TREATMENT OF RADIOACTIVE ORGANIC EFFLUENTS
The ECCLOR project (Project labelled 'Investment for the Future') aims to find a management route for challenging radioactive organic effluents. A strategy under investigation is to make the effluents compatible with existing outlets by decontaminating them of radioelements by column filtration. This involves developing ion-selective extractants in a form suitable for use in columns.
Studies are being carried out at CEA to improve the treatment of radioactive aqueous effluents by developing processes capable of achieving "zero discharge" while producing a minimum of waste. The challenge of the ECCLOR project will be to transpose this work to contaminated organic solvents with various radiological compositions and rheological properties. A first post-doctoral contract was dedicated to the development of materials for this application. A number of inorganic supports (silicas, geopolymers, aluminas, etc.) were considered for decontaminating these organic effluents.
The performance of the various materials developed in previous work can be optimised in terms of actinide capacity and selectivity with respect to competitor ions. In particular, the performance of existing materials needs to be studied further on more complex simulated LORs, with the necessary adaptations to the analytical method.
This project is intended for a post-doctoral fellow wishing to develop skills in extraction mechanism comprehension and analytical methods, with an interest in advancing the field of radioactive waste management. It will be will build upon the expertise of two laboratories at CEA Marcoule: the Design and Characterization of Mineral Materials Laboratory for materials elaboration and characterization, and the Supercritical and Decontamination Processes Laboratory for materials grafting and decontamination experiments.
Development of a new generation of reversible polymer adhesives
Polymeric adhesives are generally cross-linked systems used to bond two substrates throughout the lifetime of an assembly, which may be multi-material, for a wide range of applications. At their end of life, the presence of adhesives makes it difficult to separate materials and recycle them. Moreover, it is difficult to destroy the cross-linking of the adhesives without chemical or thermal treatment that is also aggressive for the bonded substrates.
In this context, the CEA is developing adhesives with enhanced recyclability, by integrating recyclability into the chemical structures right from the synthesis of the polymer networks. The first approach involves incorporating dynamic covalent bonds into polymer networks, which can be exchanged under generally thermal stimulus (e.g. vitrimers). A second approach involves synthesising polymers that can be depolymerised under a specific stimulus (self-immolating polymers) and have the ability to cross-link.
The post-doc will develop 2 networks that can be used as adhesives with enhanced recyclability. A first network will be based on a depolymerizable chemistry under stimulus already developed on linear polymer chains, to be transposed to a network. A second vitrimer network will be synthesised on the basis of previous work at the CEA. Activation of the bond exchange in this network will take place via a so-called photolatent catalyst, which can be activated by UV and will make it possible to obtain a UV- and heat-stimulated adhesive. The choice and synthesis of these catalysts and their impact on the adhesive will be the focus of the study. The catalysts obtained could also be used to trigger depolymerisation of the first depolymerisable system under stimulus.
Modeling of the MADISON fuel irradiation device for the future JHR reactor
The Jules Horowitz Reactor (RJH), currently under construction at CEA's Cadarache site, will irradiate materials and fuels in support of the French and international nuclear industry, as well as producing radioelements for medical use. To carry out its missions, the reactor will be equipped with numerous experimental devices. In particular, the MADISON device, currently under design, will irradiate 2 or 4 fuel samples under nominal stationary or operational transient conditions. The loop is representative of light-water reactor operating conditions, with single-phase and two-phase forced convection.
The main objective of the Post-Doc is to model the MADISON device and all associated heat exchanges precisely, in order to help determine the overall heat balance during the test and thus improve the accuracy of the linear power imposed on the samples. To this end, a coupled thermal model (describing the fuel rods and device structures) / CFD thermal-hydraulic model (describing the coolant) will be established using the NEPTUNE_CFD/SYRTHES code. The modeling will be validated based on results obtained from similar modeling carried out on the ISABELLE-1 and ADELINE single-rod devices in the OSIRIS and RJH reactors. The proposed approach fits in with the logic of developing digital twins of the RJH experimental devices.
