Study on quantitative structure-biodegradability relationships of amine collectors by GFA-ANN method
| Autor: | Ping Fang, Hao Duan, Xiaotong Zhou, Wengang Liu, Xinyang Wang, Naixu Zhang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Environmental Engineering
Health Toxicology and Mutagenesis 0211 other engineering and technologies chemistry.chemical_element Quantitative Structure-Activity Relationship 02 engineering and technology 010501 environmental sciences 01 natural sciences Molecular descriptor otorhinolaryngologic diseases Environmental Chemistry Organic chemistry Amines Waste Management and Disposal HOMO/LUMO Alkyl 0105 earth and related environmental sciences chemistry.chemical_classification 021110 strategic defence & security studies Valence (chemistry) Chemistry Biodegradation Pollution Nitrogen Quaternary Ammonium Compounds stomatognathic diseases Biodegradation Environmental Topological index Amine gas treating Neural Networks Computer |
| Zdroj: | Journal of hazardous materials. 415 |
| ISSN: | 1873-3336 |
| Popis: | In this study, the biodegradability of 17 amine collectors, categorized by fatty amine, quaternary ammonium compounds and oxygen-containing amine collectors, are tested with the Closed Bottle Test for 90 days, and the results indicate most amine collectors are not readily biodegradable. The oxygen-containing amine collectors have the best biodegradability due to the introduced oxygen-containing functional groups, subsequently fatty amine collectors with branched chains, while the tested quaternary ammonium compounds all have poor biodegradation ability. Besides, we search for and calculate 35 molecular descriptors to develop the quantitative structure biodegradability relationship (QSBR) of amine collectors. With the Genetic Function Approximation (GFA) algorithm, two sets of important molecular descriptors related to biodegradability (q) of amine collectors are selected from 35 molecular descriptors. Based on internal and external validations, the robust and reliable non-linear QSBR model with the squared correlation coefficient above 0.99 is determined via Artificial Neural Network (ANN) method, where the descriptors are respectively CL, N, E LUMO , δ v 2 , indicating the biodegradable ability of amine collectors is correlated with the alkyl chain lengths (CL), the number of nitrogen atom-containing compounds (N), energy of the lowest unoccupied molecular orbital ( E LUMO ) and valence second-order connectivity index ( δ v 2 ). |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect