## 2 Results and Discussion
Hence, the decomposition rates of these substances will depend on their chemical structure. This may result in different molecular structures of the coatings on the surface of QCM sensors prepared by EBD method. Figure 4 shows the typical curve of oscillation frequency difference of the QCM sensor coated by SPNBI-I,III in water relative to the value of its oscillation frequency at the moment of its immersion in water as a function of time. It can be seen that the characteristic time (time constant) for the signal to reach a stationary level is about 1 min. The oscillation  
Figure 3: TGA curves for SPNBI-I,III (1), SPNBI-II,III (2), and SPNBI-IIIV (3) and K (4), Ca (5), and Cr (6) salts of SPNBI-I,III measured at a heating rate of 10 \({}^{\circ}\)C/min in air atmosphere. frequency of the QCM sensors was measured when they were successively immersed into distilled water and into an acetaminophen (APAP) solution. The difference of stationary frequencies is given in Figure 5.  
As can be seen from Figure 4, the oscillation frequency of coated sensors immersed in acetaminophen solution is lower than the frequency of the same sensors immersed in distilled water. This indicates that the acetaminophen molecules in solution are adsorbed on the coating. Higher weight of resonator results in decrease of its oscillation frequency. It should be noted that the frequencies differ markedly and statistically significantly for different coatings. This means that the response of a set of coatings to a specific substance (analyte) is characteristic. Figure 4: Typical curve of oscillation frequency difference (\(\Delta f_{0}=f_{\rm water}(t)-f_{\rm water}(0)\)) of the QCM sensors coated by SPNBI-I,III immersed in water (\(f_{\rm water}(t)\)) relative to the value of its oscillation frequency at the moment of its immersion in water (\(f_{\rm water}(0)\)) as a function of time. Figure 5: The oscillation frequency difference (\(\Delta f=f_{\rm APAP}-f_{\rm water}\)) between QCM sensors coated by SPNBI-I,III and its K, Ca, and Cr salts immersed in acetaminophen solution (\(f_{\rm APAP}\)) and in distilled water (\(f_{\rm water}\)). An important issue is the relationship between sensory response and coating morphology. Atomic force microscopy (AFM) was used for morphology characterization of the coatings. Substrates for AFM from single-crystal silicon wafer as well as QCM sensors were placed in vacuum chamber and simultaneously covered by polymer coatings using EBD method. The coating thickness was calculated from the AFM images, obtained from the silicon substrates, and partly covered by mask during vacuum deposition of the coatings. The thickness of the coatings measured by AFM is given in Figure 6.  
Comparison of the change in the frequency of QCM sensors covered by different coatings and the thickness of the coatings demonstrates that the thickness of the coating plays a significant role in the magnitude of the QCM sensor response. Coatings containing calcium have the highest sensory response. At the same time, although the coatings containing potassium and chromium have the smallest and almost equal thickness, the coatings containing potassium have a significantly higher QCM sensor response, which is almost three times greater than the one of the chromium-containing coatings. This means that both the structure of the polymer, which provides the adsorption properties of the coating, and the thickness of the coating play a role in the formation of the QCM sensors response. The morphology of the coatings obtained using AFM is shown in Figure 7.  
The morphology of the coatings shows a granular structure. The grain size depends on the type of ionomer. Coatings containing calcium have the largest grain size (\(\sim\)30 nm) (Figure 7c). Coatings from SPNBI-I,III and its chromium salts have the smallest grain size (10-15 nm) (Figure 7a,d). Obviously, the grain size affects the adsorption properties of coatings with respect to various analytes.