Improved RO performance in organic aqueous solutions of methyl-functionalized silica membranes modified by atmospheric-pressure plasma

水溶液 大气压力 大气压等离子体 等离子体 化学工程 聚合膜 化学 有机化学 生物化学 量子力学 海洋学 物理 地质学 工程类
作者
Shun Aoyama,Hiroki Nagasawa,Norihiro Moriyama,Masakoto Kanezashi,Toshinori Tsuru
出处
期刊:Journal of Membrane Science [Elsevier BV]
卷期号:705: 122898-122898 被引量:2
标识
DOI:10.1016/j.memsci.2024.122898
摘要

The development of an effective organic solvent recovery process via reverse osmosis (RO) is an emerging issue for sustainable chemical industries. Organosilica membranes are key candidates for the dehydration of aqueous organic solvent solutions by RO owing to their high mechanical strength and excellent resistance to water and organic solvents. In this study, the pore size and surface affinity of an organosilica membrane were adjusted through atmospheric-pressure plasma surface modification to improve membrane selectivity while maintaining H2O permeance. The membranes were evaluated in various aqueous solution systems, ranging from alcohols, such as MeOH, EtOH, IPA, and t-BuOH, to aprotic organic solvents, including acetonitrile, N,N-dimethylformamide, N,N-dimethylacetamide, N-methyl-2-pyrrolidone, and acetone. These membranes exhibited excellent stability at high pressures (∼12.5 MPa) in the H2O/solvent = 95/5%–85/15% concentration range. Plasma modification markedly enhanced the selectivity while maintaining H2O permeance in all systems owing to the controlled pore size and affinity. For instance, in the H2O/DMF (90/10 wt%) system at 50°C and 6 MPa, the pristine and plasma-modified organosilica membranes had similar H2O fluxes of 1.0 and 1.2 kg m−2 h−1, and plasma modification increased the rejection from 85% to 95%. In addition, an activity-based permeation model was used to analyze permeation properties. The experimental points were successfully fitted with the theoretical curves, which revealed that the RO performance of the plasma-modified membranes could be predicted accurately by the activity-based permeation model.
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