COSMO-RS Exploration of Highly CO2-Selective Hydrogen-Bonded Binary Liquid Absorbents under Humid Conditions: Role of Trace Ionic Species.

It is critical to improve carbon capture efficiency while reducing costs to popularize carbon capture and storage. Considering the green chemistry and engineering objectives, this study theoretically explores the CO2 absorption capacity of 1,533,528 hydrogen-bonded mixtures, i.e., deep eutectic solvents in a broad sense. Exhaustive statistical thermodynamic calculations well explain the experimental reports; it is confirmed that deep eutectic solvents containing ionic compounds have higher CO2 selective absorption capacity than those composed of non-ionic species. Quantitative evaluation of hydrogen-bonding interaction also predicts that the capacity is higher when the ionic compounds work as hydrogen-bonding donors. This is because the trace ionic species weaken the hydrogen-bonding network in the mixtures to improve CO2 physisorption.

Machine Learning-Boosted Design of Ionic Liquids for CO2 Absorption and Experimental Verification.

Efficient CO2 capture is indispensable for achieving a carbon-neutral society while maintaining a high quality of life. Since the discovery that ionic liquids (ILs; room-temperature molten salts) can absorb CO2, various solvents composed of molecular ions have been studied. However, it is challenging to observe the properties of each isolated ion component to control the function of ILs as they are mixtures of ions. Finding the optimal cation-anion combination for the CO2 absorbent from their enormous chemical space had been impossible in a practical sense. This study applied electronic structure informatics to explore ILs with high CO2 solubility from 402,114 IL candidates. The feature variables were determined by a set of cheap quantum chemistry calculations for isolated small-ion fragments, and the importance of molecular geometries and electronic states governing molecular interactions was identified via the wrapper method. As a result, it was clearly shown that the electronic states of ionic species must have essential roles in the CO2 physisorption capacity of ILs. Considering synthetic easiness for the candidates narrowed by the machine learning model, trihexyl(tetradecyl)phosphonium perfluorooctanesulfonate was synthesized. Using a magnetic suspension balance, it was experimentally confirmed that this IL has higher CO2 solubility than trihexyl(tetradecyl)phosphonium bis(trifluoromethanesulfonyl)amide, which is the previous best IL for CO2 absorption.

Electronic fluctuation difference between trimethylamine N-oxide and tert-butyl alcohol in water.

Although small organic molecules in cells have been considered important to control the functions of proteins, their electronic fluctuation and the intermolecular interaction, which is physicochemical origin of the molecular functions, under physiological conditions, i.e., dilute aqueous solutions (0.18 mol L-1), has never been clarified due to the lack of observation methods with both accuracy and efficiency. Herein, the time evolutions of the interactions in dilute aqueous trimethylamine N-oxide (TMAO) and tert-butyl alcohol (TBA) solutions were analyzed via ab initio molecular dynamics simulations accelerated with the fragment molecular theory. It has been known that TMAO and TBA have similar structures, but opposite physiological functions to stabilize and destabilize proteins. It was clarified that TMAO induced stable polarization and charge-transfer interactions with water molecules near the hydrophilic group, and water molecules were caught even near the CH3- group. Those should affect protein stabilization. Understanding the solution dynamics will contribute to artificial chaperone design in next generation medicine.

Applicability of Effective Fragment Potential Version 2-Molecular Dynamics (EFP2-MD) Simulations for Predicting Dynamic Liquid Properties Including the Supercritical Fluid Phase.

Effective fragment potential version 2-molecular dynamics (EFP2-MD) simulations, where the EFP2 is a polarizable force field based on ab initio electronic structure calculations, were applied to predict the static and dynamic liquid properties of compressed liquid NH3. By analyzing the temperature dependence of the radial distribution function, the autocorrelation functions of velocity ( Cv( t)) and reorientation ( Cr( t)), and the self-diffusion constant, we clarified that the ab initio EFP2 force field can effectively describe the properties of compressed liquids. These descriptions can be performed with at least semiquantitative accuracy and at a sufficiently low computational cost. In the EFP2-MD protocol, no force field training is required. This training is mandatory when simulating liquid properties with classical MD techniques (especially in extreme conditions with high pressures and temperatures). EFP2-MD is a promising technique for predicting the physicochemical properties of novel functional compressed liquids, including supercritical fluid phase properties.