Prediction of single salt rejection in nanofiltration membranes by independent measurements

被引:20
|
作者
Silva, Veronica [1 ]
Montalvillo, Miguel [1 ]
Javier Carmona, Francisco [2 ]
Palacio, Laura [1 ]
Hernandez, Antonio [1 ]
Pradanos, Pedro [1 ]
机构
[1] Univ Valladolid, Dept Fis Aplicada, Grp Superficies & Mat Porosos, Fac Ciencias, E-47071 Valladolid, Spain
[2] Univ Extremadura, Escuela Politecn, Dept Fis Aplicada, Caceres 10004, Spain
关键词
Impedance spectroscopy; Nanofiltration; Membrane potential; Transport numbers; Dielectric properties; ATOMIC-FORCE MICROSCOPY; COMPOSITE POLYAMIDE RO; DIELECTRIC EXCLUSION; ELECTROLYTE-SOLUTIONS; NF MEMBRANES; PHYSIOCHEMICAL PROPERTIES; COATING LAYER; MODEL; TRANSPORT; CHARGE;
D O I
10.1016/j.desal.2015.12.012
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In this work a method is proposed to predict salt rejection by nanofiltration. The procedure starts from the steric, electric and dielectric exclusion model with charge (and permitivity) depending on the concentration along the pore, SEDE-VCh, for membrane characterization, and substitutes all fitting parameters by values obtained by independent methods. These parameters are the relative permittivity inside the pores and the two constants of the Freundlich isotherm for the volumetric charge density, which can be obtained by impedance spectroscopy techniques. Moreover, the pore size and shape and the active layer thickness are required to complement the model. The pore size was obtained by using a neutral solute rejection test and the active layer thickness was estimated by SEM. Therefore, the model also requires pore shape as input. AFM measurements suggest the assumption of a slit shape for the pores. A Desal-HL membrane has been structurally, electrically and functionally characterized. These data allowed the testing of the predictive model that was subsequently demonstrated; as far as results are good enough considering the complexity of the mechanisms involved. Consequently, it seems clear that once the model parameters have been obtained by independent methods, it can be used as a predictive tool. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 12
页数:12
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