膜
材料科学
聚砜
生物相容性
化学工程
聚乙二醇
PEG比率
共聚物
肿胀 的
中空纤维膜
色谱法
纤维
化学
复合材料
聚合物
生物化学
财务
经济
工程类
冶金
作者
Xiang Ying,Shoutian Qiu,Xiangyue Ye,Zhuo Li,Jiemei Zhou,Yong Wang
标识
DOI:10.1016/j.memsci.2024.122457
摘要
Hemodialysis has been used as the primary treatment for patients with end-stage renal disease, however, the current hemodialysis membranes still need complicated modifications to enhance the hemocompatibility and overcome the additive leaching issue. Herein, we prepare hemodialysis hollow-fiber membranes (HFMs) via the melt spinning and selective swelling of the block copolymers of polysulfone (PSF) and polyethylene glycol (PEG), PSF-b-PEG. PSF-b-PEG is first melt-extruded to form dense hollow fibers, and then soaked in selective solvents to transform the PEG microdomains into nanopores following the mechanism of selective swelling-induced pore generation, thus producing HFMs with three dimensionally interconnected porosities. As neither additives nor involatile solvents are involved in the manufacturing process of the HFMs, no elution of any organic matters could be detected for the HFMs during hemodialysis. The HFMs possess a symmetrical structure ensuring tight selectivity, and hydrophilic PEG chains are enriched on the pore surfaces, thus endowing the membranes with enhanced hydrophilicity and durable biocompatibility. We systematically investigate the effect of PEG contents and swelling conditions on pore sizes, porosities, surface properties, and consequently the hemodialysis performance. The optimized HFMs reject >99 % serum albumin while clear ∼70 % middle molecular toxins such as lysozyme and 93–95 % small molecular toxins including urea, phosphate and creatinine. This work provides a strategy to prepare elution-free hemodialysis membranes by taking advantage of selective swelling of block copolymers to balance high protein retaining and high clearance of middle and small molecular toxins, and demonstrates their superiority in hemodialysis performance and safety than conventional membranes.
科研通智能强力驱动
Strongly Powered by AbleSci AI