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Peptide Specific Nanoplastic Detection Based on Sandwich Typed Localized Surface Plasmon Resonance
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Researchers developed a sandwich-type localized surface plasmon resonance sensor using oligo-peptide-conjugated gold nanoparticles to selectively detect and quantify polystyrene nanoplastics, demonstrating high specificity via peptide-PS binding measured with a standard UV-Vis spectrophotometer.
Recently, various waste microplastics sensors have been introduced in response to environmental and biological hazards posed by waste microplastics. In particular, the detrimental effects of nano-sized plastics or nanoplastics have been reported to be severe. Moreover, there have been many difficulties for sensing microplastics due to the limited methodologies for selectively recognizing nanoplastics. In this study, a customized gold nanoparticles (Au NPs) based localized surface plasmon resonance (LSPR) system having bio-mimicked peptide probes toward the nanoplastics was demonstrated. The specific determination through the oligo-peptide recognition was accomplished by chemical conjugation both on the LSPR chip's 40~50 nm Au NPs and sandwiched 5 nm Au NPs, respectively. The peptide probe could selectively bind to polystyrene (PS) nanoplastics in the forms of fragmented debris by cryo-grinding. A simple UV-Vis spectrophotometer was used to identify the LSPR sensing by primarily measuring the absorbance change and shift of absorption peak. The sandwich-binding could increase the LSPR detection sensitivity up to 60% due to consecutive plasmonic effects. In addition, microwave-boiled DI water inside of a styrofoam container was tested for putative PS nanoplastics resource as a real accessible sample. The LSPR system could be a novel protocol overcoming the limitations from conventional nanoplastic detection.
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Researchers built nanoscale silver-silicon hybrid platforms that can detect polystyrene nanoplastics using a technique called surface-enhanced Raman spectroscopy. The platforms achieved high sensitivity with detection limits in the microgram-per-milliliter range. The technology offers a promising approach for identifying nanoscale plastic particles that are too small for conventional detection methods.
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