Highly selective molecularly imprinted polymer nanoparticles (MIP NPs)-based microfluidic gas sensor for...

Area of Science:

• Materials Science
• Analytical Chemistry
• Sensor Technology

Background:

• Developing selective and sensitive gas sensors is crucial for accurate analyte detection.
• Metal oxide-based sensors integrated with microfluidics offer potential for enhanced performance.
• Molecularly imprinted polymers (MIPs) provide tailored recognition sites for specific molecules.

Purpose of the Study:

• To report a highly selective microfluidic integrated metal oxide gas sensor for tetrahydrocannabinol (THC) detection.
• To investigate the efficacy of MIP nanoparticles (MIP NPs) with THC recognition sites in a microfluidic channel.
• To evaluate the sensor's selectivity and sensitivity against other analytes.

Main Methods:

• Synthesized MIP nanoparticles (MIP NPs) with specific THC recognition sites.
• Coated a 3D-printed microfluidic channel with MIP NPs and nonimprinted polymer nanoparticles (NIP NPs) for comparison.
• Evaluated sensor performance by exposing channels to THC, cannabidiol (CBD), methanol, and ethanol at 300°C.
• Characterized NPs using scanning electron microscopy (SEM) and Raman spectroscopy.
• Classified channel response data using a Fine KNN classification model in MATLAB (96.3% accuracy).

Main Results:

• The MIP NPs coated channel demonstrated significantly higher selectivity towards THC compared to the NIP NPs channel.
• The presence of THC recognition sites in MIP NPs enabled specific capture of THC molecules.
• The sensor system achieved 96.3% accuracy in classifying analyte responses using the Fine KNN model.

Conclusions:

• Microfluidic integrated metal oxide gas sensors based on MIP NPs offer highly selective THC detection.
• The tailored recognition sites on MIP NPs are effective in distinguishing THC from similar compounds like CBD.
• This approach provides a promising platform for sensitive and selective detection of specific volatile organic compounds.