Algorithmic solutions for the generation of digital material representation models of thin films and coatings
The structure of thin films and coatings is frequently complex due to the nature of deposition processes. It consists of columns with intercolumnar boundaries that are often precursors of crack initiation and propagation, which can lead to delamination of the film from the substrate. The simulation of the behaviour of thin film and coatings without considering their complex morphology presents a significant limitation in achieving reliable results. Therefore, to address this challenge, a set of approaches for generating a full-field digital representation of thin films/coatings for subsequent numerical studies was developed within the work. These algorithms are divided into three categories characterised by different levels of complexity. The first is based on image processing algorithms for directly mapping the exact morphology of films/coatings from experimental data. The second is based on the cellular automata and Monte Carlo algorithms, providing a statistically similar representation of films/coatings structures. Finally, the third uses physics-based modelling methods to replicate the deposition process of films/coatings on the substrate. The methodologies outlined in this work facilitate the preparation of digital morphologies of any complex deposited structure for subsequent incorporation into numerical simulations examining their behavior under processing and in-use conditions. This enables the use of numerical methods in the detailed investigation of deposited structures designed for practical applications in a wide range of industries, which is important from an ecological and economic point of view.
Authors
- Konrad Perzyński (ORCID: https://orcid.org/0000-0001-7761-2599)
Institutions
- AGH University of Krakow (PL)
Publication Details
- Journal
- Computational Materials Science
- Published
- 2025-02-08
- DOI
- https://doi.org/10.1016/j.commatsci.2025.113745
- Citations
- 2
- Primary Topic
- Advanced Numerical Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.67
Funders
- Narodowe Centrum Nauki
- Akademia Górniczo-Hutnicza im. Stanislawa Staszica
- Quest High Performance Computing