A surface-acoustic-mode aluminum nitride (AlN) transducer is utilized to determine the type of liquid dropped on the propagation path. It is based on tracking the shrinking droplet radius and observing stagnant liquid molecules during and after the liquid evaporation process. The device configuration is suitable to test small amounts of liquids, in the microliter range. According to both mass loading and physical property mechanisms, eight samples of liquids, isopropanol (IPA), ethanol (ETH), deionized-water (DW), tap water (TW), heptane (HEP), propylene glycol monomethyl ether acetate (PGMEA), hexamethyldisilazane (HMDS) and acetone (ACE), which have different equilibrium vapor pressures, molecular weights and boiling points, are accurately detected. The experimental results show that the rate of the change in the energy loss including a slow and fast attenuation region depends on the change of physical properties, such as density, sound speed in liquids and evaporation rate, during the evaporation process. As the evaporation rate of the DW is rather slow, the slow attenuation region occurs for a longer time than the fast one. Consequently, the whole oscillation duration of the attenuation occurs for a longer time, whereas that of the other liquids studied, like ACE, ETH, and IPA, having a faster evaporation rate is shorter. Sensitivities of the surface-acoustic-mode transducer to the evaporation process of liquids such as DW, TW, PGMEA, HMDS, HEP, IPA, ETH and ACE are −29.39, −29.53, −31.79, −34.12, −33.62, −32.87, −32.67, and −32.82 dB μm⁻², respectively. The concentration of stagnant liquid molecules causes a change in the surface mass of the micro-electro-mechanical transducer, which causes a frequency shift and increases the signal noise at the receiver after the liquid evaporation process. The average frequency shifts of ACE, HEP, HMDS, ETH, IPA, PGMEA, TW and DW are 241, 206, 172, 117, 76, 27.3, 11.6 and 0 kHz, respectively, coherent with the type of formed liquid pattern on the device surface, thus allowing to detect liquid samples effectively.

This work presents the mixing wave generation of a novel surface acoustic wave (M-SAW) device for sensing in liquids. Two structures are investigated: One including two input and output interdigital transducer (IDT) layers and the other including two input and one output IDT layers. In both cases, a thin (1 μm) piezoelectric AlN layer is in between the two patterned IDT layers. These structures generate longitudinal and transverse acoustic waves with opposite phase which are separated by the film thickness. A 3-dimensional M-SAW device coupled to the finite element method is designed to study the mixing acoustic wave generation propagating through a delay line. The investigated configuration parameters include the number of finger pairs, the piezoelectric cut profile, the thickness of the piezoelectric substrate, and the operating frequency. The proposed structures are evaluated and compared with the conventional SAW structure with the single IDT layer patterned on the piezoelectric surface. The wave displacement along the propagation path is used to evaluate the amplitude field of the mixing longitudinal waves. The wave displacement along the AlN depth is used to investigate the effect of the bottom IDT layer on the transverse component generated by the top IDT layer. The corresponding frequency response, both in simulations and experiments, is an additive function, consisting of sinc(X) and uniform harmonics. The M-SAW devices are tested to assess their potential for liquid sensing, by dropping liquid medium in volumes between 0.05 and 0.13 μl on the propagation path. The interaction with the liquid medium provides information about the liquid, based on the phase attenuation change. The larger the droplet volume is, the longer the duration of the phase shift to reach stability is. The resolution that the output change of the sensor can measure is 0.03 μl.

Traditional vibration-based damage detection methods often involve human intervention in decision-making, therefore being time-consuming and error-prone. In this study, we propose using Artificial Neural Networks (ANNs) to detect patterns in the structural response and create accurate predictions. The features extracted from the response signal are the Relative Frequency Shifts (RFSs) of the first eight weak-axis bending vibration modes, and the predictions refer to the damage location. To increase the accuracy of the predictions, we propose a novel stacked neural network approach, capable of detecting damage locations with high accuracy. The dataset used for training involves, as input data, the RFSs calculated with an original method for numerous damage locations and severities. The following models were used as building blocks for our stacked approach: Multilayer Perceptron, Recurrent Neural Network, Long Short-term Memory, and Gated Recurrent Units. The entire beam was thus split into segments and each network was trained in this stacked model on one beam segment. All results obtained with the models are also compared to a standard neural network trained on the entire beam. The results obtained show that the model that performs the best contains 14 stacked two-layer feedforward networks.

This paper presents a novel mixing surface acoustic wave (M-SAW) device using multiple Aluminum (Al) interdigital transducer (IDT) layers for liquid sensing applications. The stronger mechanical wave beam generated by the multiple input-IDT layers on the thin film (1 μm) Aluminum Nitride (AlN), consists of different-phase acoustic waves that can travel through a liquid medium. In contrast to the whole signal leaking into liquid medium as in typical SAW devices, the signal obtained at the receiver of the M-SAW device only has a decline in the Rayleigh component. The experimental results show that it is possible to interact with the liquid medium placed on the surface and extract information about the liquid volume based on the phase change. Phase shifts of -16.35°, -11.23°, -4.84°, and -0.86° are obtained for different volumes of demi-water after 10 seconds, 2, 4 and 5 minutes of vaporization, respectively.

This research presents a rigorous investigation into the structural optimisation and material-driven performance enhancement of 3D-printed inertial transducers, specifically focusing on the transition from monolithic thermoplastics to carbon fibre-reinforced composites (PETG-CF). Conventional Polyethylene Terephthalate Glycol (PETG) has been demonstrated functional viability under ambient conditions; however, its susceptibility to temperature-induced mechanical fluctuations and viscoelastic degradation remains a barrier to precision applications. The present study employs integrated modal, harmonic, and thermo-mechanical Finite Element Method (FEM) analysis to delineate the relationship between matrix reinforcement and operational stability across an extended thermal gradient from -40 °C to 100 °C. The analytical model yielded resonant frequencies at ambient temperature of 62.38 Hz for PETG and 102.62 Hz for PETG-CF, demonstrating a high correlation with FEM simulation results of 62.94 Hz and 103.71 Hz, respectively. The simulation results indicate that standard PETG-based transducers exhibit high thermal sensitivity, with the fundamental natural frequency decreasing from 67.1 Hz at −40 °C to 47.0 Hz at 75 °C, representing a linear frequency drift of approximately 0.32 Hz/°C. Conversely, the incorporation of carbon reinforcement (PETG-CF) significantly enhances mechanical resonance performance, achieving a fundamental natural frequency of 103.71 Hz at 25 °C, corresponding to a 65% increase over the baseline (62.945 Hz). The PETG-CF variant demonstrates superior thermal robustness, evidenced by a reduced average frequency shift of approximately 0.26 Hz/°C. The experimental validation of these findings was conducted through the utilisation of free-decay vibration measurements, which substantiated the observations. The resonant frequencies observed were found to be approximately 71 Hz for PETG and 106 Hz for PETG-CF. Static calibration yielded a sensitivity of approximately 108 mV/g. The results obtained establish a practical operational temperature limit between -40 °C and 75 °C, thus providing a fundamental framework for developing high-performance, low-cost micro-sensors through advanced Fused Deposition Modeling (FDM) techniques.