The electrochemical oxidation of diethylstilbestrol (DES) in acetonitrile

Predicting the formation of NADES using a transformer-based model

The application of natural deep eutectic solvents (NADES) in the pharmaceutical, agricultural, and food industries represents one of the fastest growing fields of green chemistry, as these mixtures can potentially replace traditional organic solvents. These advances are, however, limited by the development of new NADES which is today, almost exclusively empirically driven and often derivative from known mixtures. To overcome this limitation, we propose the use of a transformer-based machine learning approach. Here, the transformer-based neural network model was first pre-trained to recognize chemical patterns from SMILES representations (unlabeled general chemical data) and then fine-tuned to recognize the patterns in strings that lead to the formation of either stable NADES or simple mixtures of compounds not leading to the formation of stable NADES (binary classification). Because this strategy was adapted from language learning, it allows the use of relatively small datasets and relatively low computational resources. The resulting algorithm is capable of predicting the formation of multiple new stable eutectic mixtures (n = 337) from a general database of natural compounds. More importantly, the system is also able to predict the components and molar ratios needed to render NADES with new molecules (not present in the training database), an aspect that was validated using previously reported NADES as well as by developing multiple novel solvents containing ibuprofen. We believe this strategy has the potential to transform the screening process for NADES as well as the pharmaceutical industry, streamlining the use of bioactive compounds as functional components of liquid formulations, rather than simple solutes.

A glassy carbon electrode modified with silver nanoparticles and functionalized multi-walled carbon nanotubes for voltammetric determination of the illicit growth promoter dienestrol in animal urine

An electroanalytical method for determining dienestrol (DNL) in bovine urine samples is described. A glassy carbon electrode (GCE) modified with silver nanoparticles and functionalized multi-walled carbon nanotubes was used as working sensor. The modified GCE displays substantial analytical improvements including an amplified signal, fast electron transfer kinetics, and resistance to fouling. The irreversible oxidation signal of DNL is pH-dependent. Best reactivity is found at pH 3.0, where a typical anodic peak is recorded at 0.8 V (vs. Ag/AgCl). Square-wave voltammetry revealed a 8.4 nM detection limit (1.9 μg L^-1), good repeatability and reproducibility (RSDs <5.0%), and good accuracy (93.2-99.4% recovery from spiked samples). The modified electrode is highly stable even in the presence of ions (Na⁺ and K⁺), urea and uric acid. The electrochemical sensor fulfills all requisites to be used as forensic device in surveillance of illegal livestock practices. Graphical abstract Schematic presentation of the construction of a glassy carbon electrode modified with silver nanoparticles and functionalized multi-walled carbon nanotubes. This sensor exhibited a remarkable performance for voltammetric detection of the illicit growth promoter dienestrol in animal urine.

Insights into the Kinetics of Intermediate Formation during Electrochemical Oxidation of the Organic Model Pollutant Salicylic Acid in Chloride Electrolyte

The present study investigated the kinetics and formation of hydroxylated and chlorinated intermediates during electrochemical oxidation of salicylic acid (SA). A chloride (NaCl) and sulfate (Na2SO4) electrolyte were used, along with two different anode materials, boron doped diamond (BDD) and platinum (Pt). Bulk electrolysis of SA confirmed the formation of both hydroxylated and chlorinated intermediates. In line with the density functional theory (DFT) calculations performed in this study, 2,5- and 2,3-dihydroxybenzoic acid, 3- and 5- chlorosalicylic acid and 3,5-dichlorosalicylic acid were the dominating products. In the presence of a chloride electrolyte, the formation of chlorinated intermediates was the predominant oxidation mechanism on both BDD and Pt anodes. In the absence of a chloride electrolyte, hydroxylated intermediates prevailed on the Pt anode and suggested the formation of sulfonated SA intermediates on the BDD anode. Furthermore, direct oxidation at the anode surface only played a subordinate role. First order kinetic models successfully described the degradation of SA and the formation of the observed intermediates. Rate constants provided by the model showed that chlorination of SA can take place at up to more than 60 times faster rates than hydroxylation. In conclusion, the formation of chlorinated intermediates during electrochemical oxidation of the organic model pollutant SA is confirmed and found to be dominant in chloride containing waters.