0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Detection Methods Sign in to save

Targeted Analysis of Microplastics Using Discrete Frequency Infrared Imaging

Analytical Chemistry 2022 9 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 35 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Guangyu Liu, Yujuan Hua, Ronda Gras, Jim Luong

Summary

Researchers developed a targeted microplastic analysis strategy using discrete frequency infrared (DFIR) imaging with a quantum cascade laser system, demonstrating that by scanning only 20% of particles at predetermined absorption wavelengths, the method could identify 87.7% of spiked polyethylene particles and achieve at least a fivefold improvement in sample throughput over full-spectrum imaging approaches.

Polymers

An analytical strategy to improve sample throughput with discrete frequency infrared image-based targeted analysis of microplastics using a laser direct infrared chemical imaging system was successfully developed and implemented. Leveraging a quantum cascade laser as a light source, the system could lock the frequency at predetermined wavelengths and use a discrete frequency infrared imaging technique to identify particles with absorption at desired wavelengths. In this way, targeted analysis can be achieved by selectively characterizing these particles. In the concept demonstration study, the targeted analysis was able to identify 87.7% of spiked polyethylene particles by scanning only 20% of the particles in the sample. The technique substantially improves sample throughput by at least a factor of 4 under conditions used. In the tests performed with real environmental samples, the targeted analysis workflow correctly identified eight types of common microplastics by only investigating around 60% of the particles and less than 30% of the sample area. Results obtained demonstrated that this scanning strategy is a game changer to enhance sample throughput in microplastic analysis. The technique has the potential of being applied to other infrared-based analytical platforms.

Sign in to start a discussion.

More Papers Like This

Article Tier 2

Discrete frequency infrared-guided image for microplastic analysis: Performance and limitations

Researchers evaluated the performance and limitations of a discrete frequency infrared imaging approach using a quantum cascade laser for microplastic analysis, finding that over 90% of fluorescently labelled polyethylene particles larger than 20 micrometers were correctly identified, with throughput-accuracy tradeoffs at high-throughput settings.

Article Tier 2

Rapid Identification and Quantification of Microplastics in the Environment by Quantum Cascade Laser-Based Hyperspectral Infrared Chemical Imaging

Quantum cascade laser infrared microscopy was evaluated as a rapid method for identifying and quantifying microplastics in environmental samples. The technique showed potential for faster polymer identification compared to conventional FTIR mapping, offering advantages for high-throughput microplastic monitoring.

Article Tier 2

Sample-based subsampling strategies to identify microplastics in the presence of a high number of particles using quantum-cascade laser-based infrared imaging

Researchers developed a new subsampling strategy for identifying microplastics using quantum-cascade laser-based infrared imaging, which makes it practical to analyze samples containing very large numbers of particles. Their approach tailors the subsampling areas to each individual sample rather than using a one-size-fits-all method, significantly reducing errors. The technique could make large-scale microplastic monitoring in environmental samples much more feasible and accurate.

Article Tier 2

Improved method for rapid characterization of microplastics in environmental samples with QCL-IR based microscopy and micro spectroscopy (Conference Presentation)

Researchers presented a quantum cascade laser infrared (QCL-IR) microscopy method for rapidly characterizing microplastics in environmental samples. The approach combines spatial imaging with chemical identification to classify particles by size, shape, and polymer type faster than conventional FTIR microscopy. Improved throughput in microplastic characterization helps researchers process the large sample volumes needed for environmental monitoring studies.

Article Tier 2

Reviewing the fundamentals and best practices to characterize microplastics using state–of–the-art quantum-cascade laser reflectance-absorbance spectroscopy

Researchers reviewed best practices for using quantum cascade laser infrared imaging (a high-speed scanning technology) to reliably identify microplastic particles, addressing technical pitfalls like particle-size effects on spectral readings. Standardizing this method is important for generating consistent, comparable data as governments push for official microplastic monitoring programs.

Share this paper