Chitosan-Functionalized Lithium Iron Oxide Nanoparticles for Magnetic Hyperthermia Applications

Area of Science:

• Materials Science
• Nanotechnology
• Biomedical Engineering

Background:

• Iron oxide nanomaterials are promising for hyperthermia cancer therapy due to their magnetic properties.
• Controlling crystal structure and surface modification is crucial for optimizing magnetic and thermal performance.
• Chitosan coating can improve biocompatibility and stability of nanomaterials.

Purpose of the Study:

• To synthesize and characterize Li-doped iron oxide (Li_xFe_2-xO₃) and chitosan-coated (CTS) Li_1.5Fe_1.5O₃ nanomaterials (NMs).
• To evaluate their magnetic properties, hyperthermia performance (SAR), and biocompatibility.
• To utilize machine learning for optimizing synthesis conditions and predicting heating efficiency.

Main Methods:

• Sol-gel synthesis of α-Fe₂O₃ and Li₃Fe_2-xO₃ (x=0.1, 0.3, 0.5) NMs, followed by CTS coating on Li_1.5Fe_1.5O₃.
• Rietveld refinement for crystal structure analysis, FE-SEM and TEM for morphology and size.
• SQUID for magnetic properties, XPS for surface chemistry, and hyperthermia testing under AC magnetic field.
• Machine learning algorithms applied to correlate synthesis parameters with SAR and heating efficiency.

Main Results:

• Synthesized NMs showed phase transitions from rhombohedral to cubic with increasing Li doping.
• Li_1.5Fe_1.5O₃ NMs exhibited highest saturation magnetization (49.84 emu/g) and SAR (265.11 W/g).
• CTS-coated NMs demonstrated improved cell viability in MTT assays on NRK 52 E cells.
• Machine learning models provided guidelines for enhancing heating performance.

Conclusions:

• Li-doped iron oxide nanomaterials, particularly Li_1.5Fe_1.5O₃, are effective for magnetic hyperthermia.
• Chitosan coating enhances biocompatibility without significantly compromising magnetic heating efficiency.
• Machine learning aids in optimizing material design for improved therapeutic outcomes.