The modern quartz crystal microbalances (also: "QCM-D" for quartz crystal microbalance with dissipation monitoring) are now widely used. Understanding of the data (shifts of frequency and half bandwidth, Δf and ΔΓ, on a few different harmonics) still is somewhat challenging. For planar layer systems, a standard model predicts the values of Δf and ΔΓ (or of Δf and ΔD with D the "dissipation factor") from a given geometry and given viscoelastic constants. The problem is the inversion. It is often nontrivial to derive statements about the sample from the data sets {Δf, ΔΓ}. Inversion is especially difficult when the viscoelastic parameters depend on frequency and when the layer under study is in a liquid environment. This is the case for many samples of interest (bioadsorbates, in particular). Inversion is difficult, but it is not always impossible. For planar films in air, robust conclusions are possible when the film thickness is between about 20 and 1000 nm. Good models can sometimes be found for films in a liquid, but the conditions cannot be summarized in one sentence.
We have transferred our fit program to Python and made it available on the web.1,2 It is called PyQTM. The source code can be viewed. There is a detailed error analysis. Data files from different platforms can be imported. Fig. 1 shows the user interface. The algorithm, its performance and its limitations are described in [3].
[1] pyQTM software (download)
[2] https://github.com/DJohannsmann/QCM-D-Modelling-PyQTM
[3] Johannsmann, D.; Langhoff, A.; Leppin, C.; Reviakine, I.; Maan, A. M. C., Effect of Noise on Determining Ultrathin-Film Parameters from QCM-D Data with the Viscoelastic Model. Sensors 2023, 23(3), 1348. doi.org/10.3390/s23031348
Below is a collection of materials on the behavior of the quartz crystal microbalance (QCM) in complex environments.
Slides
Software: