A comparative study of ammonia solubility in imidazolium-based ionic liquids with different structural compositions

Four imidazolium-based ionic liquids (ILs) with two cations 1-pentyl-3-butylimidazolium [PBIM]+ and 1-benzyl-3-butylimidazolium tetrafluoroborate [BzBIM]+, and two anions tetrafluoroborate (BF4-) and trifluoromethanesulfonate (OTf-) were synthesized for NH3 solubility enhancement. The structural, thermal, and electrochemical stabilities, ionic conductivity, and viscosity of the four ILs, namely, [PBIM]BF4, [BzBIM]BF4, [PBIM]OTf, and [BzBIM]OTf, were investigated. Due to the intermolecular interaction of the benzyl group attached to the imidazolium ring, [BzBIM]+-based ILs exhibited higher thermal stability but lower ionic conductivity compared to [PBIM]+-based ILs. Further, the NH3 solubility in all ILs was measured using a custom-made setup at temperatures ranging from 293.15 to 323.15 K and pressures ranging from 1 to 5 bar. The effects of the cation and anion structures of ILs, as well as pressure and temperature, on the NH3 solubility in the ILs were also investigated. [PBIM]BF4 showed the best solubility because of its high free volume and low viscosity. Density functional calculations validated the superior NH3 solubility in [PBIM]BF4, attributable to the minimal reorganization of the [cation]anion complex geometry during the solvation process, yielding a low solvation free energy. The findings of this study suggest that ILs exhibit a high NH3 solubility capacity and cation and anion structures considerably affect the NH3 solubility in ILs.

Prediction of ammonia absorption in ionic liquids based on extreme learning machine modelling and a novel molecular descriptor SEP

The large amounts of ammonia emissions generated from industrial production have caused serious environmental pollution problems, such as soil acidification, eutrophication, the formation of fine particles and changes in the global greenhouse balance, and also greatly endanger human health. At present, effectively reducing ammonia emissions or recovering ammonia is still a huge challenge. Ionic liquids (ILs) as a new class of green solvent have been introduced for ammonia absorption with great potential, but a huge number on combination systems of ILs lead to the difficulty of measuring the ammonia solubility in all ILs by experiments (e.g., danger and cost). Hereby, this study proposed a novel approach for estimating the ammonia solubility in different ILs. A predictive model was developed based on the novel Algorithm - extreme learning machine (ELM) and the molecular descriptors of electrostatic potential surface areas (S_EP) as input parameters. Besides, 502 data points of ammonia solubility in 17 ILs were gathered with a wide range of pressure and temperature. For the total set, the determination coefficient (R²) and the average absolute relative deviation (AARD) of the developed model were 0.9937 and 2.95%, respectively. The regression plots revealed good consistency between predictive and experimental data points. Results show the good performance and reliability of the developed model, indicating that the proposed approach can be potentially applied for screening reasonable ILs to absorb ammonia from chemical industry processes.