High-Throughput Silica Nanoparticle Detection for Quality Control of Complex Early Life Nutrition Food Matrices

Area of Science:

• Food Science
• Analytical Chemistry
• Nanotechnology

Background:

• Nanomaterials enhance products but raise safety concerns, especially for vulnerable populations.
• Quantifying nanoparticles in complex food matrices like early life nutrition (ELN) is difficult.
• Standardized methods are needed for nanoparticle quantification and "nanoparticle-free" claims.

Purpose of the Study:

• To develop and validate methods for characterizing silica nanoparticles (SiNPs) in ELN formulations.
• To address the challenges of nanoparticle detection in complex food matrices.
• To enable accurate quantification and differentiation of SiNP-containing products.

Main Methods:

• Silica nanoparticles (SiNPs) used as a model system.
• Acid treatments for sample digestion followed by size exclusion chromatography.
• Transmission electron microscopy (TEM) for morphology and size; microwave plasma atomic emission spectrometry (MP-AES) for silicon quantification.

Main Results:

• Successfully distinguished SiNP content in ELN formulations with 2-4% anticaking agent (AA) from AA-free formulations.
• Able to sort SiNPs by specific diameters (20, 50, and 80 nm).
• Highlighted the significant impact of the ELN matrix on sample preparation and analysis, requiring method adaptation.

Conclusions:

• Developed robust methods for SiNP characterization in complex ELN matrices.
• Validated the ability to quantify and differentiate SiNP levels in food products.
• These methods are expected to be implemented in quality control for high-throughput, automated analysis.