0.11076 eV). This increase in μ is related to the interactions between the derivative and the metals, which partially stabilize the system. The ionization potential (I), which measures the energy required to extract an electron, is higher in pure CS (0.24324 eV), indicating more excellent stability against ionization. This value decreases in the functionalized derivative (0.23983 eV), evidencing a slight reduction in electronic stability. Among the metal complexes, the ionization potential decreases significantly, being the lowest for the complex with lead (0.05993 eV), followed by the complex with Zn (0.16098 eV) and Cd (0.17554 eV). This suggests that metals facilitate the loss of electrons in complex systems.

Electronegativity (χ), which represents the capacity of molecules to attract electrons, shows values similar to the behavior of μ. Pure CS has a value of 0.13645 eV, and the functionalized derivative increases slightly to 0.14301 eV, indicating a higher electron attraction. However, in metal complexes, χ decreases considerably, reaching its lowest value in the system with Pb (0.05251 eV), followed by Zn (0.11222 eV) and Cd (0.12016 eV). This reflects a decrease in electron affinity upon incorporation of metals. Electron affinity (A), which measures the energy released upon capturing an electron, follows an upward trend from pure CS (0.02965 eV) to the functionalized derivative (0.04618 eV), showing a higher capacity to accept electrons in the latter. In the metal complexes, the electron affinity reaches its maximum in the complex with Zn (0.06345 eV), followed by Cd (0.06478 eV), and decreases for the complex with Pb (0.04508 eV). This behavior suggests that the interaction with metals modulates the capacity of the system to accept electrons, being more pronounced in the systems with Zn and Cd.

The electrophilicity (ω), which combines electronegativity and chemical hardness, is low in all systems. Pure CS has a value of 0.00244 eV, while the functionalized derivative decreases slightly to 0.00182 eV. Among the metal complexes, the ω value is lowest for the system with Pb (0.00000 eV), followed by Zn (0.00023 eV) and Cd (0.00034 eV). This suggests that the complex systems have a low capacity to act as electron acceptors. Finally, the chemical hardness (η), which assesses the system’s resistance to changes in its electron density, is highest in pure CS (0.10680 eV), indicating high chemical stability. This value decreases in the functionalized derivative (0.09683 eV) and reaches its lowest value in the metal complexes, especially in the system with Pb (0.00743 eV). This reflects that the incorporation of metals significantly reduces the system’s resistance to electronic polarization.

These results demonstrate that composting CS with 1,3-dichlorocetone and forming metal complexes significantly alter its electronic and reactive properties. The decrease in chemical hardness, electrophilicity, and changes in chemical potential suggest that these modifications increase the molecules’ susceptibility to chemical interactions, making them potentially valuable for specific applications such as heavy metal adsorption.

3.5. Molecular Electrostatic Potential Map

The molecular electric potential map (MPEM) provides a detailed representation of the surrounding charge distribution, along with the influence of the nuclei and the force exerted by the electrons at a given point. The MPEM is represented by a gradient of colors ranging from red through orange, yellow and green to blue. This color gradation reflects the different intensities of the MPEM, with red indicating the lowest value and blue the highest. The determination of the MPEM is crucial to identify the active site of the molecule and its ability to interact with neighboring atoms.

Figure 5a presents the MPEM contour for CS, where a low potential red region suggests a high electron density. Therefore, the active sites on CS correspond to the NH₂ groups. Figure 5b for CS/1,3-dichlorocetone shows the MPEM contour for hydrated metals such as Zn, Cd, and Pb adsorption. This contour suggests that the structures exhibit higher reactivity in the regions where the red area is present.

3.6. Experimental Results

3.6.1. Performance

A high and excellent yield of CS was achieved from shrimp extraction (85%), while the products underwent cross-linking. With s-methyl-butylamine, glutaraldehyde, 1,3-dichloroacetone, epichlorohydrin, and p-benzoquinone. achieved values between 64% and 73%. On the other hand, the CS cross-linked with p-benzoquinone presented the lowest yield (58%). This decrease is due to the loss of small particles during the filtration, washing, and grinding processes.

3.6.2. Chitosan Solubility

Solubility tests carried out on CS produced from shrimp showed that it dissolves slightly in water, being insoluble in NaOH and partially soluble in 1.5% acetic acid.

