Computer-Aided Design of Ionic Liquids as Absorbent for Gas Separation Exemplified by CO₂ Capture Cases

Abstract

In order to design ionic liquids as absorbents for gas separation, a systematic computeraided ionic liquid design (CAILD) methodology is applied and demonstrated by three cases of CO2 capture. Mixed-integer nonlinear programming (MINLP) problems are formulated, where a mass-based Absorption-Selectivity-Desorption index (ASDI) integrating the most important thermodynamic properties of ILs (i.e., gas solubility, selectivity, and desorption capacity) is proposed as the objective function and calculated by the COSMO-GC-IL inputted COSMO-SAC model. The physical properties of ionic liquids are implemented as optimization constraints, which are estimated by semi-empirical models. The reliability of the thermodynamic method for IL-gas systems is validated firstly by comparing a large number of

Unraveling the mechanism of CO2 capture and separation by porous liquids

“…Currently, the capture of CO 2 includes not only solid adsorption, such as with metal organic frameworks (MOFs) [1][2][3] and zeolites, [4][5][6] but also liquid absorption, especially with ionic liquids. [7][8][9][10][11][12] As a new type of material, porous liquids have been a research hotspot since James et al 13 proposed the concept in 2007. In general, porous liquids are divided into three categories.…”

Integrated ionic liquid and rate‐based absorption process design for gas separation: Global optimization using hybrid models

“…Clearly, using the traditional trial-and-error method is inefficient for selecting optimal ILs. 5 So far, many efforts have been made on computational IL screening. For the purpose of IL absorbent screening, various predictive models such as ab initio calculations, equations of state (EOS), and activity coefficient models (e.g., COSMO-RS) have been utilized to estimate the thermodynamic properties of ILs (mainly gas solubility).…”

“…For the purpose of IL absorbent screening, various predictive models such as ab initio calculations, equations of state (EOS), and activity coefficient models (e.g., COSMO-RS) have been utilized to estimate the thermodynamic properties of ILs (mainly gas solubility). [5][6][7][8][9] Although these approaches can efficiently screen ILs with desired properties, they are limited by the number of available IL candidates in the databases. To further expand the search space and find new promising ILs, a systematic approach for IL design is highly necessary.…”

“…However, the number of ILs is almost infinite when considering the large number of anions, cations, and substituent groups. Clearly, using the traditional trial‐and‐error method is inefficient for selecting optimal ILs 5 . So far, many efforts have been made on computational IL screening.…”

“…So far, many efforts have been made on computational IL screening. For the purpose of IL absorbent screening, various predictive models such as ab initio calculations, equations of state (EOS), and activity coefficient models (e.g., COSMO‐RS) have been utilized to estimate the thermodynamic properties of ILs (mainly gas solubility) 5–9 . Although these approaches can efficiently screen ILs with desired properties, they are limited by the number of available IL candidates in the databases.…”