Polystyrene Magnetic Nanocomposites as Antibiotic Adsorbents

Area of Science:

• Environmental Science
• Materials Science
• Chemical Engineering

Background:

• Wastewater treatment plants (WWTP) are a significant source of antibiotics entering aquatic environments.
• Conventional WWTPs are ineffective at completely removing antibiotic compounds.
• Adsorption presents a sustainable tertiary treatment option for antibiotic removal.

Purpose of the Study:

• To synthesize a versatile poly(styrene-block-acrylic acid) diblock copolymer/Fe3O4 magnetic nanocomposite (P(St-b-AAc)/Fe3O4).
• To investigate the application of this nanocomposite for the removal of antibiotic compounds from aqueous solutions.
• To optimize removal efficiency by studying various operational parameters.

Main Methods:

• Synthesis of P(St-b-AAc) diblock copolymer using reversible addition fragmentation transfer (RAFT) polymerization.
• Adsorption of the copolymer onto Fe3O4 nanoparticles to create a magnetic nanocomposite.
• Characterization using scanning electron microscopy (SEM), X-ray diffraction (XRD), and vibrating sample magnetometer (VSM).
• Experimental studies on ciprofloxacin removal, including parameter optimization, kinetic, and isotherm analyses.

Main Results:

• The P(St-b-AAc)/Fe3O4 nanocomposite was successfully synthesized and characterized.
• Maximum ciprofloxacin removal efficiency of 97.5% was achieved under specific conditions (5 mg/L initial concentration, pH 7, 2 mg/L adsorbent dosage, 37.5 min contact time).
• Initial antibiotic concentration and adsorbent dosage were the most impactful parameters.
• Adsorption followed Langmuir isotherm model (R² = 0.9995) and second-order kinetics (R² = 0.9973).

Conclusions:

• The synthesized P(St-b-AAc)/Fe3O4 magnetic nanocomposite is a highly effective adsorbent for removing ciprofloxacin from aqueous solutions.
• The study demonstrates the potential of magnetic nanocomposites as a sustainable and efficient method for tackling antibiotic pollution in water.
• Optimization of operational parameters is crucial for maximizing removal efficiency in practical applications.