%0 Dataset
%T Evaluation of Organic Functionalized Silica Nanoparticles for Heavy Metal Adsorption Dataset (March 2019)
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/0c56714e-3378-43af-a884-626b9bd0ac7f
%W NCDC
%R 10.12072/ncdc.UTCMW.db2163.2022
%A Yang Liming
%K Silica nanoparticles;adsorption materials;surface functionalization
%X Organic functionalized SiO2nanoparticles are considered a promising material for heavy metal adsorption. However, the actual adsorption capacity of specific functional groups on SiO2surfaces is still unclear, which has sparked a debate on which type of organic groups have better affinity for heavy metals. Here, the surface functionalization of SiO2(- EDTA (ethylenediaminetriacetic acid), - COOH, - SO3H, - SH and - NH2) is achieved through a simple silanization reaction. Batch experiments have shown that surface functionalization can significantly improve the adsorption capacity of SiO2. Quantitative analysis shows that grafting 1 mol of EDTA onto the surface of SiO2can adsorb 1.51 mol of Pb (II) ions, which are 7.7, 17.1, 28.4, and 50.2 times higher than COOH-, SO3H-, SH-, and - NH2functionalized SiO2, respectively. This is the first time that the adsorption of functionalized SiO2is evaluated based on each effective functional group, which compensates for the shortcomings of traditional evaluation methods that calculate adsorption per unit mass. The adsorption mechanism of functionalized silica was determined and revealed through experiments and theoretical research. This work not only provides an effective adsorbent for heavy metal remediation, but also offers valuable insights for the evaluation and design of new silica based materials.  Evaluation of the adsorption capacity of organic functionalized silica nanoparticles for heavy metals: quantitative comparison and mechanical insight dataset, obtained using experimental methods, data format in decimal (. xls), data volume of 3 groups, a total of 8640 data points.