Adsorption of uranium (VI) by metal-organic frameworks and covalent-organic frameworks from water

Abstract

As we all know, energy and environment are two everlasting themes for the development of society. Nuclear power source, as a clean energy that is easy to be stored, has been rapidly developed in the past few decades. Because uranium is the main nuclear fuel, mining uranium from seawater is essential. Besides, uranium-containing wastewater discharged by nuclear industry also pose a serious threat for ecological environment. Considering the radioactivity and toxicity of uranium, it is urgent for us to remove U(VI) from wastewater. To achieve these ends, various uranium adsorption materials have been developed. Among them, metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) have aroused wide concern owing to the advantages of high specific surface areas, abundant active adsorption sites and controllable pore structure. However, there is huge room for MOFs and COFs in the application of uranium treatment. Herein, we provide a comprehensive review on MOFs and COFs for the enrichment and removal of U(VI) from seawater and wastewater, including synthetic approach, influencing factors, possible adsorption mechanism, as well as the performance comparison with other materials. In addition, the problem of current research is pointed out and the future direction about MOFs and COFs in uranium treatment is discussed. Noteworthy, a novel recurrent neural network (RNN) model is creatively put forward to connect the adsorption and detection of U(VI). More interestingly, the deep machine learning (ML) algorithm can replace the use of inductively couple plasma optimal emission spectrometry (ICP-OES). The goal of this paper is to provide guidance for the synthesis of novel MOFs and COFs U-adsorbents and broaden their application in the treatment of U(VI).