4.7 Review

An overview of graphene-based nanoadsorbent materials for environmental contaminants detection

期刊

TRAC-TRENDS IN ANALYTICAL CHEMISTRY
卷 139, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.trac.2021.116255

关键词

Graphene; Nanoadsorbent; Extraction materials; Sample pretreatment; Environmental analysis

资金

  1. National Natural Science Foundation of China [21906124, 31901766]
  2. Natural Science Foundation of Hubei Province

向作者/读者索取更多资源

Graphene and its composites have attracted extensive research interests due to their unique properties, making them promising candidates for efficient adsorbents and playing an important role in the development of new extraction methods for environmental analysis. Recent advances in graphene-based extraction materials have shown great potential for detecting trace contaminants in complex environmental matrices, but future challenges in developing graphene-based nanocomposite materials for environmental analysis need to be addressed.
Due to their unique porous structure, ultrahigh specific surface area, excellent mechanical/thermal stability, sufficient active sites and controllable surface properties, graphene-based composite materials have attracted extensive research interests in recent years. These remarkable performances make graphene and its composites promising candidates as efficient adsorbents for sample pretreatment, which have played an important role in the development of new extraction methods for environmental analysis. This article specifically reviews the latest advances in graphene-based extraction materials and their applications for the detection of trace contaminants from complex environmental matrices, including pesticides, polycyclic aromatic hydrocarbons, metal contamination, phthalate esters and antibiotic. Furthermore, future challenges in the development of graphene-based nanocomposite materials for environmental analysis are also put forward. (c) 2021 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据