Semi-Automatic System for ZnO Nanoflakes Synthesis via Electrodeposition Using Bioinspired Neuro-Fuzzy Control.

This research presents the development and characterization of a semi-automatic electrophoretic deposition (EPD) system designed for the synthesis of zinc oxide (ZnO) microstructures, utilizing a bioinspired neuro-fuzzy control strategy (ANFIS). The system was designed based on a chemical reactor regulated by electricity in a potentiostate cell to automate and optimize the deposition parameters by controlling the temperature. The synthesized ZnO coatings exhibited distinctive flake-like morphology, confirmed via Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), and Energy-Dispersive X-Ray Spectroscopy (EDS), validating their morphological uniformity and compositional consistency. The implemented ANFIS controller was trained using experimentally acquired data, making a correlation with the properties of the sample, thickness and porosity, also employed as inputs of the system. The system exhibited high accuracy in predicting optimal deposition conditions for ZnO nanoflakes obtention, specifically in the temperature-dependent variations in thickness and porosity employed as reference to establish four classes of working sets based on the density of ZnO flakes in the substrate. Results indicate that the bioinspired neuro-fuzzy control substantially enhances the adaptability and predictive capabilities of the electrophoretic deposition process, making it a versatile tool suitable for various applications requiring precise microstructural characteristics. Future directions include further refinement of the control system, incorporation of digital sensing technologies, and potential expansion of the platform to accommodate other functional materials and complex deposition scenarios.