Python(编程语言)
计算机科学
水准点(测量)
开源
文档
数据挖掘
程序设计语言
软件
大地测量学
地理
作者
Ian H. Bell,Erik Mickoleit,Chieh‐Ming Hsieh,Shiang‐Tai Lin,Jadran Vrabec,Cornelia Breitkopf,Andreas Jäger
标识
DOI:10.1021/acs.jctc.9b01016
摘要
The COSMO-SAC modeling approach has found wide application in science as well as in a range of industries due to its good predictive capabilities. While other models for liquid phases, as for example UNIFAC, are in general more accurate than COSMO-SAC, these models typically contain many adjustable parameters and can be limited in their applicability. In contrast, the COSMO-SAC model only contains a few universal parameters and subdivides the molecular surface area into charged segments that interact with each other. In recent years, additional improvements to the construction of the sigma profiles and evaluation of activity coefficients have been made. In this work, we present a comprehensive description of how to postprocess the results of a COSMO calculation through to the evaluation of thermodynamic properties. We also assembled a large database of COSMO files, consisting of 2261 compounds, freely available to academic and noncommercial users. We especially focus on the documentation of the implementation and provide the optimized source code in C++, wrappers in Python, and sample sigma profiles calculated from each approach, as well as tests and validation results. The misunderstandings in the literature relating to COSMO-SAC are described and corrected. The computational efficiency of the implementation is demonstrated.
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