@article{c8cfcc0fc89247069857abc3851f259c,
title = "Deep Learning Neural Network Approach for Predicting the Sorption of Ionizable and Polar Organic Pollutants to a Wide Range of Carbonaceous Materials",
keywords = "sorption, sorbents, carbon, organic compounds, Neural Networks, SINGLE, FREE-ENERGY RELATIONSHIPS, HERBICIDES, ADSORPTION, AQUEOUS-SOLUTION, THERMODYNAMICS, SULFAMETHAZINE, ACTIVATED CARBON, BIOCHAR, CORN STRAW",
author = "Gabriel Sigmund and Mehdi Gharasoo and Thorsten H{\"u}ffer and Thilo Hofmann",
note = "Publisher Copyright: Copyright {\textcopyright} 2020 American Chemical Society.",
year = "2020",
month = apr,
day = "7",
doi = "10.1021/acs.est.9b06287",
language = "English",
volume = "54",
pages = "4583--4591",
journal = "Environmental Science & Technology",
issn = "0013-936X",
publisher = "AMER CHEMICAL SOC",
number = "7",
}