Efficient heavy metal ion removal by fluorographene nanochannel templated molecular sieve: a molecular dynamics simulation study

Author:

Ou Youguan,Gu Zonglin,Luo Yuqi

Abstract

AbstractEnvironmental water contamination, particularly by heavy metal ions, has emerged as a worldwide concern due to their non-biodegradable nature and propensity to accumulate in soil and living organisms, posing a significant risk to human health. Therefore, the effective removal of heavy metal ions from wastewater is of utmost importance for both public health and environmental sustainability. In this study, we propose and design a membrane consisting of fluorographene (F-GRA) nanochannels to investigate its heavy metal ion removal capacity through molecular dynamics simulation. Although many previous studies have revealed the good performance of lamellar graphene membranes for desalination, how the zero-charged graphene functionalized by fluorine atoms (fully covered by negative charges) affects the heavy metal ion removal capacity is still unknown. Our F-GRA membrane exhibits an exceptional water permeability accompanied by an ideal heavy metal ion rejection rate. The superior performance of F-GRA membrane in removing heavy metal ions can be attributed to the negative charge of the F-GRA surface, which results in electrostatic attraction to positively charged ions that facilitates the optimal ion capture. Our analysis of the potential of mean force further reveals that water molecule exhibits the lowest free energy barrier relative to ions when passing through the F-GRA channel, indicating that water transport is energetically more favorable than ion. Additional simulations of lamellar graphene membranes show that graphene membranes have higher water permeabilities compared with F-GRA membranes, while robustly compromising the heavy meal ion rejection rates, and thus F-GRA membranes show better performances. Overall, our theoretical research offers a potential design approach of F-GRA membrane for heavy metal ions removal in future industrial wastewater treatment.

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3