Efficient Adsorption of Arsenic from Smelting Wastewater by CoMn-MOF-74 Bimetallic Composites

双金属片 吸附 废水 冶炼 材料科学 废物管理 冶金 复合材料 化学 工程类 金属 有机化学
作者
Junwei Feng,Gang Zhi,Xianjin Qi,Mengmeng Geng
出处
期刊:Sustainability [Multidisciplinary Digital Publishing Institute]
卷期号:17 (7): 3060-3060
标识
DOI:10.3390/su17073060
摘要

Removing arsenic from industrial wastewater remains a crucial task. To protect public health and safety and address environmental pollution, there is an urgent need for a material that can efficiently remove arsenic from wastewater. In this study, a simple and highly efficient adsorbent, namely, a Co/Mn bimetallic-based organic framework (CoMn-MOF-74) adsorbent, was prepared by a hydrothermal synthesis method. Experimental results demonstrate that CoMn-MOF-74 exhibits excellent adsorption capacity for arsenic ions in wastewater. It was found that the optimal Co/Mn molar ratio of the adsorbent is 1:1. The CoMn-MOF-74 adsorbent compensates for the deficiencies in the adsorption performance of Co-MOF-74 and Mn-MOF-74, increasing the adsorption rate and the highest adsorption capacity. The maximum adsorption rate of CoMn-MOF-74 is 93.4%, and the highest adsorption capacity is 531 mg/g. Fitting CoMn-MOF-74 according to two categories of models, specifically, the adsorption isotherm and adsorption kinetics models, indicated that CoMn-MOF-74 adheres to the Langmuir model and pseudo-second-order kinetic model. The adsorption process is mainly chemical adsorption and monolayer adsorption. Analysis by XPS revealed that metal–oxygen groups and hydroxyl groups play important roles in the adsorption process. In conclusion, the CoMn-MOF-74 adsorbent shows excellent prospects in the field of arsenic adsorption from wastewater and is a promising arsenic-removing adsorbent.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
hansJAMA发布了新的文献求助20
1秒前
3秒前
追寻的身影完成签到,获得积分10
4秒前
5秒前
科研通AI6.2应助wk有若采纳,获得10
5秒前
hanyun完成签到,获得积分10
5秒前
5秒前
xiaoyi发布了新的文献求助10
6秒前
七因发布了新的文献求助10
7秒前
9秒前
10秒前
10秒前
10秒前
月月鸟发布了新的文献求助10
11秒前
爆米花应助djking采纳,获得10
11秒前
岚叶应助科研通管家采纳,获得10
13秒前
害羞白云应助科研通管家采纳,获得10
13秒前
molihuakai应助科研通管家采纳,获得10
13秒前
桐桐应助科研通管家采纳,获得10
13秒前
Hello应助科研通管家采纳,获得10
13秒前
ding应助科研通管家采纳,获得10
13秒前
Hello应助科研通管家采纳,获得10
13秒前
13秒前
传奇3应助科研通管家采纳,获得10
14秒前
脑洞疼应助科研通管家采纳,获得10
14秒前
完美巧凡应助科研通管家采纳,获得10
14秒前
orixero应助科研通管家采纳,获得10
14秒前
小肥发布了新的文献求助10
14秒前
菜菜鱼完成签到,获得积分10
15秒前
15秒前
书雁完成签到,获得积分10
16秒前
Copper_Yu发布了新的文献求助10
16秒前
16秒前
尤里有气发布了新的文献求助10
16秒前
17秒前
沉静胜完成签到,获得积分10
18秒前
张慧华完成签到,获得积分10
18秒前
Jasmine完成签到,获得积分10
18秒前
19秒前
rtf完成签到,获得积分10
19秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Markov Chain Monte Carlo 5000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Evidence Summary. Injection (subcutaneous):op- timal administration 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7494468
求助须知:如何正确求助?哪些是违规求助? 9085858
关于积分的说明 19377892
捐赠科研通 7106325
什么是DOI,文献DOI怎么找? 3249711
关于科研通互助平台的介绍 2419139
邀请新用户注册赠送积分活动 2235461