3.6.3. Moisture Content

According to previous studies, the synthesized CS showed a moisture content around 7.3%, a value that is within the typical range for commercial CS [53,54].

3.6.4. Ash Content

The ash content of the CS prepared from shrimp shells was 2.4%, comparable to that of commercial CS, which is close to 2%. This result suggests that the prepared CS is suitable for applications such as industrial wastewater treatment.

3.6.5. Degree of Deacetylation (DDA)

The deacetylation degree of the obtained CS was 73%, which falls within the satisfactory range of 72% to 85% typically reported for commercial products. This parameter is crucial, as it directly influences properties such as solubility and biodegradability. It should be noted that DDA can vary between 31% and 96%, depending on the source, preparation method, analytical technique, and equipment used.

3.6.6. FTIR Analysis

The CS extracted from shrimp underwent characterization through FTIR spectroscopy unveiling fascinating structural details. Distinct bands in the 3200–3700 cm⁻¹ range highlighted the stretching of OH and NH₂ functional groups associated with the amine group. Vibrations detected at 2870 and 2340 cm⁻¹ signaled the presence of methylene groups within CH₂OH and NHCOCH₃, alongside the pyranose ring featuring a methyl group. A notable peak at 1657 cm⁻¹, found within the 1651–1558 cm⁻¹ interval, was attributed to the secondary amide group (RNHCO). Further, the bands at 1421, 1379, and 1389 cm⁻¹ revealed the torsional vibrations of CH₂ groups, while absorptions between 1160 and 1000 cm⁻¹ captured the stretching of CO groups. Subtle peaks at 610 cm⁻¹ and 647 cm⁻¹ showcased the characteristic flapping of the polysaccharide backbone in CS. Interestingly, the spectrum also revealed the absence of the 3425 cm⁻¹ peak, tied to the OH group, and the 2921 cm⁻¹ peak, associated with CH₂OH in methylene, marking clear evidence of specific structural transformations.

Conversely, the peak at 1630 cm⁻¹ highlighted the extension of the CO bond within the amide group, while the peaks in the range of 1656–1628 cm⁻¹ corresponded to NH stretching vibrations. The presence of the NHCOCH₃ group in the pyranose ring was evident from the peaks between 1257 and 1380 cm⁻¹. Notably, the strong peaks at 1158 cm⁻¹ and 1154 cm⁻¹ were attributed to COC glycosidic bonds. The peak at 1099 cm⁻¹ indicated the auxiliary hydroxyl group (OH), while the essential OH group was reflected in the peaks at 1027 cm⁻¹. Additionally, the CO bending vibrations within the CH ring appeared at 894 cm⁻¹, representing the skeletal movements of the pyranose ring. Finally, out-of-plane vibrations were marked by peaks at 603 cm⁻¹ and 665 cm⁻¹, further enriching the structural insights.

3.6.7. Diffractometry (XRD)

X-ray diffraction (XRD) analysis of the CS uncovered two prominent diffraction peaks, located at 2θ = 8° and 2θ = 20°, evidencing key structural features, as well as demonstrating a high crystallinity level in the material. The vigorous intensity of these peaks is attributed to the incorporation of water molecules within the crystal structure. In the range between 20° and 60°, a significant decrease in the intensity of the peaks was observed, suggesting a reduction in hydrogen bonding, both at the intermolecular and intramolecular levels. The peaks were assigned to the 022 and 115 crystallographic planes, corresponding to the lowest angles recorded for CS, as shown in Figure 6.

Notably, the peak associated with plane 115 presented the maximum intensity, although this decreased progressively with increasing deacetylation degree to reappear near the same reflection angle. This behavior is consistent with findings reported in previous research, which describe characteristic X-ray diffraction patterns of CS, reaffirming its distinctive crystalline structure.

These experimental results were compared with previous research in the literature, such as Vieira et al. (2019) [37], in which the researchers explored the adsorption capacity of chitosan for Pb(II) and Cu(II) ions, finding that the process was endothermic and spontaneous, highlighting the importance of functional groups in the stabilization of metal complexes. In another study, Ezzat et al. (2020) [38] used DFT to evaluate the selectivity of chitosan towards various heavy metals, confirming a higher affinity for Pb and Cu. Menazea et al. (2020) [39] also and found that the chitosan/graphene oxide interaction showed superior selectivity compared to pure chitosan.

