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.

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A green approach for the encapsulation of Mentha pulegium essential oil in commercial baker's yeast and its evaluation as a pesticide against the insect pest Myzus persicae are presented. Upon treating aqueous yeast cell dispersion with the essential oil, the formation of essential-oil-loaded microparticles of about 9 μm is observed, with a loading capacity ranging from 29 to 36%, depending upon the encapsulation conditions. The thermal properties of the microparticles were characterized using differential scanning calorimetry and thermogravimetric analysis, confirming the protection of the essential oil from the cells. Encapsulation prolonged the insecticidal activity of the essential oil by 3 days.

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In this work we investigate the structure – property relationship in a series of alkylimidazolium ionic liquids with almost identical molecular weight. Using a combination of theoretical calculations and experimental...

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Understanding the structure-property relationship and nanoscopic behaviour of ionic liquids is of utmost importance for their potential applications. Focusing these studies on sets of homobaric ionic liquids could provide important...

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