| Literature DB >> 30857103 |
Chunzhen Fan1, Kan Li2, Yi He3, Yalin Wang4, Xufang Qian4, Jinping Jia5.
Abstract
Although many magnetic chitosan materials have been prepared for adsorption of metal ions, there is no standard method for comprehensive evaluation of material performance. The common practice simply compares either adsorption capacity (Q) or saturation magnetization (Ms) of interested materials; however, these two important parameters often work in opposite way. This study aims to establish two methods for evaluation of the overall performance of magnetic materials. The proposed methods consider both heavy metal ion adsorption capacity and magnetic recovery of the material after use. The first method introduces adsorption recovery index (ARI, ARI=Qt), which is calculated using Q and recovery time (t) needed for achieving 98% material recovery. Higher ARI value shows better performance of a magnetic material. The second method uses effort-vector data visualization, in which the position of a magnetic material is shown on a coordinate depicted using normalized Q and Ms value. The distance of the data point to the target (ideal Q and Ms value) indicates the performance of the material. The shorter the distance, the better the overall performance is. Two series of MCBs with different Fe3O4 chitosan mass ratios were prepared by using embedding method and chemical co-precipitation method respectively. They were used as model compounds for investigation of the feasibility of the proposed evaluation methods through adsorption of various metal ions (Ag+, Cu2+, Hg2+, Cr3+ and Cr6+) and MCBs recovery test. The best performers were able to be identified by using both methods and the results agreed with each other. Compared with ARI, the effort-vector data visualization was more straightforward and easier to use. This method was successfully applied to evaluate a wide selection of magnetic materials, including those prepared in this work and reported from literatures, for their overall performance.Entities:
Keywords: Adsorption recovery index; Effort-vector data visualization; Evaluation; Heavy metal ions; Magnetic chitosan
Year: 2018 PMID: 30857103 DOI: 10.1016/j.scitotenv.2018.02.033
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963