4.7 Article

Analysis of the Effect of Electrode Materials on the Sensitivity of Quartz Crystal Microbalance

Journal

NANOMATERIALS
Volume 12, Issue 6, Pages -

Publisher

MDPI
DOI: 10.3390/nano12060975

Keywords

humidity sensor; quartz crystal microbalance (QCM); graphene oxide (GO); electrode material parameters; mass sensitivity

Funding

  1. National Natural Science Foundation of China [61871098]

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This study investigated the impact of electrode materials on the performance of quartz crystal microbalance (QCM) sensors through theoretical calculations, experimentation, and finite element analysis. The results showed that QCM with gold electrodes had the highest mass sensitivity and better humidity sensitivity compared to those with silver and aluminum electrodes. The simulation indicated that the density and Young's modulus of the electrode material parameters mainly affected sensitivity, providing guidance for optimizing QCM sensor performance and enhancing quantitative analysis capabilities.
This paper investigated the effect of electrode materials on the performance of quartz crystal microbalance (QCM) sensors by means of theoretical calculation, experiment, and finite element analysis methods. First, we calculated the particle displacement amplitude and thus obtained the mass sensitivity function distribution of QCMs with gold, silver and aluminum electrodes, and found that the QCM with the gold electrode has the highest mass sensitivity at the center of the electrode. Then, we tested the humidity-sensing performance of QCMs with gold, silver, and aluminum electrodes using graphene oxide (GO) as the sensitive material, and found that the QCM with the gold electrode has higher humidity sensitivity. Finally, we used the finite element analysis software COMSOL Multiphysics to simulate the specific electrode material parameters that affect the sensitivity of the QCMs. The simulation results show that the density and Young's modulus of the electrode material parameters mainly affect the sensitivity. The results of this paper are instructive for optimizing QCM sensor performance and improving the capability of QCM quantitative analysis.

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