Trapping tiny pollutants: SERS-driven strategies for microplastics and nanoplastics detection

Area of Science:

• Environmental Science
• Analytical Chemistry
• Materials Science

Background:

• Microplastics and nanoplastics are pervasive environmental contaminants with significant ecological and human health risks.
• Their complex nature, diverse sizes, and morphologies present substantial challenges for accurate detection and quantification.
• Advanced spectroscopic techniques are crucial for addressing these analytical hurdles.

Purpose of the Study:

• To review the principles, instrumentation, and substrate design strategies of Raman and SERS for micro/nanoplastic analysis.
• To highlight SERS's potential for ultrasensitive detection and its integration with chemometrics and machine learning.
• To discuss current limitations and future prospects for real-world applicability.

Main Methods:

• Introduction to fundamental principles of Raman and SERS.
• Overview of relevant instrumentation and SERS substrate design.
• Discussion of SERS-enabled ultrasensitive detection methodologies.

Main Results:

• Raman and SERS show significant promise for micro/nanoplastic detection and characterization.
• Integration with chemometrics and machine learning enhances analytical capabilities.
• SERS offers a pathway towards ultrasensitive quantification in complex matrices.

Conclusions:

• Raman and SERS are powerful tools for micro/nanoplastic analysis, with SERS offering superior sensitivity.
• Addressing challenges like signal variability, standardization, and sample preparation is key for broader adoption.
• Future research focusing on AI, substrate engineering, and multi-modal approaches will advance real-world applications.