We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Towards a low-cost, rapid microplastic optical detection system using fluorescent staining through Nile Red for in situ ocean deployment
AI summary Read the abstract
This study presents a proof-of-concept for a portable, low-cost microplastic detection device that uses fluorescent dye (Nile Red) and a simple optical sensor to detect plastic particles in water. The system produced a signal that scaled linearly with microplastic concentration in lab tests. Development of cheap, field-deployable sensors like this could dramatically improve our ability to monitor microplastic pollution in real time across oceans and waterways, where current lab-based methods are too expensive and slow for widespread use.
Millions of tons of plastics are released into the ocean each year. Environmental forces break down these plastics into micro and nano-sized fragments, referred to respectively as microplastics (MPs) and nanoplastics (NPs). Their small size allows these plastic fragments to propagate across the planet’s ecosystems. The grave health consequences of plastic proliferation within the marine environment have increasingly garnered public concern. Given that current methodologies of analyzing MPs in environmental samples are expensive and time-intensive, there exists an urgent need for inexpensive, real-time microplastic detection systems. This research presents a proof-of-concept rapid microplastic detection system designed to be portable and low-cost. The system relies on a fluorescence-based optical-detection approach utilizing the staining of plastics with the fluorescent dye, Nile Red (NR). In this study, known quantities of polypropylene MPs were added to solutions of Nile Red. Resulting emissions were detected using a optical lens to focus fluorescent light on a silicon photodiode. Preliminary results showed that the system output signal is linear with the MP concentration of the measurement sample. This proof-of-concept serves as the basis for a low-cost, field-deployable instrument capable of rapid in situ MP detection. Future work will improve the sensitivity and resolution of the system, and work towards incorporating field tests.
More Papers Like This
Potential for Nile red dye-based analysis of microplastics from oceanic samples
AI summary Read the abstract
Researchers evaluated the Nile red fluorescent dye method for detecting and characterizing microplastics in ocean water samples, assessing its effectiveness compared to other analytical techniques. The method shows promise as a faster, lower-cost approach to large-scale microplastic monitoring.
Suitability of Nile Red Dye for In-Situ Microplastic Detection
AI summary Read the abstract
This thesis evaluated the suitability of Nile Red fluorescent dye for detecting microplastics in environmental samples, examining its effectiveness and limitations for field use. Accurate and affordable detection methods are essential for tracking plastic pollution in oceans and waterways.
A rapid-screening approach to detect and quantify microplastics based on fluorescent tagging with Nile Red
AI summary Read the abstract
Researchers developed a rapid fluorescent screening method using Nile Red dye to detect and quantify microplastics in environmental samples, finding it significantly faster than conventional methods while maintaining reasonable accuracy.
Identification and Quantification of Microplastics Using Nile Red Staining
AI summary Read the abstract
This study developed a rapid fluorescent staining method using the dye Nile Red to identify and quantify microplastics in environmental samples, offering an alternative to slower and more expensive spectroscopic techniques. Nile Red staining provides a faster way to differentiate microplastics from natural particles in large sample sets, improving throughput for environmental monitoring.
A dual-channel optical sensor for real-time microplastic classification via ratiometric fluorescence analysis
AI summary Read the abstract
Researchers tested a low-cost light-based sensor that stains tiny plastic particles with a dye and reads two color signals to identify the plastic type. In lab water samples containing six common plastics, the device correctly classified particle types 77.8% of the time overall, working better for some plastics (PP, PE, PS) than others (PMMA, PVC, PET).
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.