3.6.8. Analysis of the Performance of Cross-Linked Chitosan Products in Removing Elements from Poultry Wastewater

Data obtained through atomic absorption spectroscopy indicate that the cross-linked products from CS (designated as A–E) show remarkable efficiency in the capturing of Cr, Cu, and Pb, which has significantly reduced their concentrations in the analyzed wastewater. The measurements revealed that the residual concentrations of Cr and Pb were 0.03 mg/L, while the concentration of Cu reached 0.05 mg/L. Although the level of iron (Fe) was somewhat higher (up to 0.9 mg/L), the levels of Cr, Cu, and Pb were found in low ranges between traces and ultra-trace (<0.05 mg/L), thanks to the adsorbent action of the cross-linked derivatives of CS. However, the persistence of these metals, even at minimal concentrations, raises long-term concerns due to their capacity to accumulate in aquatic bodies through processes such as evaporation. These results corroborate previous reports on water contamination by heavy metals, highlighting that Pb and Cu constitute a significant threat due to their high toxicity, which can result in serious diseases in both animals and humans.

Among the derivatives analyzed, CS cross-linked with 1,3-dichloroacetone proved the most effective in removing Cr, Cu, Zn, and Pb, outperforming other products evaluated. The order of efficiency for cross-linked products in heavy metal adsorption is as follows: product E proved to be the most effective for Pb and Zn, whereas product A excelled in the adsorption of Cu, Fe, and Cr (See Figure 7, Figure 8, Figure 9, Figure 10 and Figure 11).

Cross-linked materials used in the removal of heavy metals from wastewater from the poultry industry include the following:

(A)

Glutaraldehyde;

(B)

Epichlorohydrin;

(C)

S-methylbutylamine;

(D)

p-Benzoquinone;

(E)

1,3-Dichloroaceton.

Our research focuses on studying the CS biopolymer-derived structure, precisely the CS/1,3-dichlorocetone combination, to develop a reliable, economically viable, and highly efficient material for capturing heavy metals in contaminated waters. The stability and interaction between the CS derivative and heavy metals were studied through DFT, employing the B3LYP functional and the LANLD2Z basis set. The results obtained indicate band gap energy values for the combinations of CS/1,3-dichlorocetone with different metals: CS/1,3-dichlorocetone + Zn (0.09753 eV), CS/1,3-dichlorocetone + Cd (0.11076 eV), and CS/1,3-dichlorocetone + Pb (0.01485 eV). This finding suggests that the CS derivative exhibits remarkable selectivity and affinity towards hydrated metals Zn and Pb, while it shows low selectivity towards Cd metal. The observed interrelation among Zn and Pb with CS suggests that CS/1,3-dichlorocetone could be effectively used to detect and remove these metals in wastewater.

Table 5. Absorption parameters for each metal.

Metal	Concentration Range (mg/L)	qmax (mg/g)	KL (L/mg)	% Removal
Pb	0.01–0.05	0.05	0.45	72
Cr	0.01–0.02	0.02	0.38	68
Cu	0.011–0.05	0.05	0.42	70
Zn	0.017–0.09	0.09	0.35	63
Fe	0.50–0.85	0.85	0.30	57

presents the adsorption parameters for various metals, with iron (Fe) exhibiting the highest concentration range (0.50–0.85 mg/L) and maximum adsorption capacity (qmax = 0.85). Lead (Pb) shows the highest Langmuir constant (KL = 0.45), indicating the strongest affinity of the adsorbent for this metal. In terms of removal efficiency, Pb (72%) and Cu (70%) have the highest values, followed by Cr (68%), Zn (63%), and Fe (57%), highlighting variations in the adsorption process effectiveness depending on the metal analyzed.

