Design of novel polymeric adsorbents for metal ion removal from water using computer-aided molecular design
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- 作者：Rajib Mukherjee ; Berhane Gebreslassie…
- 关键词：Chelating resin ; Heavy metal ions ; Group contribution method (GCM) ; Adsorbate–solid solution theory (ASST) ; Computer ; aided molecular design (CAMD) ; Efficient ant colony optimization (EACO)
- 刊名：Clean Technologies and Environmental Policy
- 出版年：2017
- 出版时间：March 2017
- 年：2017
- 卷：19
- 期：2
- 页码：483-499
- 全文大小：
- 刊物类别：Engineering
- 刊物主题：Sustainable Development; Industrial Chemistry/Chemical Engineering; Industrial and Production Engineering; Environmental Engineering/Biotechnology; Environmental Economics;
- 出版者：Springer Berlin Heidelberg
- ISSN：1618-9558
- 卷排序：19
文摘
Heavy metals in drinking water act as contaminants that can cause serious health problems. These metal ions in drinking water are generally removed using cation exchange resins that are used as adsorbents. Generally, chelating resins with limited adsorption capacity are commercially available. Manufacturing novel resin polymers with enhanced adsorption capacity of metal ion requires ample experimental efforts that are expensive as well as time consuming. To overcome these difficulties, application of computer-aided molecular design (CAMD) will be an efficient way to develop novel chelating resin polymers. In this paper, CAMD based on group contribution method (GCM) has been used to design novel resins with enhanced adsorption capability of removing heavy metal ions from water. A polymer consists of multiple monomer units that repeat in a polymer chain. Each repeat unit of the polymer can be subdivided into different structural and functional groups. The adsorption mechanism of heavy metals on resin depends on the difference between activities in adsorbents and the bulk fluid phase. The contribution of the functional groups in the adsorption process is found by estimating the activity coefficient of heavy metal in the solid phase and bulk phase using a modified version of the UNIFAC GCM. The interaction parameters of the functional groups are first determined and then they are used in a combinatorial optimization method for CAMD of novel resin polymers. In this work, designs of novel resin polymers for the removal of Cu ions from drinking water are used as a case study. The proposed new polymer resin has an order of magnitude higher adsorption capacity compared to conventional resin used for the same purpose.