Variable roughness development in statically deposited SiO₂ thin films: a spatially resolved surface morphology analysis

Abstract

For the first time a systematic analysis of the growth front evolution of statically deposited silica films in an atmospheric pressure-plasma enhanced chemical vapour deposition (AP-PECVD) reactor was carried out. The growth front evolution was studied as a function of time and position in the reactor. Focussed beam spectroscopic ellipsometry was used to assess the local film growth rate and atomic force microscopy (AFM) to analyse the surface roughness development. Spatially resolved AFM analysis showed a strong dependence of the rms roughness on the position, and consequently on the thickness and local deposition rate (LDR), in the reactor. Time resolved surface morphology analysis at two specific positions at high and low LDR indicated different growth exponents β = 0.33 and β = 0.11, respectively. From the analysis of the static roughness development in the AP-PECVD reactor certain limitations on the deposition time and the maximum LDR for dynamic or web rolled deposition conditions have been elucidated. Moreover, the system is characterized by a set of roughness exponents α loc = 0.9, α s = 1.6 and global roughness exponent α = 2.3. The different values of α indicate an anomalous scaling behaviour of the system whereas different growth exponents β suggest a breakdown of the anti-shadowing mechanism.

Graphene setting the stage: tracking DNA hybridization with nanoscale resolution

“…we deposited SiO2 steps of 15, 30, 45 and 60 nm on Si wafer substrate (roughness RRMS = 0.18 ± 0.03 nm) and acquired the AFM images shown in Figure S5 (a-e). We verify that the roughness increases exponentially with the thickness (see Figure S5 (f)), as previously reported [15] . We also observe a roughness of 0.36 ± 0.06 @ t = 30 nm, which indicates that the SiO2 roughness is small.…”

Native Silicon Oxide Properties Determined by Doping

“…Figure suggests the physical reason for α modulation: a profile with relatively larger and smoother oscillations (red profile) has a relatively larger α value, while relatively small oscillations forming a more jagged profile (blue profile) has a relatively lower α value . The roughness exponent α, equivalent to the Hurst exponent, is related to the fractal dimension D f of a surface through the simple relationship D f = 3 – α, where, in agreement to the aforementioned observations on the topographic profiles, a larger value of α corresponds to a locally smooth surface, while a smaller one corresponds to more locally jagged morphology. , The α vs N plot in Figure c is therefore inverted in the D f vs N plot.…”

Surface super-roughening driven by spatiotemporally correlated noise

“…This leads to the existence of an independent local roughness exponent α loc that characterizes the local interface fluctuations and differs from the global roughness exponent α obtained by, for instance, the global width. This phenomenon is referred to as anomalous roughening and has received much attention in the last few years because its commonness in experiments [9][10][11][12][13][14][15][16][17][18][19][20][21]. Current theoretical knowledge has firmly established [22] that, indeed, the existence of power-law scaling of the correlation functions (i.e., scale invariance) does not determine a unique dynamic scaling form of the correlation functions.…”

“…This leads to the existence of an independent local roughness exponent α loc that characterizes the local interface fluctuations and diers from the global roughness exponent α obtained by, for instance, the global width. This phenomenon is referred to as anomalous roughening and has received much attention in the last few years because its commonness in experiments [10][11][12][13][14][15][16][17][18][19][20][21][22].…”