Natural deep eutectic solvents (NADES) may be considered ‘designer solvents’ due to their numerous structural variations and the possibility of tailoring their physicochemical properties. Prior to their industrial application, characterization of NADES is essential, including determination of their physicochemical properties, cytotoxicity, and antioxidative activity. The most important physicochemical properties of eight prepared NADES (choline chloride:malic acid, proline:malic acid, choline chloride:proline:malic acid, betaine:malic acid, malic acid:glucose, malic acid:glucose:glycerol, choline chloride:citric acid, and betaine:citric acid) were measured as functions of temperature and water content. In general, the structure of prepared NADES greatly influences their physical properties, which could be successfully modified and adjusted by addition of water. All tested NADES were absolutely benign and noncorrosive for investigated steel X6CrNiTi18-10. Furthermore, cytotoxicity of prepared solvents was assessed toward three human cell lines (HEK-293T, HeLa, and MCF-7 cells), and antioxidative activity was measured by the Oxygen Radical Absorbance Capacity (ORAC) method. With regard to cell viability, all tested NADES containing carboxylic acid could be classified as practically harmless and considered environmentally safe. The ORAC values indicated that the tested NADES displayed antioxidative activity.

Drying kinetics of convective, vacuum, and microwave drying of a pharmaceutical product, chlorpropamide, has been investigated on a laboratory scale, in the temperature interval from 40 • C to 60 • C, and the range of microwave heating power from 154 W/kg dm to 385 W/kg dm .The experimental data obtained were approximated with the "thin-layer" equation and a two parameter exponential model. In order to compare convective, vacuum, and microwave drying, effective diffusion coefficients and specific heat consumption were calculated for each drying method.Higher rates and shorter drying times were achieved at a higher temperature and microwave heating power. The highest drying rates and the lowest specific heat consumption were achieved with microwave drying. This leads to the conclusion that microwave heating is the most appropriate method for drying of chlorpropamide. The quality of product was not changed for all applied methods.

Different quantities of additives (sodium chloride and oxalic acid) and antisolvent (ethanol) were used in order to define their influence on crystallization of glycine from aqueous solutions. The solubility curves were determined for all process conditions but the nucleation points only for the initial concentration of glycine. The obtained results showed that both the quantity and type of the additive affect the solubility curves, the metastable zone width as well as the granulometric characteristics of crystals (aspect ratio, external shape, and the crystal size distribution). X-ray analysis confirmed occurrences of c-glycine by adding sodium chloride and oxalic acid, regardless of the added mass while the a-polymorphs were achieved by adding ethanol. IntroductionCrystallization is one of the most important methods to obtain pure solid crystalline compounds. In different industries, the most important requirements a crystallized solid-state product has to fulfil are its phase or polymorph stability with respect to thermodynamics and kinetics during its storage life and growth. Additionally, the size distribution determines the product solid-state properties such as separation, flowability, compaction, dissolution, and packing [1].Here, cooling crystallization of glycine from solution in the presence of different additives is investigated. Glycine was chosen as the model system because its solution and solid chemistries have been well studied and characterized and due to the properties of glycine crystals to be crystallized in three different polymorphs. Glycine exists in three crystalline modifications: a-, ß-, and c-forms with different relative stabilities and structures. It is well-known that the least stable form of glycine is the ß-form which transforms readily to the a-or c-form in a humid environment. Although, the a-form is quite stable at room temperature but c-glycine is thermodynamically the most stable form and has some special properties which are important for the pharmaceutical industry (nonlinear optical materials) [2].The crucial factors which yield different polymorphs are the thermodynamic variables (temperature, pressure, and concentration) and the process variables (agitation, supersaturation, seeding, cooling rate, pH values, and additives) [3]. Foreign substances present in the medium, used for the growth of a variety of various substances, have long been recognized to have a profound influence on the external appearance of crystals. Understanding the conditions of occurrence of the polymorphic forms and their transformations from one form into the other would be of great interest and useful for pharmaceutical applications [4].ß-Glycine can be produced under high-supersaturation conditions [5] and is usually crystallized using methanol, ethanol, 2-propanol, or acetone as antisolvent [6][7][8][9]. Pure aqueous solutions lead to the a-form, and the c-form occurs from aqueous solution only in the presence of selected impurities (sodium chloride, sodium hydroxide, sodium fluoride, sodium ni...

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The present work was aimed at investigating the applicability of the proposed correlation equations that link the coefficients of the thin-layer equations. Materials of different properties were chosen and dried in four types of laboratory dryers. The experimental data were approximated applying the commonest thinlayer equations: the Lewis equation, the modified Page's model, and Fick's second law. The best match was achieved with the modified Page's model. The applicability of the stated literature correlations was confirmed. Irrespective of the match between measuring data (X = f(t)) and Lewis equation, the evaluated drying constant K allowed evaluation of the parameters of the employed two-parameter models.