We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Dual-mode optical nanoprobe based on red-emissive carbon dots for sensitive detection of positively charged nanoplastics
Summary
Researchers developed a dual-mode optical nanoprobe based on red-emissive carbon dots to detect positively charged nanoplastics in food and environmental samples. The probe detected charged nanoplastics with high sensitivity and selectivity via both fluorescence and colorimetric signals, offering a practical rapid-detection approach for a particle type that is especially bioaccumulative.
The large-scale production and use of plastics have led to the widespread distribution of nanoplastics (NPs) in environmental media and the food chain. Among various NPs, positively charged nanoplastics (pNPs) generated through aging processes exhibit enhanced bioaccumulation in living organisms and significantly increased biotoxicity. To achieve rapid detection of pNPs in food and environmental samples, this study synthesized red-emissive fluorescent carbon dots (CAT-RCDs) using 3,4-diaminobenzenesulfonic acid and catechol as precursors. Based on this, a sensing platform capable of fluorescence/colorimetric dual-mode detection of positively charged polystyrene nanoplastics (pPS-NPs) was constructed. The sensor exhibited a linear response from 1 to 50 mg/L (fluorescence) and 5-60 mg/L (colorimetric), with detection limits of 0.58 and 1.04 mg/L, respectively. Recovery rates of 90.91-104.80 % confirmed its accuracy. This dual-mode strategy allows visual detection and cross-validation of pPS-NPs, providing a rapid screening tool and a foundation for advanced nanoplastic sensing technologies.
Sign in to start a discussion.
More Papers Like This
Advances and prospects of carbon dots for microplastic analysis
This review assessed the potential of carbon dots, luminescent nanomaterials derived from carbon sources, as tools for microplastic detection and analysis in food and environmental samples, offering advantages in sensitivity and selectivity over conventional methods. The authors identify carbon dot-based sensing as a promising direction for filling the gap in standardized microplastic analytical methods.
Fluorescent molecular rotor-based probes for sensitive and selective detection of nanoplastics in food, environment, and living cells
Researchers developed two molecular rotor-based fluorescent probes that selectively detect oppositely charged nanoplastics through hydrophobic and electrostatic interactions. The probes demonstrated high sensitivity and specificity for nanoplastics in food, environmental, and live cell samples, providing a new tool for nanoplastic detection.
A photoluminescence strategy for detection nanoplastics in water and biological imaging in cells and plants
Researchers developed a fluorescent probe that can rapidly detect nanoplastics in water samples down to very low concentrations. The probe works by binding to nanoplastic surfaces through electrical and chemical interactions, which causes it to glow, enabling both detection and visual tracking in cells and plant tissues. This tool could help scientists better monitor nanoplastic contamination in water and understand how these tiny particles move through living organisms.
Selective Identification and Quantification of Microplastics Using Solid Fluorescent Green Carbon Dots (SFGCDs) – A Novel, Naked Eye Sensing Fluoroprobe
Researchers developed a novel fluorescent carbon dot probe that can selectively detect and quantify microplastics released from surgical face masks and cosmetic cleansers. The probe works through a fluorescence turn-off mechanism when microplastics are present, with a detection limit as low as 0.0063 g/L for particles 6 micrometers and larger. The study also demonstrated a simple filtration-based remediation approach, with the fluorescence signal recovering after microplastic removal.
Principles, performance and emerging trends for optical detection of environmental microplastics: A review
This review summarizes recent advances in optical detection methods for identifying microplastics in environmental samples, covering both spectroscopic techniques like Raman and infrared spectroscopy and fluorescence-based approaches using dyes such as Nile red. Researchers highlight how machine learning is improving the accuracy and efficiency of spectroscopic identification. The study also evaluates emerging fluorescent materials like carbon dots for specific microplastic identification and environmental behavior tracing.