Development of a CVD process inside the nuclear reactor cladding tubes to the industrial scale
The FULL SCALE CVD project aims to demonstrate the feasibility of synthesizing an anti-corrosion coating inside a zirconium alloy fuel cladding tube at full scale (4.5 meters long). This project is part of the CEA’s Surface Engineering Action Plan, which focuses on developing a limited number of high-potential coating technologies—from laboratory scale to pilot scale—for pre-industrial technological demonstration.
The internal coating of fuel cladding tubes is designed to limit pellet-cladding interaction. This enables faster ramp-up and ramp-down cycles, allowing for finer control of electricity production. It also helps mitigate the consequences of incidents similar to the Fukushima event.
To achieve a dense, homogeneous, and sufficiently thick coating, a dedicated system capable of coating six 4.5-meter tubes simultaneously has been developed at the CEA. The goal of the postdoctoral research is to develop coating processes that meet the targets in terms of composition, thickness, homogeneity, and density of the synthesized film. The targeted coatings are Cr2O3 and CrC?.
The success of this project could lead to a technology transfer to fuel cladding manufacturers or the creation of a start-up.
Thermal properties of 3D aluminum nitride structures for electronic packaging
The 12-month postdoctoral fellowship is part of the overall 3DNAMIC project, funded by the Occitanie region and involving the Materials platform of the DRTDOCC department and the Laplace laboratory. A thesis began in December 2024 aimed at “the study and characterization of 3D aluminum nitride ceramics for the thermal packaging and management of electronic components.”
The postdoc is scheduled to begin at approximately in September 2026, with the following main objectives:
Objective 1: Perform a comparative analysis of the thermal properties of ceramics produced by AF elements and on model structures using different materials available in the CEA materials platform.
Objective 3: Propose, qualify, and validate, numerically and then experimentally, heat dissipation structures for ceramics obtained by FA as part of the 3DNAMIC project.
Design and Implementation of a Neural Network for Thermo-Mechanical Simulation in Additive Manufacturing
The WAAM (Wire Arc Additive Manufacturing) process is a metal additive manufacturing method that allows for the production of large parts with a high deposition rate. However, this process results in highly stressed and deformed parts, making it complex to predict their geometric and mechanical characteristics. Thermomechanical modeling is crucial for predicting these deformations, but it requires significant computational resources and long calculation times. The NEUROWAAM project aims to develop a precise and fast thermomechanical numerical model using neural networks to predict the physical phenomena of the WAAM process. An internship in 2025 will provide a database through thermomechanical simulations using the CAST3M software. The post-doc's objective is to develop a neural network architecture capable of learning the relationship between the manufacturing configuration and the thermomechanical characteristics of the parts. Manufacturing tests on the CEA's PRISMA platform will be conducted to validate the model and prepare a feedback loop. The CEA List's Interactive Simulation Laboratory will contribute its expertise in accelerating simulations through neural networks and active learning to reduce training time.