纳米技术
分离(统计)
生化工程
材料科学
分离法
环境科学
计算机科学
环境分析
污染物
仿生学
环境污染
环境监测
色谱分离
环境系统
膜
人类健康
膜技术
铅(地质)
有机分子
工艺工程
作者
Defang Ding,Bingquan Qi,Xueqin Luo,Jiaguo Yu,Hansong Cheng,Jian Jin,Lei Jiang,Yu Huang,Fan Xia
出处
期刊:ACS Nano
[American Chemical Society]
日期:2025-11-10
卷期号:19 (46): 39564-39588
标识
DOI:10.1021/acsnano.5c14828
摘要
Industrialization has led to increasingly severe environmental pollution, particularly aquatic environments, posing threats to ecosystems and human health. Researchers propose using bioinspired nanochannel separation membranes for the selective separation of targets in environmental samples, aiming to remove pollutants and recover resources for environmental remediation. Furthermore, nanochannel-based sensors can perform qualitative and quantitative analysis of targets, providing support for the implementation of selective separation processes. The environmental separation and sensing by nanochannel technology are two closely related fields. We consider the improvement of the nanochannel performance, the selectivity and flux for separation, and the sensitivity and specificity for sensing, which follows two general strategies: (1) the fabrication of nanochannels to achieve the desired nano/subnano pore sizes and morphologies and (2) the modification of nanochannels with functional elements. This paper summarizes the research progress of bioinspired nanochannels in environmental separation and sensing over the past 5 years. Separation applications encompass ion separation, small organic molecule separation, and oil-water separation, while sensing applications involve ion sensing and small organic molecule sensing. Additionally, the current research limitations and potential solutions of each application are discussed. Finally, several suggestions for future research directions are proposed. Integrating the environmental separation and sensing based on bioinspired nanochannel technologies can share mutual insights in designing nanochannels and functional elements, driving joint advancements and thereby enhancing their real-world adaptability.
科研通智能强力驱动
Strongly Powered by AbleSci AI