Immobilization of Bi2WO6 on Polymer Membranes for Photocatalytic Removal of Micropollutants from Water - A Stable and Visible Light Active Alternative.

In this work, bismuth tungstate Bi2WO6 is immobilized on polymer membranes to photocatalytically remove micropollutants from water as an alternative to titanium dioxide TiO2. A synthesis method for Bi2WO6 preparation and its immobilization on a polymer membrane is developed. Bi2WO6 is characterized using X-ray diffraction and UV-vis reflectance spectroscopy, while the membrane undergoes analysis through scanning electron microscopy, X-ray photoelectron spectroscopy, and degradation experiments. The density of states calculations for TiO2 and Bi2WO6, along with PVDF reactions with potential reactive species, are investigated by density functional theory. The generation of hydroxyl radicals OH• is investigated via the reaction of coumarin to umbelliferone via fluorescence probe detection and electron paramagnetic resonance. Increasing reactant concentration enhances Bi2WO6 crystallinity. Under UV light at pH 7 and 11, the Bi2WO6 membrane completely degrades propranolol in 3 and 1 h, respectively, remaining stable and reusable for over 10 cycles (30 h). Active under visible light with a bandgap of 2.91 eV, the Bi2WO6 membrane demonstrates superior stability compared to a TiO2 membrane during a 7-day exposure to UV light as Bi2WO6 does not generate OH• radicals. The Bi2WO6 membrane is an alternative for water pollutant degradation due to its visible light activity and long-term stability.

Efficient Molecular Dynamics Simulations of Deep Eutectic Solvents with First-Principles Accuracy Using Machine Learning Interatomic Potentials.

In recent years, deep eutectic solvents emerged as highly tunable and ecofriendly alternatives to common organic solvents and liquid electrolytes. In the present work, the ability of machine learning (ML) interatomic potentials for molecular dynamics (MD) simulations of these liquids is explored, showcasing a trained neural network potential for a 1:2 ratio mixture of choline chloride and urea (reline). Using the ML potentials trained on density functional theory data, MD simulations for large systems of thousands of atoms and nanosecond-long time scales are feasible at a fraction of the computational cost of the target first-principles simulations. The obtained structural and dynamical properties of reline from MD simulations using our machine learning models are in good agreement with the first-principles MD simulations and experimental results. Running a single MD simulation is highlighted as a general shortcoming of typical first-principles studies if the dynamic properties are investigated. Furthermore, velocity cross-correlation functions are employed to study the collective dynamics of the molecular components in reline.

Ion Correlation in Choline Chloride-Urea Deep Eutectic Solvent (Reline) from Polarizable Molecular Dynamics Simulations.

In recent years, deep eutectic solvents (DESs) emerged as highly tunable and environmentally friendly alternatives to common ionic liquids and organic solvents. In this work, a polarizable model based on the CHARMM Drude polarizable force field is developed for a 1:2 ratio mixture of choline chloride/urea (reline) DES. To successfully reproduce the structure of the liquid as compared to first-principles molecular dynamics simulations, a damping factor was introduced to correct the observed over-binding between the chloride and the hydrogen bonding site of choline. Investigated radial distributions reveal the formation of hydrogen bonds between all the constituents of reline and similar interactions for chloride and urea's oxygen atoms, which could contribute to the melting point depression of the mixture. Predicted dynamic properties from our polarizable force field are in good agreement with experiments, showing significant improvements over nonpolarizable models. Similar to some ionic liquids, an oscillatory behavior in the velocity autocorrelation function of the anion is visible, which can be interpreted as a rattling motion of the lighter anion surrounded by the heavier cations. The obtained results for ionic conductivity of reline show some degree of correlated ion motion in this DES. However, a joint diffusion of ion pairs cannot be observed during the simulations.

Molecular Features of Reline and Homologous Deep Eutectic Solvents Contributing to Nonideal Mixing Behavior.

Deep eutectic solvents based on choline chloride and a series of urea derivatives are studied by molecular dynamics simulations with the aim to identify molecular features contributing to nonideal mixing behavior of these compounds. In case of reline, a mixture of choline chloride and urea in 1:2 ratio, urea molecules provide sufficient hydrogen bond donor sites to take up the chloride anions into their polar network. Replacing any of the hydrogen atoms of urea by a methyl group strongly pushes the anion to interact with these alkyl chains, resulting in a positive deviation of the activity coefficients of choline chloride compared to reline. Furthermore, the oxygen atom of urea can interact with the nitrogen atom of the cation. This enables the chloride anion to move off-center of the cation toward the hydrogen atom of its hydroxyl group, possessing stronger directional Coulomb interactions than the nitrogen atom of the cation. The substitution of urea's hydrogen atoms in cis position to the carbonyl group as in 1,3-dimethylurea, pushes the newly introduced nonpolar alkyl chains toward the nitrogen atom of the cation. This effect can be responsible for the experimentally observed increase of the activity coefficient of the urea derivative compared to urea. Additionally, indications for formation of nonpolar domains within the liquid and, thus, nanoscale segregation is visible as soon as one hydrogen atom of urea is replaced by an alkyl group.