A review on machine learning algorithms for the ionic liquid chemical space

There are thousands of papers published every year investigating the properties and possible applications of ionic liquids. Industrial use of these exceptional fluids requires adequate understanding of their physical properties, in order to create the ionic liquid that will optimally suit the application. Computational property prediction arose from the urgent need to minimise the time and cost that would be required to experimentally test different combinations of ions. This review discusses the use of machine learning algorithms as property prediction tools for ionic liquids (either as standalone methods or in conjunction with molecular dynamics simulations), presents common problems of training datasets and proposes ways that could lead to more accurate and efficient models.

In this review article, the authors discuss the use of machine learning algorithms as tools for the prediction of physical and chemical properties of ionic liquids.     

Design and investigation of UV image detectors

The results of investigation of optical image detectors designed for the largest problem, near-VUV, range of the spectrum are presented. The possibility of using a dual-stage image detection system to appreciably lower the sensitivity threshold and make computer data processing feasible is considered. The integration of a UV module into a wideband image detector is studied.     

Two fluoro compounds of main group elements: Synthesis,characterization, theoretical and spectroscopic study

Two new compounds of fluorine: (C₂H₅)₄N[I₂F] and (C₂H₅)₄N[Br₂F], have been easily synthesized in a nearly quantitative by a direct reaction of (C₂H₅)₄NF, I₂ and Br₂. The products were isolated and characterized by elemental analysis and spectroscopic methods such as: Fourier transform infrared spectroscopy (FTIR) and ultraviolet-visible spectroscopy (UV-Vis). These compounds have been studied computationally with the Scalar ZORA relativistic level of theory using the ADF program package. The molecular parameters, and vibrational spectra were calculated. The excitation energies were found by timedependent perturbation density functional theory (TD-DFT). Molecule optimization, frequencies and excitation energies were calculated with standard Slatertype-orbital (STO) basis sets with triple-zeta quality double plus polarization functions (TZ2P) for all atoms. The FTIR, UV-Vis spectra and assignment of principal transitions and total density of state (TDOS) were extracted using the GaussSum 2.2 program. The comparison between experimental and calculated values showes that the experimental results correlate well with the predicted data.     

Condensation of Diamantan-3-one with Malononitrile and Methyl and Ethyl Cyanoacetates in the Presence of Binder-Free FeHY and NiHy Zeolites

Russian Journal of Organic Chemistry - Binder-free iron- and nickel-containing micro-, meso-, and macroporous zeolites FeHY and NiHY were found to effectively catalyze Knoevenagel condensation of...     

Sulfonamide-Functionalized Porous Organic Framework as an Efficient Heterogeneous Acid Catalyst for One-Pot Preparation of 1,8-Dioxooctahydroxanthenes

Russian Journal of Organic Chemistry - Herein, we report the sulfonamide-functionalized covalent organic framework (COF-SO3H), prepared by condensation of melamine and terephthalaldehyde and...     

Graphene sheet-encased silica/sulfur composite cathode for improved cyclability of lithium-sulfur batteries

Journal of Solid State Electrochemistry - The “shuttle effect” of polysulfides is a serious issue, resulting in a decrease in the life-cycle of lithium-sulfur (Li-S) batteries. To...     

Role of method of synthesis on the size of flakes,dispersion stability and thermophysical properties of aqua based reduced graphene oxide nanofluids

Journal of Thermal Analysis and Calorimetry - The role of method of synthesis on the size of flakes, dispersion stability and thermophysical properties of aqua based reduced graphene oxide (rGO)...