Aqueous Pb(II) Removal Using ZIF-60: Adsorption Studies, Response Surface Methodology and Machine Learning...

Area of Science:

• Materials Science
• Environmental Science
• Chemistry

Background:

• Zeolitic Imidazolate Frameworks (ZIFs) exhibit excellent porosity and stability, yet their application in water purification is largely unexplored beyond ZIF-8 and ZIF-67.
• The potential of other ZIF materials as adsorbents for water contaminants remains largely uninvestigated.

Purpose of the Study:

• To evaluate the efficacy of ZIF-60 as an adsorbent for removing lead ions from aqueous solutions.
• To characterize the synthesized ZIF-60 and optimize lead removal parameters using a multivariate approach.

Main Methods:

• Synthesis and characterization of ZIF-60 using FTIR, XRD, and TGA.
• Application of response surface methodology (RSM) to determine the impact of ZIF-60 dose and lead concentration on removal efficiency.
• Adsorption kinetics, isotherm, and thermodynamic studies to elucidate the lead removal mechanism.
• Machine learning algorithms, including random forest, were employed for predictive modeling.

Main Results:

• ZIF-60 dose and initial lead concentration were identified as the most significant factors influencing lead removal efficiency.
• Adsorption followed Avrami and pseudo-first-order kinetic models, indicating a complex adsorption process.
• The maximum adsorption capacity (qmax) for lead was predicted to be 1905 mg/g.
• Thermodynamic analysis confirmed the adsorption process to be endothermic and spontaneous.
• The random forest algorithm provided the most accurate predictive model for lead removal.

Conclusions:

• ZIF-60 is a novel and highly effective adsorbent for lead removal from contaminated water.
• The study provides a comprehensive understanding of ZIF-60's adsorption behavior and potential for water treatment applications.
• Machine learning integration offers a powerful tool for optimizing and predicting the performance of ZIF-based adsorbents.