The adsorption isotherms presented in Figure 12 illustrate the distinct adsorption behaviors of Pb, Cr, Cu, Zn, and Fe, highlighting the differences in their retention by the adsorbent material. The isotherm for Pb (Figure 12a) shows a clear exponential increase in the adsorbed amount (qe) with increasing initial concentration (Co), suggesting strong interactions and high selectivity of the adsorbent for Pb. This behavior aligns with a Langmuir-type adsorption model, where Pb ions occupy available adsorption sites efficiently. Conversely, Figure 12b–e, corresponding to Cr, Cu, Zn, and Fe, depicts a declining adsorption trend, indicating limited or ineffective retention of these metals. Cr (Figure 12b) shows a pronounced decrease in qe, likely due to ionic competition, unfavorable electrostatic interactions, or the presence of soluble chromium species in solution. Similarly, Cu (Figure 12c) and Zn (Figure 12d) exhibit decreasing qe values, which could be attributed to desorption processes, weak binding to the adsorbent, or early saturation of adsorption sites. Fe (Figure 12e) also follows this negative trend, suggesting that Fe speciation, influenced by pH, may play a role in its low adsorption efficiency.

Overall, Figure 12 demonstrates that the adsorbent is highly effective for Pb removal but shows poor performance for Cr, Cu, Zn, and Fe under the tested conditions. This highlights the need for modifications in experimental parameters, such as pH adjustment, ionic strength optimization, or adsorbent surface modifications, to enhance the retention of these metals and improve the efficiency of the adsorption process.

4. Conclusions

The present study has demonstrated that the CS derivative combined with 1,3-dichlorocetone is a promising material for the selective adsorption and removal of heavy metals, namely Zn and Pb, in wastewater. The experimental results were complemented by a computational analysis based on DFT and the B3LYP/LANL2DZ method, allowing for correlation of the electronic properties of the complexes formed with their behavior under experimental conditions. This methodological combination confirmed that the low band gap energies (HOMO–LUMO) and the high dipole moment values observed in the systems with Zn and Pb are directly associated with their higher adsorption capacity and selectivity. In contrast, the lower affinity towards Cd, evidenced by the simulations, reflects a limited interaction with this metal, delimiting the scope of the material in terms of specific applications.

Integrating the experimental and computational approaches allowed us to cross-validate the findings and provided a predictive framework to optimize future material modifications. These advances position the CS derivative as an effective, economical, and sustainable alternative to environmental remediation technologies. In addition, the material has great potential to be incorporated into composting processes, taking advantage of its biocompatibility and sustainability, which opens the possibility of combining the recovery of heavy metals with the generation of valuable products for agriculture and other sectors. Overall, this work reaffirms the value of CS as a selective and versatile adsorbent and highlights the impact of integrating computational tools with practical experimentation to design innovative and sustainable solutions.

5. Supplementary Information

The global descriptors provide crucial information about the ability of molecules to interact with their chemical environment, allowing us to predict their behavior in chemical reactions, intermolecular interactions, and electron transfer processes. The descriptors considered include the following:

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Chemical potential (μ): This descriptor reflects the molecule’s tendency to undergo electron gain or loss and is related to the energetic stability of the system. Low values of μ indicate a greater probability that the molecule will give up electrons, while high values suggest a greater propensity to accept them [37].

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Ionization potential (I): Defines the energy required to detach an electron from a molecule in its ground state. This parameter is directly related to the system’s electronic stability against ionization and indicates its resistance to losing electrons [38,50].

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Electron affinity (A): Represents the energy released when a molecule absorbs an additional electron. Electron affinity is associated with the molecule’s ability to act as an electron acceptor, making it relevant in redox interaction processes [38,50].

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Electronegativity (χ): This descriptor, introduced by Pauling, measures the tendency of an atom or molecule to draw electrons towards itself in a chemical interaction. In global terms, high electronegativity implies more significant electron attraction, which influences the polarity of molecular interactions [39,55].

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Chemical hardness (η): Related to a molecule’s resistance to changes in its electron density, hardness is a key parameter for assessing chemical stability. Higher hardness implies lower reactivity to external agents, while low hardness indicates greater susceptibility to chemical interactions [37,38].

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Electrophilicity (ω): This descriptor combines electronegativity and hardness to quantify a molecule’s ability to accept electrons during a chemical interaction. It is beneficial for identifying highly reactive systems in electron transfer processes or nucleophilic reactions [56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71].