Interdigitated Electrode for Electrical Characterization of Commercial Pseudo-Binary Biodiesel-Diesel Blends.

Non-standard diesel blends can be harmful to the environment and human health. In this context, a simple analytical method to estimate the biodiesel mixture ratio in diesel was developed based on impedance spectroscopy (IS) associated with interdigitated sensors. In this article, four different interdigitated sensors with varied comb spacing (G) were simulated using the COMSOL Multiphysics software. Based on finite element simulations, four interdigitated electrode architectures were manufactured and evaluated. The best geometry was chosen according to theoretical data simulations, and its interdigitated electrodes were manufactured for the compositional evaluation of pseudo-binary biodiesel-diesel mixtures. According to the X-ray powder diffraction technique, the deposition of the conductive layer (Au0) over the surface of the dielectric substrate (SiO2) did not alter its phase composition. In the analysis of AFM and SEM, it was possible to observe irregular edges on the electrodes, possibly related to the manufacturing process of the thin layers and mechanical stability. Another characteristic observed in the AFM images was the height of the step of the gold layer of the sensor. Several cross sections were obtained, and the mean step value was 225.71 ± 0.0032 nm. Although there were differences in the roughness, the whole sensor had nanometric roughness. Based on the finite element method simulation performed, it can be assumed that the geometric parameters more suitable for the manufacturing of the electrode are W = 20 µm, L = 1000 µm, G = 50 µm, and N = 40 digits. The electrical characterization performed by impedance spectroscopy showed that we could differentiate between biodiesel and diesel fuels and their pseudo-binary mixtures in the low-frequency region.

Zebrafish automatic monitoring system for conditioning and behavioral analysis.

Studies using zebrafish (Danio rerio) in neuro-behavioural research are growing. Measuring fish behavior by computational methods is one of the most efficient ways to avoid human bias in experimental analyses, extending them to various approaches. Sometimes, thorough analyses are difficult to do, as fish can behave unpredictably during an experimental strategy. However, the analyses can be implemented in an automated way, using an online strategy and video processing for a complete assessment of the zebrafish behavior, based on the detection and tracking of fish during an activity. Here, a fully automatic conditioning and detailed analysis of zebrafish behavior is presented. Microcontrolled components were used to control the delivery of visual and sound stimuli, in addition to the concise amounts of food after conditioned stimuli for adult zebrafish groups in a conventional tank. The images were captured and processed for automatic detection of the fish, and the training of the fish was done in two evaluation strategies: simple and complex. In simple conditioning, the zebrafish showed significant responses from the second attempt, learning that the conditioned stimulus was a predictor of food presentation in a specific space of the tank, where the food was dumped. When the fish were subjected to two stimuli for decision-making in the food reward, the zebrafish obtained better responses to red light stimuli in relation to vibration. The behavior change was clear in stimulated fish in relation to the control group, thus, the distances traveled and the speed were greater, while the polarization was lower in stimulated fish. This automated system allows for the conditioning and assessment of zebrafish behavior online, with greater stability in experiments, and in the analysis of the behavior of individual fish or fish schools, including learning and memory studies.