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.     

Solid-phase synthesis of a tyrphostin ether library

The solid-phase synthesis of a 4500-member (30 x 15 x 10) tyrphostin library is demonstrated utilizing the Irori-directed sorting system. Fmoc-protected PL-Rink resin was used as the solid support. After Fmoc-deprotection, aryl aldehydes were attached to the resin through reductive amination. Acylation of the resulting secondary amines with cyanoacetic acid was followed by a Knoevenagel condensation with phenolic aldehydes. Mitsunobu coupling of primary alcohols to the resin-bound phenols yielded the final library of compounds 1.     

Sampled-data minimumH ∞-norm regulation of linear continuous-time systems using multirate-output controllers

This paper deals with the problem of designing multirate-output contrlleers for sampled-dataH -optimal control of linear continuous-time systems. Two formulations of the problem are studied. In the first, the intersample behavior of the disturbance and the controlled output signals is not considered, whereas in the second the continuous-time nature of these signals is taken into account. It is shown that, in both cases and unter appropriate conditions, it is plausible to reduce the repective initial problem to an associated discrete-timeH -optimization problem for which a fictitious static state feedback controller is to be designed. This fact has a beneficial influence on the theoretical and numerical complexity of the problem, since only one algebraic Riccati equation is to be solved here, as compared to two algebraic Riccati equations needed in known techniques concerning theH -optimization problem with dynamic measurement feedback.The work described in this paper has been partially funded by the General Secretariat for Research and Technology of the Greek Ministry of Industry, Research, and Technology and by the Heracles General Cement Company of Greece.     

Efficiency of tributyltin extraction from rhine river sediment

A Rhine river sediment sample was spiked with tributyltin (TBT), equilibrated for ten days and the tributyltin extraction efficiency was optimised using a simplex algorithm. Analysis was effected using hydride generation gas chromatography-atomic absorption spectroscopy (GC-AAS) apparatus. The results show that, in this sediment sample, different molarities of HCl in methanol extract different species with varying extraction efficiencies. The least polar extraction solution extracted TBT more efficiently, whilst DBT and MBT require molar solution of HCl in methanol for efficient extraction.     

Oxygen evolution reaction: a perspective on a decade of atomic scale simulations

Multiple strategies to overcome the intrinsic limitations of the oxygen evolution reaction (OER) have been proposed by numerous research groups. Despite the substantial efforts, the driving force required for water oxidation is largely making the reaction inefficient. In the present work, we collected published studies involving DFT calculations for the OER, with the purpose to understand why the progress made so far, for lowering the overpotential of the reaction, is relatively small. The data revealed that the universal scaling relationship between HO* and HOO* intermediates is still present and robust, despite the variety in methods and structures used for calculating the binding energies of the intermediates. On the other hand, the data did not show a clear trend line regarding the O* binding. Our analysis suggested that trends in doped semiconducting oxides behave very differently from those in other oxides. This points towards a computational challenge in describing doped oxides in a realistic manner. We propose a way to overcome these computational challenges, which can be applied to simulations corresponding to doped semiconductors in general.

Multiple strategies to overcome the intrinsic limitations of the oxygen evolution reaction (OER) have been proposed by numerous research groups.