Assessing conformal thin film growth under nonstochastic deposition conditions: application of a phenomenological model of roughness replication to synthetic topographic images

Abstract

In this work, a simple method to follow the evolution of the surface of thin films during growth on substrates characterised by high roughness is detailed. To account for real cases as much as possible, the approach presented is based on the hypothesis that deposition takes place under nonstochastic conditions, such as those typical of many thin film processes in industry and technology. In this context, previous models for roughness replication, which are mainly based on idealised deposition conditions, cannot be applied and thus ad hoc approaches are required for achieving quantitative predictions. Here it is suggested that under nonstochastic conditions a phenomenological relation can be proposed, mainly based on local roughening of surface, to monitor the statistical similarity between the film and the substrate during growth or, in other words, to detect changes of the bare substrate morphological profile occurring during the film growth on top. Such approximation is based on surface representation in terms of power spectral density of surface heights, derived from topographic images; in this work, such method will be tested on two separate batches of synthetic images which simulate thin films growth onto a real rough substrate. In particular, two growth models will be implemented: the first reproduces the surface profile obtained during an atomic force microscopy measurement by using a simple geometrical envelope of surface, regardless the thin film growth mechanism; the second reproduces the columnar growth expected under nonstochastic deposition conditions. It will be shown that the approach introduced is capable to highlight differences between the two batches and, in the second case, to quantitatively account for the replication of the substrate roughness during growth. The

Synthetic Data in Quantitative Scanning Probe Microscopy

“…Synthetic surfaces are invaluable for addressing this problem. Columnar thin films were synthesised in References [ 17 , 18 ] using ballistic deposition with limited particle relaxation. The goal of this procedure in Reference [ 17 ] was to better understand the growth-related roughening processes when conformal films are deposited on rough surfaces.…”

“…Columnar thin films were synthesised in References [ 17 , 18 ] using ballistic deposition with limited particle relaxation. The goal of this procedure in Reference [ 17 ] was to better understand the growth-related roughening processes when conformal films are deposited on rough surfaces. Reference [ 18 ] studied the evolution of different statistical parameters of roughness when sample is convolved with tips of different radius, showing that the impact of wrong measurements on pores between individual columns using bigger tips has significant influence on both the height and lateral statistical quantities.…”

“…They were used to test data processing methods and to determine uncertainties related to the imaging process, namely tip convolution and its impact on different quantities. The impact of tip convolution on statistic properties of columnar thin films [ 17 , 18 ], fractal properties of self-affine surfaces [ 19 , 20 ], and size distribution of nanoparticles [ 21 ] were studied using entirely synthetic data. Novel approaches for tip estimation using neural networks were developed using artificial rough data [ 22 ] and methods for using neural networks for surface reconstruction to remove such tip convolution errors were developed using simulated patterned surfaces [ 23 ].…”

Preface to StSPM2019EV special issue

“…In addition, it was presented a phenomenological and simple model to follow the evolution of the surface of thin films during their growth under nonstochastic deposition conditions on substrates characterised by high roughness, with the capability of reproducing synthetic depositions of different films and experimental contexts. 3 Bednarikova et al 2 reviewed several advancement in scanning probe techniques for biological applications, for example for the investigation of proteins, lipids and DNA, and also larger objects such as cells. A detailed application of atomic force microscopy for the variation of the mechanical properties of red blood cells (erythrocytes) due to spur cell anaemia and cold agglutinated disease is reported, aiming to develop erythrocyte-based mechanical biomarkers, useful for disease diagnosis and therapy monitoring.…”

“…developed an analytical model of the electrostatic interactions for the Phase‐mode electrostatic force microscopy (EFM‐Phase) imaging of the surface electrostatic potential of silicon oxide stripes fabricated by oxidation scanning probe lithography. In addition, it was presented a phenomenological and simple model to follow the evolution of the surface of thin films during their growth under nonstochastic deposition conditions on substrates characterised by high roughness, with the capability of reproducing synthetic depositions of different films and experimental contexts 3 …”