TY - JOUR
T1 - Effect of Noise on Determining Ultrathin-Film Parameters from QCM-D Data with the Viscoelastic Model
AU - Johannsmann, Diethelm
AU - Langhoff, Arne
AU - Leppin, Christian
AU - Reviakine, Ilya
AU - Maan, Anna M.C.
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/2
Y1 - 2023/2
N2 - Quartz crystal microbalance with dissipation monitoring (QCM-D) is a well-established technique for studying soft films. It can provide gravimetric as well as nongravimetric information about a film, such as its thickness and mechanical properties. The interpretation of sets of overtone-normalized frequency shifts, ∆f/n, and overtone-normalized shifts in half-bandwidth, ΔΓ/n, provided by QCM-D relies on a model that, in general, contains five independent parameters that are needed to describe film thickness and frequency-dependent viscoelastic properties. Here, we examine how noise inherent in experimental data affects the determination of these parameters. There are certain conditions where noise prevents the reliable determination of film thickness and the loss tangent. On the other hand, we show that there are conditions where it is possible to determine all five parameters. We relate these conditions to the mathematical properties of the model in terms of simple conceptual diagrams that can help users understand the model’s behavior. Finally, we present new open source software for QCM-D data analysis written in Python, PyQTM.
AB - Quartz crystal microbalance with dissipation monitoring (QCM-D) is a well-established technique for studying soft films. It can provide gravimetric as well as nongravimetric information about a film, such as its thickness and mechanical properties. The interpretation of sets of overtone-normalized frequency shifts, ∆f/n, and overtone-normalized shifts in half-bandwidth, ΔΓ/n, provided by QCM-D relies on a model that, in general, contains five independent parameters that are needed to describe film thickness and frequency-dependent viscoelastic properties. Here, we examine how noise inherent in experimental data affects the determination of these parameters. There are certain conditions where noise prevents the reliable determination of film thickness and the loss tangent. On the other hand, we show that there are conditions where it is possible to determine all five parameters. We relate these conditions to the mathematical properties of the model in terms of simple conceptual diagrams that can help users understand the model’s behavior. Finally, we present new open source software for QCM-D data analysis written in Python, PyQTM.
KW - diffuse double layer
KW - film thickness
KW - high-frequency rheology
KW - polymeric adsorbates
KW - PyQTM
KW - QCM-D
KW - quartz crystal microbalance with dissipation monitoring
KW - thin soft films
KW - viscoelasticity
UR - https://www.scopus.com/pages/publications/85147893292
U2 - 10.3390/s23031348
DO - 10.3390/s23031348
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C2 - 36772387
AN - SCOPUS:85147893292
SN - 1424-8220
VL - 23
JO - Sensors
JF - Sensors
IS - 3
M1 - 1348
ER -