Login / Signup

Investigation of deposition temperature effect on spatial patterns of MgF 2 thin films.

Reza ShakouryRobert Saraiva MatosHenrique Duarte da Fonseca FilhoSahar RezaeeAli ArmanArash BoochaniStanislav JurečkaAmir ZelatiMohsen MardaniȘtefan Ţălu
Published in: Microscopy research and technique (2022)
In this work, the atomic force microscopy (AFM) technique was used to characterize 3D MgF 2 thin film surfaces through advanced analysis involving morphological, fractal, multifractal, succolarity, lacunarity and surface entropy (SE) parameters, consistent with ISO 25178-2: 2012. Samples were synthesized by electron beam deposition, grown in three different temperatures. Three different temperatures of 25°C (laboratory temperature), 150 and 300°C were chosen. The temperature of 300°C is usually the highest temperature that can be deposited with the electron beam evaporation coating system. The substrates were made of glass (diameter 16 mm, thickness 3 mm), and the samples were prepared at a pressure of 5 × 10 -5  Torr. The statistical results from the AFM images indicate that topographic asperities decrease with increasing deposition temperature, showing a decrease in roughness values. Regardless of the deposition temperature, all surfaces have a self-similar behavior, presenting a very linear PSD distribution, and, according to our results, the sample deposited at 300° had the highest spatial complexity. On the other hand, surface percolation is increasing when temperature increases, indicating that its low roughness and high spatial complexity play an important role on the formation of their most percolating surface microtexture. Our results demonstrate that the lower deposition temperature promoted the formation of less discontinuous height distributions in the MgF 2 films.
Keyphrases
  • atomic force microscopy
  • high speed
  • escherichia coli
  • optical coherence tomography
  • deep learning
  • high resolution
  • machine learning
  • room temperature
  • candida albicans
  • ionic liquid
  • neural network