Sigma-Profile Database for Using COSMO-Based Thermodynamic Methods

Fortran语言 COSMO-RS公司 西格玛 溶剂化 热力学 计算机科学 隐溶剂化 化学 统计物理学 数据库 物理 量子力学 分子 程序设计语言 离子液体 催化作用 生物化学
作者
Eric Mullins,Richard Oldland,Y. A. Liu,Shu Wang,Stanley I. Sandler,Chau‐Chyun Chen,Michael Zwolak,Kevin C. Seavey
出处
期刊:Industrial & Engineering Chemistry Research [American Chemical Society]
卷期号:45 (12): 4389-4415 被引量:435
标识
DOI:10.1021/ie060370h
摘要

Thermodynamic methods based on conductor-like screening models (COSMO) originated from the use of solvation thermodynamics and computational quantum mechanics. These methods rely on sigma profiles specific to each molecule. A sigma profile is the probability distribution of a molecular surface segment having a specific charge density. Two COSMO-based thermodynamic models are COSMO−RS (realistic solvation) developed by Klamt and his colleagues, and COSMO−SAC (segment activity coefficient) published by Lin and Sandler. Quantum mechanical calculations for generating the sigma profiles represent the most time-consuming and computationally expensive aspect of using COSMO-based methods. A growing number of scientists and engineers are interested in the COSMO-based thermodynamic models but are intimidated by the complexity of performing quantum mechanical calculations. This paper presents the first free, web-based sigma profile database of 1432 compounds. We describe the procedure for sigma profile generation, and we have validated our database by comparing COSMO-based predictions of activity coefficients, normal boiling point and solubility with experimental data and thermodynamic property database. We discuss improvements which include using supplemental geometry optimization software packages to provide good initial guesses for molecular conformations as a precursor to the COSMO calculation. Finally, this paper provides a FORTRAN program and a procedure to generate additional sigma profiles, as well as a FORTRAN program to generate binary phase-equilibrium predictions using the COSMO−SAC model. Our sigma profile database will facilitate predictions of thermodynamic properties and phase behaviors from COSMO-based thermodynamic models.
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