MolPipeline: A Python Package for Processing Molecules with RDKit in Scikit-learn.

The open-source package scikit-learn provides various machine learning algorithms and data processing tools, including the Pipeline class, which allows users to prepend custom data transformation steps to the machine learning model. We introduce the MolPipeline package, which extends this concept to cheminformatics by wrapping standard RDKit functionality, such as reading and writing SMILES strings or calculating molecular descriptors from a molecule object. We aimed to build an easy-to-use Python package to create completely automated end-to-end pipelines that scale to large data sets.

Structure and Dynamics of Aqueous 2-Aminothiazole/NaCl Electrolytes at Electrified Interfaces.

A computational study was performed to investigate the dynamics of aqueous electrolytes containing organic corrosion inhibitors near electrified interfaces by using the constant-charge model in classical molecular dynamics simulations. The results showed that when inhibitors form films at the interface, the surface charge of the electrode causes displacement of the molecules, referred to as electroporation. The hydrophobicity of the inhibitor molecules affects both the stability of the films and their recovery time.

ConfSolv: Prediction of Solute Conformer-Free Energies across a Range of Solvents.

Predicting Gibbs free energy of solution is key to understanding the solvent effects on thermodynamics and reaction rates for kinetic modeling. Accurately computing solution free energies requires the enumeration and evaluation of relevant solute conformers in solution. However, even after generation of relevant conformers, determining their free energy of solution requires an expensive workflow consisting of several ab initio computational chemistry calculations.

Analyzing Learned Molecular Representations for Property Prediction.

Advancements in neural machinery have led to a wide range of algorithmic solutions for molecular property prediction. Two classes of models in particular have yielded promising results: neural networks applied to computed molecular fingerprints or expert-crafted descriptors and graph convolutional neural networks that construct a learned molecular representation by operating on the graph structure of the molecule. However, recent literature has yet to clearly determine which of these two methods is superior when generalizing to new chemical space.

Homoleptic borates and aluminates containing the difluorophosphato ligand - [M(O2PF2)x](y-) - synthesis and characterization.

Weakly coordinating anions (WCAs) with the difluorophosphato ligand (O2PF2) were the target of this study. Initial experiments were conducted towards the preparation of homoleptic aluminates of the well-studied [Al(OR)4](-)-type. The preparation of the initial target structure Li[Al(O2PF2)4] failed due to the remaining Lewis acidic character of the central aluminum atom.

Li[B(OCH2CF3)4]: synthesis, characterization and electrochemical application as a conducting salt for LiSB batteries.

A new Li salt with views to success in electrolytes is synthesized in excellent yields from lithium borohydride with excess 2,2,2-trifluorethanol (HOTfe) in toluene and at least two equivalents of 1,2-dimethoxyethane (DME). The salt Li[B(OTfe)4 ] is obtained in multigram scale without impurities, as long as DME is present during the reaction. It is characterized by heteronuclear magnetic resonance and vibrational spectroscopy (IR and Raman), has high thermal stability (Tdecomposition >271 °C, DSC) and shows long-term stability in water.

Modeling the influence of salts on the critical micelle concentration of ionic surfactants.

We show for the first time that a phenomenological, augmented volume-based thermodynamics (aVBT) model is capable to predict the critical micelle concentrations of ionic surfactants, including ionic liquids, with added salts. The model also adjusts for the type of salt added by including its molecular volume, which might form a connection to the Hofmeister effect. The other physico-chemically relevant quantities included in the model include surface area and solvation enthalpies.

Establishing consistent van der Waals volumes of polyatomic ions from crystal structures.

Based on temperature (T) dependent crystal structure data of seven organic salts, a radii-based scheme for the calculation of the van der Waals volume (V(vdw)) is analyzed. The obtained volumes (V(vdw,r), r=radius-based) are nearly T independent. An ion volume partitioning scheme is proposed by fixing the anion volumes of [Cl](-), [Br](-), [I](-), [BF(4)](-), [PF(6)](-), [OTf](-) and [NTf(2)](-).

Temperature dependence of the viscosity and conductivity of mildly functionalized and non-functionalized [Tf2N](-) ionic liquids.

A series of bis(trifluoromethylsulfonyl)imide ionic liquids (ILs) with classical as well as mildly functionalized cations was prepared and their viscosities and conductivities were determined as a function of the temperature. Both were analyzed with respect to Arrhenius, Litovitz and Vogel-Fulcher-Tammann (VFT) behaviors, as well as in the context of their molecular volume (V(m)). Their viscosity and conductivity are highly correlated with V(m)/T or related expressions (R(2) ≥0.

In silico predictions of the temperature-dependent viscosities and electrical conductivities of functionalized and nonfunctionalized ionic liquids.

The viscosity (η) and electrical conductivity (κ) of ionic liquids are, next to the melting point, the two key properties of general interest. The knowledge of temperature-dependent η and κ data before their first synthesis would permit a much more target-oriented development of ionic liquids. We present in this work a novel approach to predict the viscosity and electrical conductivity of an ionic liquid without further input of experimental data.

An experimental and theoretical study of the aluminium species present in mixtures of AlCl3 with the ionic liquids [BMP]Tf2N and [EMIm]Tf2N.

It is known that nano- or microcrystalline aluminium may be electrodeposited from mixtures of AlCl(3) and the ionic liquids 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)amide ([BMP]Tf(2)N) and 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)amide ([EMIm]Tf(2)N), and that two phases form with higher formal concentrations of AlCl(3) (at 1.6 mol L(-1) (x(Al)=0.33) and 2.