Modified macroporous adsorption resins with amino and acetyl groups through a novel method and adsorption behaviors for alizarin yellow GG |
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Authors: | Yi Liu Yongfeng Liu Zhenxing Zhang Dong Pei Jianteng Wei Duolong Di |
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Affiliation: | 1. Key Laboratory of Chemistry of Northwestern Plant Resources and Key Laboratory for Natural Medicine of Gansu Province, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, , Lanzhou, 730000 People's Republic of China;2. Centre of Resource Chemical and New Material, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, , Qingdao, 266100 People's Republic of China;3. Department of Pharmacy, Key Laboratory of Chemistry and Quality for Traditional Chinese Medicines of the College of Gansu Province, Gansu College of Traditional Chinese Medicine, , Lanzhou, 730000 People's Republic of China |
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Abstract: | Under bubble with air compressor, macroporous adsorption resin was functionalized with amino and acetyl groups. The method avoided the fragmentation of the resin during modification. Alizarin yellow GG (AYGG) was used as an adsorbate to investigate adsorption kinetics of the modified resins. It showed that pseudofirst‐order and pseudosecond‐order kinetics cannot reasonably express the adsorption process. A new kinetic model, multi‐layer adsorption model, showed much better fit to the adsorption kinetic data and corresponding kinetic parameters could predict adsorption mechanism. Meantime, AYGG can be easily recovered, and the resins can be regenerated. Due to π – π , electrostatic force and hydrogen bond interaction between the resin and carboxyl, phenolic hydroxyl, and azo groups of AYGG, the resin with amino group showed higher adsorption capacity than the other resins used in this study. Steric hindrance and decrease in electrostatic force were unfavorable for the enrichment of AYGG by the resin with acetyl group. Response surface model combining with central composite design was used to determine effects of pH and initial concentration on adsorption. It showed that a second‐order polynomial regression model could reasonably express the experimental data and optimum adsorption conditions were obtained. The design provided an effective methodology to optimize an adsorption process. POLYM. ENG. SCI., 54:1960–1968, 2014. © 2013 Society of Plastics Engineers |
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