Equivalent Circuit Model Extraction for a SAW Resonator: Below and above Room Temperature.

In this work, a SAW resonator is characterized in terms of admittance (Y-) parameters in the temperature range spanning from 0 °C to 100 °C, with the aim of highlighting how its physical properties are affected by the temperature change. A lumped-element equivalent-circuit model is used to represent the device under test at the considered temperature conditions and a parameters extraction process based on a Lorentzian fitting is developed for the determination of the equivalent-circuit elements in the investigated temperature range. A very good agreement is observed between the performed measurements and the model simulations. The characterization process and the subsequent equivalent-circuit parameters extraction at different temperature values are described and discussed.

Characterization and Neural Modeling of a Microwave Gas Sensor for Oxygen Detection Aimed at Healthcare Applications.

The studied sensor consists of a microstrip interdigital capacitor covered by a gas sensing layer made of titanium dioxide (TiO2). To explore the gas sensing properties of the developed sensor, oxygen detection is considered as a case study. The sensor is electrically characterized using the complex scattering parameters measured with a vector network analyzer (VNA). The experimental investigation is performed over a frequency range of 1.5 GHz to 2.9 GHz by placing the sensor inside a polytetrafluoroethylene (PTFE) test chamber with a binary gas mixture composed of oxygen and nitrogen. The frequency-dependent response of the sensor is investigated in detail and further modelled using an artificial neural network (ANN) approach. The proposed modelling procedure allows mimicking the measured sensor performance over the whole range of oxygen concentration, going from 0% to 100%, and predicting the behavior of the resonant frequencies that can be used as sensing parameters.

Development and Validation of an ANN-Based Approach for Temperature-Dependent Equivalent Circuit Modeling of SAW Resonators.

In this paper, a novel approach is proposed for modeling the temperature-dependent behavior of a surface acoustic wave (SAW) resonator, by using a combination of a lumped-element equivalent circuit model and artificial neural networks (ANNs). More specifically, the temperature dependence of the equivalent circuit parameters/elements (ECPs) is modeled using ANNs, making the equivalent circuit model temperature-dependent. The developed model is validated by using scattering parameter measurements performed on a SAW device with a nominal resonant frequency of 423.22 MHz and under different temperature conditions (i.e., from 0 °C to 100 °C). The extracted ANN-based model can be used for simulation of the SAW resonator RF characteristics in the considered temperature range without the need for further measurements or equivalent circuit extraction procedures. The accuracy of the developed ANN-based model is comparable to that of the original equivalent circuit model.

On the Performance Evaluation of Commercial SAW Resonators by Means of a Direct and Reliable Equivalent-Circuit Extraction.

Nowadays, surface acoustic wave (SAW) resonators are attracting growing attention, owing to their widespread applications in various engineering fields, such as electronic, telecommunication, automotive, chemical, and biomedical engineering. A thorough assessment of SAW performance is a key task for bridging the gap between commercial SAW devices and practical applications. To contribute to the accomplishment of this crucial task, the present paper reports the findings of a new comparative study that is based on the performance evaluation of different commercial SAW resonators by using scattering (S-) parameter measurements coupled with a Lorentzian fitting and an accurate modelling technique for the straightforward extraction of a lumped-element equivalent-circuit representation. The developed investigation thus provides ease and reliability when choosing the appropriate commercial device, depending on the requirements and constraints of the given sensing application. This paper deals with the performance evaluation of commercial surface acoustic wave (SAW) resonators by means of scattering (S-) parameter measurements and an equivalent-circuit model extracted using a reliable modeling procedure. The studied devices are four TO-39 packaged two-port resonators with different nominal operating frequencies: 418.05, 423.22, 433.92, and 915 MHz. The S-parameter characterization was performed locally around the resonant frequencies of the tested SAW resonators by using an 8753ES Agilent vector network analyzer (VNA) and a home-made calibration kit. The reported measurement-based study has allowed for the development of a comprehensive and detailed comparative analysis of the performance of the investigated SAW devices. The characterization and modelling procedures are fully automated with a user-friendly graphical user interface (GUI) developed in the Python environment, thereby making the experimental analysis faster and more efficient.