Magnetically Retrievable Core@Shell Nanocomposites for Rare Earth Element Adsorption: Experimental and Machine...

Area of Science:

• Materials Science
• Environmental Science
• Nanotechnology

Background:

• Sustainable recovery of rare earth elements (REEs) is critical for modern technologies.
• Conventional REE extraction methods face challenges due to limited reserves and environmental concerns.
• Developing efficient and eco-friendly REE adsorption platforms is essential.

Purpose of the Study:

• To synthesize magnetically retrievable core@shell nanocomposites (MRCSNs) for effective REE adsorption from aqueous media.
• To investigate the adsorption performance of MRCSNs functionalized with different ligands (NH2, NHNH2, EDTA).
• To integrate machine learning models with experimental data to predict and optimize REE adsorption.

Main Methods:

• Synthesis of core@shell magnetic nanoparticles with functional ligands (NH2, NHNH2, EDTA).
• Characterization of synthesized MRCSNs using various analytical techniques.
• Adsorption experiments to evaluate REE removal efficiency for different ions (Er3+, La3+, Nd3+, Pr3+, Sm3+).
• Development and application of XGBoost machine learning models for adsorption prediction.

Main Results:

• MRCSNs demonstrated efficient adsorption of target REE ions from water.
• MRCSN-EDTA exhibited superior performance, achieving up to 82% Er3+ and 75% Sm3+ adsorption.
• XGBoost models accurately predicted adsorption behavior (R2 ≈ 0.93).
• Sorbent loading was identified as the primary factor influencing adsorption, followed by REE atomic number.

Conclusions:

• Magnetically retrievable core@shell nanocomposites offer a promising platform for sustainable REE recovery.
• The integration of machine learning accelerates the optimization of adsorption processes.
• This combined approach holds potential for efficient and selective REE separation from complex matrices.