Combinatorial HIPims for Sovereignty
Challenge
Accelerated discovery of coating materials with complex, architected and multifunctional compositions for innovative applications serving major transitions
OBJECTIVES
- Creation of a dynamic combinatorial synthesis platform – DIADEM-2D- for thin layer coatings by PVD-HiPIMS, for research and training, equipped with a new generation plasma power supply from the University of Nantes, diagnostic tools for High-throughput, online plasma and characterization powering AI-assisted data processing
- Provision of this platform for the Diadem scientific community
Final objective of the artificial intelligence tool: determination of the process parameters in order to obtain a layer with specific characteristics.
This project is dedicated to the definition and implementation of the DIADEM 2D platform within INSTN. This platform will be used to carry out combinatorial synthesis in dynamic mode. It will be instrumented both for in situ plasma diagnosis (optical spectrometry, ion energy measurement) and for high-throughput characterization of thin layers (Raman, LIBS). The idea is to have an autonomous synthesis machine like certain processes developed within the framework of PEPR DIADEM, for example in the field of the synthesis of nanomaterials by microfluidics. A parametric study will be carried out to study the influence of deposition parameters on the plasma characteristics and the characteristics of the deposited layers and their usage properties. Thus, a microstructural characterization study using different complementary experimental techniques (Raman spectroscopy, scanning and/or transmission electron microcopy, chemical analysis by X-ray photoelectron spectroscopy) will be accomplished and will aim to correlate the microstructural properties to the deposition parameters. This characterization phase will be carried out using the experimental platforms of CEA Saclay.
The results obtained within the framework of CHIPS will subsequently be integrated into the database on innovative processes, an initiative which recently started within the CEA. This data will be used by Artificial Intelligence tools to optimize complex processes more quickly, transfer processes more easily from one machine to another, reverse the process to more easily find process parameters depending on the application or the covred physical properties.
A high-power plasma supply will also be developed in collaboration with IMN-Nantes University, and will be integrated into the synthesis platform for the production of promising coatings, and more particularly doped metal alloys.