硫醇在烃类和碱性水溶液中的扩散系数

IF 2.4 3区 工程技术 Q3 CHEMISTRY, MULTIDISCIPLINARY
Journal of Chemical & Engineering Data Pub Date : 2026-10-08 Epub Date: 2026-09-23 DOI:10.1021/acs.jced.6c00232
Nikolay Madaminov, Alexander Razinov, Alexander Klinov, Victor Arkhipov, Ivan Anashkin, Ruslan Arkhipov, Renat Akhmadullin
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引用次数: 0

摘要

本研究考察了乙烷硫醇和正丙硫醇在模型烃相(正戊烷和正辛烷)和碱相(氢氧化钠和氢氧化钾溶液)中的扩散系数。理论分析表明,在低硫醇浓度下,多组分扩散矩阵降低到爱因斯坦自扩散系数,支持它们在相间传质模型中的应用。通过核磁共振扩散法和分子动力学模拟测定了硫醇扩散系数。对Wilke-Chang方程和lusis - ratcliffe方程的预测性能进行了评价,并预测了烃混合物中硫醇在无限稀释下的扩散系数。结果表明,这些计算方法可用于预测硫醇脱除过程传质模型中的硫醇扩散系数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diffusion Coefficients of Thiols in Hydrocarbon and Aqueous Alkaline Solutions

This study examines the diffusion coefficients of ethanethiol and n-propanethiol in model hydrocarbon phases (n-pentane and n-octane) and aqueous alkaline phases (NaOH and KOH solutions). A theoretical analysis shows that, at low thiol concentrations, the multicomponent diffusion matrices reduce to the Einstein self-diffusion coefficients, supporting their use in interphase mass-transfer modeling. Thiol diffusion coefficients were determined by NMR diffusometry and molecular dynamics simulations. The predictive performance of the Wilke–Chang and Lusis–Ratcliff equations was also evaluated, and thiol diffusion coefficients at infinite dilution in hydrocarbon mixtures were predicted. The results show that these computational approaches can be used to predict thiol diffusion coefficients for mass-transfer modeling of thiol-removal processes.

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来源期刊
Journal of Chemical & Engineering Data
Journal of Chemical & Engineering Data 工程技术-工程:化工
CiteScore
5.20
自引率
19.20%
发文量
324
审稿时长
2.2 months
期刊介绍: The Journal of Chemical & Engineering Data is a monthly journal devoted to the publication of data obtained from both experiment and computation, which are viewed as complementary. It is the only American Chemical Society journal primarily concerned with articles containing data on the phase behavior and the physical, thermodynamic, and transport properties of well-defined materials, including complex mixtures of known compositions. While environmental and biological samples are of interest, their compositions must be known and reproducible. As a result, adsorption on natural product materials does not generally fit within the scope of Journal of Chemical & Engineering Data.
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