Defining the optimal conditions using FFNNs and NARX neural networks for modelling the extraction of Sc from aqueous solution by Cryptand-2.2.1 and Cryptand-2.1.1

The main aim of this study is to figure out how well cryptand-2.2.1 (C 2.2.1) and cryptand-2.1.1 (C 2.1.1) macrocyclic compounds (MCs) work as novel extractants for scandium (Sc) by using an artificial neural network (ANN) models in MATLAB software. Moreover, C2.2.1 and C2.1.1 have never been evaluated to recover Sc. The independent variables impacting the extraction process (concentration of MC, concentration of Sc, pH, and time), and a nonlinear autoregressive network with exogenous input (NARX) and feed-forward neural network (FFNN) models were used to estimate their optimum values. The greatest obstacle in the selective recovery process of the REEs is the similarity in their physicochemical properties, specifically their ionic radius. The recovery of Sc from the aqueous solution was experimentally evaluated, then the non-linear relationship between those parameters was predictively modeled using (NARX) and (FFNN). To confirm the extraction and stripping efficiency, an atomic absorption spectrophotometer (AAS) was employed. The results of the extraction investigations show that, for the best conditions of 0.008 mol/L MC concentration, 10 min of contact time, pH 2 of the aqueous solution, and 75 mg/L Sc initial concentration, respectively, the C 2.1.1 and C 2.2.1 extractants may reach 99 % of Sc extraction efficiency. Sc was recovered from a multi-element solution of scandium (Sc), yttrium (Y), and lanthanum (La) under these circumstances. Whereas, at a concentration of 0.3 mol/L of hydrochloric acid, the extraction of Sc was 99 %, as opposed to Y 10 % and La 7 %. The Levenberg-Marquardt training algorithm had the best training performance with an mean-squared-error, MSE, of 5.232x10-6 and 6.1387x10-5 for C 2.2.1 and C 2.1.1 respectively. The optimized FFNN architecture of 4-10-1 was constructed for modeling recovery of Sc. The extraction process was well modeled by the FFNN with an R2 of 0.999 for the two MC, indicating that the observed Sc recovery efficiency consistent with the predicted one.

Bistren cryptands and cryptates: versatile receptors for anion inclusion and recognition in water

Bistren cryptands can be easily synthesised through the Schiff base condensation of two molecules of tren and three molecules of a dialdehyde, followed by hydrogenation of the six C=N double bonds to give octamine cages, whose ellipsoidal cavity can be varied at will, by choosing the appropriate dialdehyde, in order to include substrates of varying sizes and shapes. Bistrens can operate as effective anion receptors in two ways: (i) in their protonated form, providing six secondary ammonium groups capable of establishing hydrogen bonding interactions with the anion; (ii) as dicopper(II) cryptates, in which the two coordinatively unsaturated metal centres can be bridged by an ambidentate anion. Representative examples of the two approaches, as well as the design of an anion molecular dispenser, in which a dicopper(II) bistren cryptate acts as a bottle will be illustrated.

Kinetic buffers

This paper proposes a new type of molecular device that is able to act as an inverse proton sponge to slowly decrease the pH inside a reaction vessel. This makes the automatic monitoring of the concentration of pH-sensitive systems possible. The device is a composite formed of an alkyl chloride, which kinetically produces acidity, and a buffer that thermodynamically modulates the variation in pH value. Profiles of pH versus time (pH-t plots) have been generated under various experimental conditions by computer simulation, and the device has been tested by carrying out automatic spectrophotometric titrations, without using an autoburette. To underline the wide variety of possible applications, this new system has been used to realize and monitor HCl uptake by a di-copper(II) bistren complex in a single run, in a completely automatic experiment.