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A smart pre-treatment system for automated microplastic separation from soil: design and efficiency validation
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Scientists built an automated machine that pulls tiny plastic bits out of soil samples more consistently than manual methods, catching 85 to 97% of plastic depending on the type. This matters because better detection tools help researchers track how much plastic is contaminating our soil, food supply, and ultimately our bodies.
Microplastic (MP) contamination results in environmental degradation and human health impairments. The existing methods for MP separation from soil samples are either non-automated or semi-automated. This makes the extraction process operator dependent, time-consuming, and prone to contamination. The aim of this study was to develop a remotely controlled automated pre-treatment system for MP separation from soil samples. The proposed system integrates digestion, density separation, and overflow-based filtration in a single compact unit. An ESP32-based controller was used to automate the reagent flow rate, temperature, and processing time. The experiment was conducted under controlled laboratory conditions using 15 soil sub samples of 10 g each spiked with 1 g of a predefined amount of MP. The system was validated using low-density polyethylene (LDPE), polypropylene (PP) and polyvinyl chloride (PVC) with different size range. Each sub sample underwent digestion with 30% H 2 O 2 followed by density separation with ZnCl 2 . MP was finally separated by using the overflow-based filtration method and analyzed by Raman spectroscopy. Validation results showed recovery efficiency of 89 to 94% for LDPE, with a mean recovery efficiency of 91.8± 1.92% (mean ± SD), 95 to 99% for PP with a mean recovery efficiency of 97% ± 1.6% (mean ± SD) and 83 to 88% for PVC with a mean recovery efficiency of 85.2% ± 1.92% (mean ± SD). This proposed automated MP separation system for soil samples reduces manual intervention and process variability. This system also supports reliable environmental microplastic analysis and large-scale applications.
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