We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Identification of common textile microplastics via autofluorescence spectroscopy coupled with k-means cluster analysis
AI summary Read the abstract
This research demonstrated that autofluorescence spectroscopy combined with k-means cluster analysis can successfully identify common textile polymer types in greywater from laundry, using a minimal input dataset. The method accounts for the effects of photooxidation and dyes on spectral signatures, offering a practical approach for microplastic fiber identification.
This research proposes autofluorescence spectroscopy for the successful identification of common polymers present in greywater from a minimal input data set. The effects of photooxidation and dyes are also considered.
More Papers Like This
Sensitive quantification and morphological analysis of microfibers in laundry wastewater: Standardization and validation of a fluorescence-based method
AI summary Read the abstract
Synthetic microfibers shed during laundry make up a large share of microplastics found in aquatic environments, but accurately counting them in wastewater has been technically inconsistent between labs. This study standardized and validated a fluorescence-based staining method for quantifying microfibers in laundry effluent, making it faster and more accessible than conventional spectroscopic approaches. A validated standard method is critical for generating comparable data across studies and informing regulations on microfiber pollution from washing machines.
Optimising microplastics analysis for quantifying and identifying microplastic fibres in laundry wastewater
AI summary Read the abstract
This methodological paper optimized microplastic analysis protocols for identifying and quantifying particles in environmental samples, comparing extraction, digestion, and spectroscopic identification approaches to improve accuracy and reduce contamination.
Spectroscopic Analysis of Microplastic Fibers Released During Laundry Washing Cycle
AI summary Read the abstract
Researchers analyzed microplastic fibers released from synthetic textiles during laundry washing cycles using FTIR spectroscopy, demonstrating that spectroscopic identification of fiber polymer type is feasible and identifying key fiber release characteristics from different fabric types.
Optical, spectroscopic and thermal analysis of fibers released during laundry washing cycle
AI summary Read the abstract
Researchers analyzed the synthetic fibers released from laundry washing using optical microscopy, spectroscopy, and thermal analysis to fully characterize their size, polymer composition, and structure. The study found that a significant number of plastic fibers are released per wash cycle and that current wastewater treatment is insufficient to capture all of them before they reach waterways. Detailed fiber characterization is important for developing targeted solutions to reduce this major source of microplastic pollution.
Fourier-Transform Infrared Spectroscopy of Environmentally Weathered Textile Fabrics for Enhanced Microplastic Identification
AI summary Read the abstract
This study used infrared spectroscopy to identify microplastic fibers from clothing that had been weathered by ocean conditions, finding that environmental aging makes spectral identification more difficult. Accurate detection of these aged fibers is essential for understanding the true scale of textile microplastic pollution in the ocean.
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.