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Based on T.E.S.T toxicity prediction and machine learning to forecast toxicity dynamics in the photocatalytic degradation of tetracycline

Kaihang Liu, Wenhui Ni, Qiaoyu Zhang, Xu Huang, Tao Luo, Jian Huang, Hua Zhang, Yongcai Zhang, Fumin Peng

2024Physical Chemistry Chemical Physics15 citationsDOI

Abstract

= 0.878 and a mean absolute error of MAE = 0.02. The model can track the changes of photocatalytic intermediates, in combination with toxicity simulation, which facilitates the prediction of toxicity at different degradation stages, thus allowing selection of the optimal timing of biological treatment interventions.

Topics & Concepts

ToxicityDegradation (telecommunications)TetracyclinePhotocatalysisChemistryEnvironmental chemistryComputer scienceBiochemistryCatalysisOrganic chemistryAntibioticsTelecommunicationsWater Quality Monitoring and AnalysisAdvanced Chemical Sensor TechnologiesBiosensors and Analytical Detection
Based on T.E.S.T toxicity prediction and machine learning to forecast toxicity dynamics in the photocatalytic degradation of tetracycline | Litcius