Extract Temperature Coefficients of LGS for High-Temperature Applications Based on the Finite Element Method

Surface-acoustic-wave (SAW) sensors with Langasite (LGS) substrate have broad prospects in the field of wireless passive temperature sensing in harsh environments. However, there are still challenges in terms of accuracy regarding the material temperature coefficient of LGS and the temperature simulation of heavy mass load electrodes. This paper presents a method for fitting the material temperature coefficient of LGS based on a combination of finite element simulation (FEM) and measured data. Eleven different cuts of LGS SAW resonators were fabricated, and the frequency response of each cut device at 30–800 °C was obtained through experiments. Some of the data were used in the training dataset and the material temperature coefficient of LGS was obtained through comsol simulation fitting. The remaining data were used as a test dataset to verify the accuracy of the results. The results show that the material coefficient obtained using this method has good accuracy in the frequency prediction of thick electrode LGS SAW sensors at different temperatures with different cuts.