Synthesis of chitosan-based molecularly imprinted biopolymer for thin-film solid-phase microextraction of tramadol followed by its on-site detection using digital image colorimetry.

BACKGROUND

The development of sustainable analytical methods is crucial to minimize environmental impacts and align with green chemistry principles. In this study, a novel chitosan-based molecularly imprinted polymer (CS-MIP) thin film was designed for the selective microextraction of tramadol (TRA) from biological and environmental samples. Chitosan, a biodegradable and renewable polymer, was employed as a green functional monomer and supportive matrix. The integration of molecular imprinting with thin-film solid-phase microextraction (TF-SPME) provides a robust and eco-friendly approach to enhance extraction efficiency and selectivity for trace-level analysis.

RESULTS

The synthesized CS-MIP thin film was thoroughly characterized using SEM, ATR-FTIR, and TGA, confirming its structural stability and imprinting efficiency. The thin film was employed as a selective sorbent for TRA extraction using TF-SPME, coupled with digital image colorimetry (DIC) for on-site detection. The DIC method utilized the colorimetric shift of bromocresol green (BCG) in the presence of TRA, transitioning from green to dark green through an ion-pair production mechanism. Optimal conditions for colorimetric detection were determined using a one-variable-at-a-time approach, while TF-SPME parameters were optimized via central composite design. The method demonstrated a linear dynamic range of 9.9-500 ng mL, with limits of detection and quantification at 3.3 ng mL and 9.9 ng mL, respectively. High recoveries (80.70 %-106.00 %) were achieved for saliva, urine, and wastewater samples, showcasing the method's accuracy and applicability.

SIGNIFICANCE

This study introduces a sustainable and selective analytical method combining molecular imprinting and colorimetric detection. The CS-MIP-DIC system represents a breakthrough in green sample preparation and on-site monitoring, offering a practical, cost-effective solution for detecting TRA in various matrices. The proposed methodology sets a precedent for environmentally friendly and efficient analytical applications.