Electrochemical Sensor to Detect Antibiotics in Milk Based on Machine Learning Algorithms.

The present study is dedicated to the problem of electrochemical analysis of multicomponent mixtures, such as milk. A combination of cyclic voltammetry facilities and machine learning techniques made it possible to create a pattern recognition system for the detection of antibiotic residues in skimmed milk. A multielectrode sensor including copper, nickel, and carbon fiber was fabricated for the collection of electrochemical data. Processes occurring at the electrode surface were discussed and simulated with the help of molecular docking and density functional theory modeling. It was assumed that the antibiotic fingerprint reveals a potential drift of electrodes, owing to complexation with metal ions present in milk. The gradient boosting algorithm showed the best efficiency in training the machine learning model. High accuracy was achieved for the recognition of antibiotics in milk. The elaborated method may be incorporated into existing milking systems at dairy farms for monitoring the residue concentrations of antibiotics.

Piezo-Responsive Hydrogen-Bonded Frameworks Based on Vanillin-Barbiturate Conjugates.

A concept of piezo-responsive hydrogen-bonded π-π-stacked organic frameworks made from Knoevenagel-condensed vanillin-barbiturate conjugates was proposed. Replacement of the substituent at the ether oxygen atom of the vanillin moiety from methyl (compound 3a) to ethyl (compound 3b) changed the appearance of the products from rigid rods to porous structures according to optical microscopy and scanning electron microscopy (SEM), and led to a decrease in the degree of crystallinity of corresponding powders according to X-ray diffractometry (XRD). Quantum chemical calculations of possible dimer models of vanillin-barbiturate conjugates using density functional theory (DFT) revealed that π-π stacking between aryl rings of the vanillin moiety stabilized the dimer to a greater extent than hydrogen bonding between carbonyl oxygen atoms and amide hydrogen atoms. According to piezoresponse force microscopy (PFM), there was a notable decrease in the vertical piezo-coefficient upon transition from rigid rods of compound 3a to irregular-shaped aggregates of compound 3b (average values of d33 coefficient corresponded to 2.74 ± 0.54 pm/V and 0.57 ± 0.11 pm/V), which is comparable to that of lithium niobate (d33 coefficient was 7 pm/V).