利用庞大的实验数据库，将体积转换重标扰动链统计关联流体理论状态方程应用于纯化合物

IF 3.5 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal Pub Date : 2024-05-15 DOI:10.1002/aic.18466

Jialin Shi, Changxu Wu, Honglai Liu, Huazhou Li

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引用次数: 0

摘要

扰动链统计关联流体理论型状态方程（PC-SAFT-type EOSs）在预测临界区纯化合物性质方面的性能受到了影响。在之前的研究中，我们通过加入无量纲距离函数，引入了一种改进的体积转换重标定 PC-SAFT 状态方程（VTR-PC-SAFT EOS）。这种 VTR-PC-SAFT EOS 建立在基于临界点的 PC-SAFT EOS 基础上，可以再现纯化合物的临界温度、临界压力和临界摩尔体积。研究发现，VTR-PC-SAFT EOS 能显著提高纯化合物在临界和非临界区域的相行为预测精度。在本研究中，我们评估了 VTR-PC-SAFT EOS 在再现 251 种纯化合物临界和非临界特性方面的性能，其中包括 20 种不同的化学物质。测试结果表明，与其他三种 PC-SAFT 型 EOS 相比，VTR-PC-SAFT EOS 可以持续更准确地表示 251 种纯化合物的临界和非临界性质。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Application of volume-translated rescaled perturbed-chain statistical associating fluid theory equation of state to pure compounds using an expansive experimental database

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Application of volume-translated rescaled perturbed-chain statistical associating fluid theory equation of state to pure compounds using an expansive experimental database

The performance of the perturbed-chain statistical associating fluid theory-type equations of state (PC-SAFT-type EOSs) is compromised in predicting properties of pure compounds in the critical region. In our previous research, we introduced an improved volume-translated rescaled PC-SAFT EOS (VTR-PC-SAFT EOS) by incorporating a dimensionless distance-function. Such VTR-PC-SAFT EOS is built based on a critical point-based PC-SAFT EOS that can reproduce the critical temperature, critical pressure, and critical molar volume of pure compounds. VTR-PC-SAFT EOS is found to significantly improve the accuracy of phase behavior predictions in both critical and noncritical regions for pure compounds. In this study, we assess the performance of VTR-PC-SAFT EOS in reproducing the critical and noncritical properties of 251 pure compounds, encompassing 20 distinct chemical species. The testing results indicate that, compared to the other three PC-SAFT-type EOSs, the VTR-PC-SAFT EOS can consistently provide more accurate representations of critical and noncritical properties of 251 pure compounds.

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来源期刊

AIChE Journal 工程技术-工程：化工

CiteScore

7.10

自引率

10.80%

发文量

411

审稿时长

3.6 months

期刊介绍： The AIChE Journal is the premier research monthly in chemical engineering and related fields. This peer-reviewed and broad-based journal reports on the most important and latest technological advances in core areas of chemical engineering as well as in other relevant engineering disciplines. To keep abreast with the progressive outlook of the profession, the Journal has been expanding the scope of its editorial contents to include such fast developing areas as biotechnology, electrochemical engineering, and environmental engineering. The AIChE Journal is indeed the global communications vehicle for the world-renowned researchers to exchange top-notch research findings with one another. Subscribing to the AIChE Journal is like having immediate access to nine topical journals in the field. Articles are categorized according to the following topical areas: Biomolecular Engineering, Bioengineering, Biochemicals, Biofuels, and Food Inorganic Materials: Synthesis and Processing Particle Technology and Fluidization Process Systems Engineering Reaction Engineering, Kinetics and Catalysis Separations: Materials, Devices and Processes Soft Materials: Synthesis, Processing and Products Thermodynamics and Molecular-Scale Phenomena Transport Phenomena and Fluid Mechanics.