Thermodynamic Modelling of Complex Oxides for Smart Sensors H/F

Thermodynamic Modelling of Complex Oxides for Smart Sensors H/F

Domaine

Contrat

Post-doctorat

The Hiway-2-mat project aims to accelerate the discovery of materials for smart sensors using high-throughput combinatorial approaches and autonomous configurations to explore complex oxide compositions. In this context, the CALPHAD method is a valuable tool for calculating phase diagrams, either to better prepare experiments or guide the autonomous robot in real-time, providing crucial data for on-the-fly characterization and enhancing material exploration.

Your role will be to:

1. Perform thermodynamic simulations using CALPHAD method and Thermo-Calc Software to predict the stability range of a set of complex oxides (i.e. (Ba/Ca/Sr)(Ti/Zr/Sn/Hf)O3, doped VO2 or ZrO2-HfO2-CeO2-SnO2) in different atmosphere conditions (temperature and oxygen partial pressure). In this step, the candidate will also perform a critical review of the thermodynamic data available in the literature.
2. Develop a rapid screening method to search for the most promising compositions.
3. Perform thermodynamic modelling assessment of most promising compositions not yet included in the available databases.

The candidate will work closely with the experimental platform development team to guide future trials and adapt the method to better meet large-scale production needs.

Skills/Qualifications:

- PhD degree in Chemistry, Physics, Chemical Engineering, Materials Engineering or related fields.

- Strong background in thermodynamics.

- Experience with method CALPHAD and Thermo-Calc is expected; programming skills are essential.

Site

Saclay, France

Gif-sur-Yvette

28/10/2024