Design and optimization for the separation of xylene isomers with a novel double extractants-based extractive distillation

萃取蒸馏 二甲苯 化学 蒸馏 色谱法 分离(统计) 工艺工程 萃取(化学) 有机化学 计算机科学 工程类 甲苯 机器学习
作者
Fangkun Zhang,Yunlong Wang,Cuncheng Ma,Peizhe Cui,Yinglong Wang,Zhaoyou Zhu,Qi Xu
出处
期刊:Journal of Industrial and Engineering Chemistry [Elsevier]
标识
DOI:10.1016/j.jiec.2024.05.027
摘要

Xene is a crucial chemical raw material, serving as a synthetic monomer and solvent extensively employed in coating, medicine, rubber and other industries. It contains of three isomers: o-xylene (OX), m-xylene (MX), and p-xylene (PX), their separation is considered a worldwide challenge due to their extremely close boiling points. A novel extractive distillation based on double extractants is first proposed to separate these isomers in this paper, while it was considered impractical to separate these isomers by distillation technology alone in the past. Through the analysis of residual curve and extractant screening, two potential solvents, i.e., N-Methylpyrrolidone (NMP) and Tetramethylene sulfone (Sul) were used as extractants, and then the separation sequences were designed and optimized. The extractive distillation processes were optimized by sequential iterative method according to the minimum total annual cost (TAC), and the best separation sequence and process parameters were determined. For comparison, it was found that the optimized double extractant-based extractive distillation (DEED) process has the best economic performance with TAC of 5.72*106$, and the energy consumption was greatly reduced by 41.2% compared to the single extractant-based extractive distillation (SEED). This article provides a new perspective on energy-efficient distillation technology for industrial xylene separation and purification production.
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
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
852应助我的djwhjja采纳,获得10
刚刚
所所应助风趣雅柏采纳,获得10
1秒前
万能图书馆应助3dyf采纳,获得10
1秒前
2秒前
ding应助Jzhang采纳,获得10
3秒前
4秒前
4秒前
9527完成签到,获得积分10
5秒前
欢喜大地发布了新的文献求助10
5秒前
早日毕业完成签到,获得积分10
5秒前
6秒前
楚狂接舆完成签到,获得积分10
6秒前
英姑应助怕黑的豌豆采纳,获得10
8秒前
缥缈太清完成签到,获得积分10
8秒前
zgt01发布了新的文献求助10
9秒前
KEHUGE发布了新的文献求助10
10秒前
秃头博士发布了新的文献求助10
11秒前
12秒前
4195183j完成签到,获得积分20
13秒前
13秒前
李子敬完成签到,获得积分10
13秒前
13秒前
欢喜大地完成签到,获得积分10
14秒前
淡然平灵发布了新的文献求助10
15秒前
上官若男应助xy采纳,获得10
17秒前
感动的曼容应助dd36采纳,获得10
17秒前
沐言发布了新的文献求助10
17秒前
17秒前
风趣雅柏发布了新的文献求助10
17秒前
18秒前
阿白完成签到,获得积分10
18秒前
18秒前
情怀应助科研通管家采纳,获得10
20秒前
搜集达人应助科研通管家采纳,获得10
20秒前
Phosphene应助科研通管家采纳,获得10
21秒前
xzy998应助科研通管家采纳,获得10
21秒前
cctv18应助科研通管家采纳,获得10
21秒前
科研通AI2S应助科研通管家采纳,获得10
21秒前
研友_Z34DG8应助科研通管家采纳,获得10
21秒前
英姑应助科研通管家采纳,获得10
21秒前
高分求助中
Mantiden: Faszinierende Lauerjäger Faszinierende Lauerjäger Heßler, Claudia, Rud 1000
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 1000
Natural History of Mantodea 螳螂的自然史 1000
A Photographic Guide to Mantis of China 常见螳螂野外识别手册 800
Autoregulatory progressive resistance exercise: linear versus a velocity-based flexible model 500
Spatial Political Economy: Uneven Development and the Production of Nature in Chile 400
Research on managing groups and teams 300
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3330025
求助须知:如何正确求助?哪些是违规求助? 2959638
关于积分的说明 8596158
捐赠科研通 2637996
什么是DOI,文献DOI怎么找? 1444096
科研通“疑难数据库(出版商)”最低求助积分说明 668934
邀请新用户注册赠送积分活动 656517