Three-Dimensionally Printed Resonator with Piezoelectric Actuation and Machine Learning Calibration for In-Line Density–Viscosity Sensing

Three-dimensionally printed cuboid-shaped flow cells featuring a rectangular vibrating plate in one of the sides, actuated by PZT piezoelectric films, were designed, fabricated, and tested. Instead of oscillator circuits based on single resonances, we use the frequency response of the cell in a range with multiple resonances, sensitive to the liquid properties. Machine learning techniques were implemented for training and calibration with water–glycerol mixtures at different temperatures. Various materials, fabrication parameters, and post-treatment processes were investigated. The calibration errors and resolutions are compared for different devices, conditioning circuits, and machine learning algorithms. Our results demonstrate the high potential of the low-cost sensor to monitor density and viscosity in aqueous solutions.