We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
A high-throughput, automated technique for microplastics detection, quantification, and characterization in surface waters using laser direct infrared spectroscopy
AI summary Read the abstract
Researchers applied laser direct infrared spectroscopy in a high-throughput automated workflow to detect, quantify, and characterize microplastics in surface water from three urban creeks in Ohio. The method achieved 88.3% recovery and could identify particles as small as 20 micrometers by polymer type, size, and shape without manual intervention.
A high-throughput approach to detecting, quantifying, and characterizing microplastics (MPs) by shape, size, and polymer type using laser direct infrared (LDIR) spectroscopy in surface water samples is demonstrated. Three urban creeks were sampled for their MP content near Cincinnati, OH. A simple Fenton reaction was used to oxidize the surface water samples, and the water samples were filtered onto a gold-coated polyester membrane. Infrared (IR) analysis for polymer identification was conducted, with recoveries of 88.3% ± 1.2%. This method was able to quantify MPs down to a diameter of 20 µm, a size comparable to that of MPs quantified by other techniques such as Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy. A shape-classifying algorithm was designed using the aspect ratio values of particles to categorize MPs as fibers, fibrous fragments, fragments, spherical fragments, or spheres. Cut-off values were identified from measurements of known sphere, fragment, and fibrous particles. About half of all environmental samples were classified as fragments while the other shapes accounted for the other half. A cut-off hit quality index (HQI) value of 0.7 was used to classify known and unidentified particles based on spectral matches to a reference library. Center for Marine Debris Research Polymer Kit 1.0 standards were analyzed by LDIR and compared to the given FTIR spectra by HQI, showing that LDIR obtains similar identifications as FTIR analysis. The simplicity and automation of the LDIR allows for quick, reproducible particle analysis, making LDIR attractive for high-throughput analysis of MPs.
More Papers Like This
Rapid, Automated Characterization of Microplastics Using Laser Direct Infrared Imaging and Spectroscopy
AI summary Read the abstract
Researchers evaluated laser direct infrared imaging as a rapid, automated method to characterize microplastic particles, which addresses the bottleneck of analyzing thousands of particles per sample. Automated spectroscopic characterization is essential for making large-scale microplastic monitoring faster and more objective than traditional visual microscopy.
Identification and Quantification of Microplastics in the Marine Environment Using the Laser Direct Infrared (LDIR) Technique
AI summary Read the abstract
Researchers evaluated the laser direct infrared (LDIR) technique for identifying and quantifying marine microplastics, demonstrating it as a faster and more automated alternative to conventional FTIR methods with comparable accuracy.
Quantification and characterization of microplastics in surface water samples from the Northeast Atlantic Ocean using laser direct infrared imaging
AI summary Read the abstract
Researchers quantified microplastics in Northeast Atlantic Ocean surface waters using laser direct infrared imaging, detecting particles down to 20 micrometers and revealing microplastic concentrations and polymer compositions across eight sampling locations.
Methodologic insights aimed to set-up an innovative Laser Direct InfraRed (LDIR)-based method for the detection and characterization of microplastics in wastewaters
AI summary Read the abstract
Researchers developed and validated a method using Laser Direct Infrared imaging technology to detect and characterize microplastics in wastewater. Testing at a large municipal treatment plant in Italy, they found that the facility removed about 82% of microplastics, with most remaining particles smaller than 100 micrometers. The study provides a reproducible analytical approach that could help standardize how microplastic contamination in wastewater is measured and compared across different facilities.
Development of a Near-Infrared Imaging System for Identifying Microplastics in Water
AI summary Read the abstract
Researchers developed a near-infrared imaging system capable of automatically identifying and characterizing microplastics suspended in water, successfully obtaining material identification images without the manual sorting typically required by conventional methods.
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.