Issue 47, 2020
From the journal:

New Journal of Chemistry

Solubility predictions through LSBoost for supercritical carbon dioxide in ionic liquids

Yun Zhang ORCID logo *a  and  Xiaojie Xua  

* Corresponding authors

a North Carolina State University, Raleigh, NC 27695, USA
E-mail: yzhang43@ncsu.edu, xxu6@ncsu.edu

Abstract

The solubility of supercritical carbon dioxide in ionic liquids (ILs) is a key parameter for designing chemical processes in a biphasic system. Experimental measurements to determine the molar solubility requires specially-designed apparatus, which may be resource-intensive. Alternatively, predictive models can facilitate the estimation of the solubility by modeling via computational intelligence approaches. In the current work, we develop the least-squares boosting model to predict the solubility of supercritical carbon dioxide in 24 ionic liquids by using critical properties of ILs and biphasic system parameters as descriptors. The model is highly accurate, stable, and promising as a fast, robust, and low-cost tool for solubility estimations.

Graphical abstract: Solubility predictions through LSBoost for supercritical carbon dioxide in ionic liquids

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Article information

DOI
https://doi.org/10.1039/D0NJ03868G
Article type
Paper
Submitted
01 Aug 2020
Accepted
26 Oct 2020
First published
20 Nov 2020

New J. Chem., 2020,44, 20544-20567

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Solubility predictions through LSBoost for supercritical carbon dioxide in ionic liquids

Y. Zhang and X. Xu, New J. Chem., 2020, 44, 20544 DOI: 10.1039/D0NJ03868G

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