甲基叔丁基醚(MTBE)+乙酸(AA)体系等压气液平衡(VLE)数据的测量与相关性分析

IF 2.218 Q2 Chemistry
Priyank Khirsariya , Vyomesh M. Parsana , Kedar Joshi
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引用次数: 0

摘要

醋酸(AA)是工业流程中广泛使用的一种商品化学品,从水溶液中分离醋酸是工业流程中的一个关键环节。甲基叔丁基醚(MTBE)是通过萃取从水溶液中分离纯醋酸最有前途的溶剂之一。要从萃取相中回收 MTBE 溶剂,需要 VLE 数据。本文使用等压 VLE 研究了 MTBE + AA 在 60-90 kPa 范围内的变化。采用 Wilson、NRTL 和 UNIQUAC 等过剩吉布斯能模型来关联 VLE 数据。计算得出的 BIPs 适合于呈现所有压力范围内的 VLE 数据,并且没有观察到共沸物的形成。报告了 Wilson、NRTL 和 UNIQUAC 模型在温度方面的平均绝对偏差。Redlich 和 Kister 的面积检验以及 Wisniak 的 L-W 检验被用来检查实验数据的热力学一致性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Measurement & correlation of isobaric vapor-liquid equilibrium (VLE) data of methyl tert‑butyl ether (MTBE) + acetic acid (AA) system

Measurement & correlation of isobaric vapor-liquid equilibrium (VLE) data of methyl tert‑butyl ether (MTBE) + acetic acid (AA) system

Acetic acid (AA) is extensively used as a commodity chemical in industrial processes and its separation from aqueous solutions is a critical aspect of industrial processes. Methyl tert‑butyl ether (MTBE) is one of the most promising solvents for separating pure acetic acid from its aqueous solution via extraction. To recover MTBE solvent form extract phase, VLE data is required. An isobaric VLE study of MTBE + AA using an ebulliometer in the range of 60–90 kPa is reported in this article. Excess Gibbs energy models such as Wilson, NRTL, and UNIQUAC were used to correlate VLE data. The calculated BIPs were found suitable for presenting the VLE data in all pressure range and no azeotrope formation was observed. Average absolute deviation in temperature for Wilson, NRTL, and UNIQUAC models was reported. Redlich and Kister's area test and Wisniak's L–W test were used to check the thermodynamic consistency of the experimental data.

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来源期刊
Chemical Data Collections
Chemical Data Collections Chemistry-Chemistry (all)
CiteScore
6.10
自引率
0.00%
发文量
169
审稿时长
24 days
期刊介绍: Chemical Data Collections (CDC) provides a publication outlet for the increasing need to make research material and data easy to share and re-use. Publication of research data with CDC will allow scientists to: -Make their data easy to find and access -Benefit from the fast publication process -Contribute to proper data citation and attribution -Publish their intermediate and null/negative results -Receive recognition for the work that does not fit traditional article format. The research data will be published as ''data articles'' that support fast and easy submission and quick peer-review processes. Data articles introduced by CDC are short self-contained publications about research materials and data. They must provide the scientific context of the described work and contain the following elements: a title, list of authors (plus affiliations), abstract, keywords, graphical abstract, metadata table, main text and at least three references. The journal welcomes submissions focusing on (but not limited to) the following categories of research output: spectral data, syntheses, crystallographic data, computational simulations, molecular dynamics and models, physicochemical data, etc.
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