2021
DOI: 10.1016/j.mseb.2021.115090
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Evaluation of nanostructured BiZn0.5Ti0.5O3 thin films deposited by RF magnetron sputtering

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Cited by 15 publications
(9 citation statements)
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“…According to the feature presented and discussed above in Figure 7a, we see in Figure 6b that all the samples presented a relatively small (below 5%) perceptual fraction of outliers ( f out ) in the L RMS ( x , y ) distribution, whose average values are 0.029 (BK7), 0.008 (Si), and 0.004 (Glass), indicating that all the roughness is still uniformly distributed locally. The overall consonance between the results ranging from the global scale ( E ~ 1) (Matos et al, 2018) and the local scale ( f out < < 1) (Romaguera‐Barcelay, Pedraça, et al, 2021) provide evidence that deposition of the Cr films on the set of samples is able to form correlated surfaces with multiscale level of uniformity of the roughness over the surface. Such features are in line with the absence of sudden changes in the Height distribution and Abbott‐Firestone curves shown in Figure 4a, b.…”
Section: Resultsmentioning
confidence: 79%
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“…According to the feature presented and discussed above in Figure 7a, we see in Figure 6b that all the samples presented a relatively small (below 5%) perceptual fraction of outliers ( f out ) in the L RMS ( x , y ) distribution, whose average values are 0.029 (BK7), 0.008 (Si), and 0.004 (Glass), indicating that all the roughness is still uniformly distributed locally. The overall consonance between the results ranging from the global scale ( E ~ 1) (Matos et al, 2018) and the local scale ( f out < < 1) (Romaguera‐Barcelay, Pedraça, et al, 2021) provide evidence that deposition of the Cr films on the set of samples is able to form correlated surfaces with multiscale level of uniformity of the roughness over the surface. Such features are in line with the absence of sudden changes in the Height distribution and Abbott‐Firestone curves shown in Figure 4a, b.…”
Section: Resultsmentioning
confidence: 79%
“…According to the feature presented and discussed above in Figure 7a, we see in Figure 6b that all the samples presented a relatively small (below 5%) perceptual fraction of outliers (f out ) in the L RMS (x, y) distribution, whose average values are 0.029 (BK7), 0.008 (Si), and 0.004 (Glass), indicating that all the roughness is still uniformly distributed locally. The overall consonance between the results ranging from the global scale (E $ 1) (Matos et al, 2018) and the local scale (f out < < 1) (Romaguera- Barcelay, Pedraça, et al, 2021) provide evidence that deposition of the Cr films on the set of samples is able to form correlated surfaces with In Figure 8 it is clear that the previously mentioned multiscale uniformity of the roughness also leaves signatures on the log-log plot of the lacunarity where we see a satisfactory power-law fit with high values of R 2 (measure of the goodness of the fit). Such power-law for the fractal lacunarity (FL) highlights that, during the stochastic deposition, the substrates support the emergence of hierarchical roughness across several scales, which is in agreement with the non-Gaussian behavior detected in Figure 4 and Table 2, and the fractal measures shown in Figure 6.…”
Section: Lrms X Ymentioning
confidence: 77%
“…As an important qualitative observation tool available in MountainsMap and widely used for the evaluation of surface microtextures of thin films or other systems [25,[53][54][55][56][57], the renderings of the surface microtexture shown in Figure 2 reveal contour lines and furrows belonging to each analyzed sample. As seen in Figure 2(e) (contour lines), the grain appears to have a ricelike shape, which can also be seen in Figure S1, while the smoother morphology of LuMnO650 and LuMnO750 reveal grain clusters' minors who have not coalesced.…”
Section: Microtexture Analysismentioning
confidence: 99%
“…The fractal succolarity (FS) measures the degree of fluid penetration of a surface that can be estimated by the box-counting algorithm. In the present work, we have calculated FS using eq , where P 0 ( n ) is the number of boxes/line, P r ( k ) is the abscissa of the pressure centroid related to each box that occupies the image, and P 0 ( k ) is the number of occupied boxes/line. , Similar to Melo and Conci, we use boxes of 1 pixel × 1 pixel covering the image. The fluid inlet direction is considered from top to bottom, where the centroid pressure is positioned at the central point of the boxes: …”
Section: Computational Details: Advanced Fractal Parametersmentioning
confidence: 99%