首页|Jiangnan University Reports Findings in Nanoplastics (The suspension stability o f nanoplastics in aquatic environments revealed using meta-analysis and machine learning)
Jiangnan University Reports Findings in Nanoplastics (The suspension stability o f nanoplastics in aquatic environments revealed using meta-analysis and machine learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Nanotechnology - Nanoplastics is the subject of a report. According to news reporting from Wuxi, People’s Republi c of China, by NewsRx journalists, research stated, “Nanoplastics (NPs) aggregat ion determines their bioavailability and risks in natural aquatic environments, which is driven by multiple environmental and polymer factors. The back propagat ion artificial neural network (BP-ANN) model in machine learning (R = 0.814) can fit the complex NPs aggregation, and the feature importance was in the order of surface charge of NPs > dissolved organic matter (DOM) > functional group of NPs > ioni c strength and pH > concentration of NPs.” The news correspondents obtained a quote from the research from Jiangnan Univers ity, “Meta-analysis results specified low surface charge (0 |z| <10 mV) of NPs, low concentration (<1 mg/L) and low molecu lar weight (<10 kg/mol) of DOM, NPs with amino groups, hig h ionic strength (IS > 700 mM) and acidic solution, and high concentration ( 20 mg/L) of NPs with smaller size (<1 00 nm) contribute to NPs aggregation, which is consistent with the prediction in machine learning. Feature interaction synergistically (e.g., DOM and pH) or ant agonistically (e.g., DOM and cation potential) changed NPs aggregation. Therefor e, NPs were predicted to aggregate in the dry period and estuary of Poyang Lake. Research on aggregation of NPs with different particle size,shapes, and functio nal groups, heteroaggregation of NPs with coexisting particles and aging effects should be strengthened in the future.”
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