In this work, biomass obtained from seeds (S-MO) and leaves (L-MO) of the Moringa oleifera plant were used as low-cost biosorbents to remove the Pb(II), Cd(II), Co(II), and Ni(II) from aqueous solutions. The biosorption of the heavy metal ions was done using the batch technique. The effects of contact time (30–1440 min), biosorbent dosage (10–50 g/L) (0.1–0.5 g), and initial concentration of metals (10–500 mg/L) on the sorption capacity of metal ions were investigated. The S-MO and L-MO samples’ characterization was performed using pH_pzc, X-ray Diffraction (XRD), and Fourier Transform Infrared Spectroscopy (FTIR). It was found that the pH_pzc was notably different between the seeds and leave-derived biosorbents. The removal process’s experimental kinetic data for both S-MO and L-MO were best described by the pseudo-second-order model for all metal ions, with R² above 0.997 in all cases. Langmuir and Freundlich’s models were also used to analyze the isotherms parameters. Based on the Langmuir model, the maximum sorption capacities (Qm) for L-MO were found as follows: L-MO-Pb > L-MO-Cd > L-MO-Co ≥ L-MO-Ni, and for S-MO, the values of Qm values presented the following order: S-MO-Pb > S-MO-Co > S-MO-Cd > S-MO-Ni.

Adsorption of Pb(II) from aqueous solution using MFe₂O₄ nanoferrites (M = Co, Ni, and Zn) was studied. Nanoferrite samples were prepared via the mechanochemical method and were characterized by X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), micro-Raman, and vibrating sample magnetometry (VSM). XRD analysis confirms the formation of pure single phases of cubic ferrites with average crystallite sizes of 23.8, 19.4, and 19.2 nm for CoFe₂O₄, NiFe₂O₄, and ZnFe₂O₄, respectively. Only NiFe₂O₄ and ZnFe₂O₄ samples show superparamagnetic behavior at room temperature, whereas CoFe₂O₄ is ferromagnetic. Kinetics and isotherm adsorption studies for adsorption of Pb(II) were carried out. A pseudo-second-order kinetic describes the sorption behavior. The experimental data of the isotherms were well fitted to the Langmuir isotherm model. The maximum adsorption capacity of Pb(II) on the nanoferrites was found to be 20.58, 17.76, and 9.34 mg·g⁻¹ for M = Co, Ni, and Zn, respectively.

This work aimed to describe the adsorption behavior of Congo red (CR) onto activated biochar material prepared from Haematoxylum campechianum waste (ABHC). The carbon precursor was soaked with phosphoric acid, followed by pyrolysis to convert the precursor into activated biochar. The surface morphology of the adsorbent (before and after dye adsorption) was characterized by scanning electron microscopy (SEM/EDS), BET method, X-ray powder diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR) and, lastly, pH_pzc was also determined. Batch studies were carried out in the following intervals of pH = 4–10, temperature = 300.15–330.15 K, the dose of adsorbent = 1–10 g/L, and isotherms evaluated the adsorption process to determine the maximum adsorption capacity (Q_max, mg/g). Kinetic studies were performed starting from two different initial concentrations (25 and 50 mg/L) and at a maximum contact time of 48 h. The reusability potential of activated biochar was evaluated by adsorption–desorption cycles. The maximum adsorption capacity obtained with the Langmuir adsorption isotherm model was 114.8 mg/g at 300.15 K, pH = 5.4, and a dose of activated biochar of 1.0 g/L. This study also highlights the application of advanced machine learning techniques to optimize a chemical removal process. Leveraging a comprehensive dataset, a Gradient Boosting regression model was developed and fine-tuned using Bayesian optimization within a Python programming environment. The optimization algorithm efficiently navigated the input space to maximize the removal percentage, resulting in a predicted efficiency of approximately 90.47% under optimal conditions. These findings offer promising insights for enhancing efficiency in similar removal processes, showcasing the potential of machine learning in process optimization and environmental remediation.

Leucaena leucocephala is a potential source of polyphenols widely available in southern Mexico. This work highlights the extraction of polyphenols from Leucaena leucocephala leaves waste (LLEPs) and the evaluation of their efficiency to remove the single and multicomponent Pb(II) and Cd(II) metal ions from aqueous solutions. Batch test conditions were carried out to examine the effects of contact time, initial metal ion concentration, and adsorbent dosage on the biosorption process. The surface textures and the composition of the LLEP biosorbent was characterized using pH of point of zero charge (pH_PZC), attenuated total reflectance Fourier transform infrared (ATR-FTIR), and matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry, respectively. Further analysis using ATR-FTIR after adsorption contact of biosorbent was also investigated. The highest Langmuir saturation monolayer adsorption capacity, q_m, for the removal of Pb(II) by LLEPs was obtained as 25.51 and 21.55 mg/g in mono- and bimetal solutions, respectively. The pseudo-second-order model provided the best fit for the kinetic data obtained for the removal of Pb(II), Cd(II), and their mixture, and the k₂ values depend on the adsorbent mass. This implied that the chemisorption process might be the mechanism of the solute ions-LLEPs interaction in this study. Furthermore, nearly 100% removal of lead and cadmium individually and 95% of their mixture was found using 0.9 g of LLEPs.