Deep Learning Neural Network Approach for Predicting the Sorption of Ionizable and Polar Organic Pollutants to a Wide Range of Carbonaceous Materials
Gabriel Sigmund, Mehdi Gharasoo, Thorsten Hüffer, Thilo Hofmann
Abstract
). The neural network models are based on parameters generally available for carbonaceous sorbents and/or parameters freely available from online databases. A freely accessible graphical user interface is provided.
Topics & Concepts
SorptionEnvironmental remediationSorbentFreundlich equationFiltration (mathematics)WastewaterPollutantAdsorptionEnvironmental scienceEnvironmental chemistryContaminationChemistryEnvironmental engineeringOrganic chemistryMathematicsStatisticsEcologyBiologyWater Quality Monitoring and AnalysisToxic Organic Pollutants ImpactAdsorption and biosorption for pollutant removal