Environmental science & technologyMachine LearningArsenicWater PollutantsChemical
Enabling Emergency Response to Arsenic Contamination: Simultaneous and Rapid Identification of Arsenic Speciation by a Machine Learning-Driven Fluorescent Sensor Array.
Dali Wei, Yunxiang Fan, Bohan Wu, Yuxuan Shen, Chunmeng Deng, Qiu Shen, Kun Zeng, Ligang Hu, Jingfu Liu, Zhugen Yang, Zhen Zhang
Published: 202510.1021/acs.est.5c08536
Abstract
The rapid identification of arsenic speciation is critical for assessing its toxicity and guiding emergency response during water contamination events, yet it remains a significant challenge for current analytical methods. Herein, a novel machine lea…
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