Dataset Information

CO2-Switchable Solvents as Entrainer in Fluid Separations.

ABSTRACT: CO2-switchable solvents, typically neutral solvents that switch with CO2 into ionic species, were investigated for use as entrainer in fluid separations such as extractive distillation. Their switchable nature was investigated, which may facilitate liquid-liquid extraction or extractive distillation as ionic liquid (IL), whereas during regeneration their decarboxylation into the amine form prevents temperature shoot-up. Studied elements included a property screening and detailed mechanistic and kinetic studies on the switching of 2-ethylhexylamine and N,N-benzyl methylamine. Decarboxylation of a 50 vol % switchable solvent, 25 vol % heptane, and 25 vol % toluene mixture at 1.00 × 104 Pa showed a 40% CO2 release before reaching the operational pressure, and total decarboxylation took over 2 h. An effective increase of the relative volatility of heptane/toluene was found, showing that, indeed, CO2-switchable solvents can be applied for extractive distillation. However, low pressure in combination with elevated temperature will lead to quick decarboxylation, limiting the operational window of this class of solvents. Their use in low temperature application such as C4-distillations or liquid-liquid extraction appears more suited.

SUBMITTER: Schuur B

PROVIDER: S-EPMC6092160 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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CO2-Switchable Solvents as Entrainer in Fluid Separations.

Schuur Boelo B Nijland Mart M Blahušiak Marek M Juan Alberto A

ACS sustainable chemistry & engineering 20180629 8

CO2-switchable solvents, typically neutral solvents that switch with CO2 into ionic species, were investigated for use as entrainer in fluid separations such as extractive distillation. Their switchable nature was investigated, which may facilitate liquid-liquid extraction or extractive distillation as ionic liquid (IL), whereas during regeneration their decarboxylation into the amine form prevents temperature shoot-up. Studied elements included a property screening and det ...[more]

PMID: 30123725

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Project description:Metal-organic frameworks (MOFs) have been considered as highly promising materials for adsorption-based CO2 separations. The number of synthesized MOFs has been increasing very rapidly. High-throughput molecular simulations are very useful to screen large numbers of MOFs in order to identify the most promising adsorbents prior to extensive experimental studies. Results of molecular simulations depend on the force field used to define the interactions between gas molecules and MOFs. Choosing the appropriate force field for MOFs is essential to make reliable predictions about the materials' performance. In this work, we performed two sets of molecular simulations using the two widely used generic force fields, Dreiding and UFF, and obtained adsorption data of CO2/H2, CO2/N2, and CO2/CH4 mixtures in 100 different MOF structures. Using this adsorption data, several adsorbent evaluation metrics including selectivity, working capacity, sorbent selection parameter, and percent regenerability were computed for each MOF. MOFs were then ranked based on these evaluation metrics, and top performing materials were identified. We then examined the sensitivity of the MOF rankings to the force field type. Our results showed that although there are significant quantitative differences between some adsorbent evaluation metrics computed using different force fields, rankings of the top MOF adsorbents for CO2 separations are generally similar: 8, 8, and 9 out of the top 10 most selective MOFs were found to be identical in the ranking for CO2/H2, CO2/N2, and CO2/CH4 separations using Dreiding and UFF. We finally suggested a force field factor depending on the energy parameters of atoms present in the MOFs to quantify the robustness of the simulation results to the force field selection. This easily computable factor will be highly useful to determine whether the results are sensitive to the force field type or not prior to performing computationally demanding molecular simulations.

Dataset Information

CO2-Switchable Solvents as Entrainer in Fluid Separations.

Publications

CO<sub>2</sub>-Switchable Solvents as Entrainer in Fluid Separations.

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