GPU ray tracing with OptiX for a Monte Carlo particle transport software
This postdoctoral research subject is proposed in the context of the development by CEA List of the CIVA software platform, used for the simulation of non-destructive testing techniques, in particular X-radiography and computed tomography. This research is supported by a collaborative project between two CEA divisions (DRT and DES). It aims to optimize the performance of the Monte-Carlo method used in the CIVA software in order to improve the processing of complex industrial radiographic configurations. More precisely, More precisely, the following two tasks will be carried out:
- Developing a eTLE-fd type estimator on CPU in the CIVA environment, in order to accelerate the Monte-Carlo calculation by generating pseudo-particles transported directly to the detector. This estimator, already implemented in a DES code (TRIPOLI-4®), will have to be adapted to the NDT applications processed by CIVA.
- Port this estimator to GPU using Nvidia's OptiX library in order to optimize the Monte-Carlo calculation, including taking into account particle attenuation and energy deposition, to be coded in CUDA.
DTCO for RF & mmW Applications:Focus on Homogeneous & Heterogeneous Chiplet Hybrid Bonding Challenge
In recent years, there have been numerous technological advancements in silicon-based semiconductors. However, the limits in terms of frequency performance and power seem to have been reached, requiring the development of new type III-V devices (such as InP and GaN) that are faster, more powerful and well adapted for new RF mmW applications. For reasons of flexibility, performance, and cost, it is crucial to co-integrate these new high-performance III-V components with the more traditional silicon technologies. This is one of the major objectives of the proposed topic.
The focus will be on the design and optimisation of millimetre-wave RF circuits using 3D heterogeneous hybrid bonding assembly technology. In recent years, numerous test vehicles have been fabricated and characterised to demonstrate the advantages and disadvantages of the hybrid bonding assembly process for millimetre wave RF applications. The aim is to extend this work and focus the studies and research on real RF systems, such as millimetre-wave power amplifiers. The DTCO (Design and Technology Co-Optimisations) approach will not only enable the design of efficient 3D RF circuits, but will also allow the adaptation of different 3D design rules to make 3D hybrid bonding technology relevant for the production of millimetre-scale 3D integrated systems.
2D materials electrical characterization for microelectronics
Future microelectronic components will be ever smaller and ever more energy-efficient. To meet this challenge, 2D materials are excellent candidates, thanks to their remarkable dimensions and electronic properties (high mobility of charge carriers, high light emission/absorption). What's more, they feature van der Waals (vdW) surfaces, i.e. no dangling bonds, enabling them to retain their properties even at very small dimensions (down to the monolayer). New 2D materials and vdW stacks with novel physical properties are being discovered every day. However, integrating them and measuring their performance in circuits remains an ongoing challenge, as their properties must be preserved during integration.
The aim of this post-doc is to develop components for qualifying 2D materials for microelectronic (RF transistor) and spintronic (magnetic memory) applications in horizontal configuration on silicon. A vertical measurement method has already been developed by CEA LETI. Building on these developments, the candidate will develop this measurement system and characterize various materials produced in MBE by CEA-IRIG. The work will involve transferring these layers onto chips, optimizing the electrical contacts and developing the in-plane electrical measurement chain.
Comparison of Diamond and vertical GaN technologies to SiC and Si for power applications
Power devices based on wide band gap semiconductors are increasingly being studied and adopted in commercial products, driven by the electrification of our societies. Among these wide band gap devices, SiC-based technologies are the most mature, at the industrial production stage. Other materials are being studied to achieve higher performance, in particular diamond, whose intrinsic physical properties offer great potential, as well as GaN components in a vertical architecture. However, the real benefits of these materials compared with existing Si or SiC solutions have not been clearly demonstrated and might strongly depend on the applications considered. The aim of this project is to identify one or more applications where vertical GaN and diamond technologies are likely to bring significant benefits, taking into account the current and/or projected market for these applications. Then, using TCAD and SPICE simulations as well as experimental test device characterizations, we will compare the estimated performance of industrially viable diamond and GaN components, designed for these applications, with that of SiC and Si.
Disruptive RF substrates based on polycrystalline materials
A high resistivity substrate is essential for the design of state-of-the-art high-frequency circuits. The high-resistivity (HR) SOI substrate with a trap-rich layer below the buried oxide (BOX) is the option with the highest performance at present for CMOS technologies. However, these substrates have two major limitations: (1) their relatively high price and (2) the degradation of their RF performance at operating temperatures above 100 °C.
As part of this postdoctoral study, we propose to study, in collaboration with the Catholic University of Louvain (UCL), the RF performance over a wide temperature range of a polycrystalline substrate over its entire thickness (several hundred µm). These polycrystalline substrates indeed have a high density of electronic traps distributed throughout the entire volume, which in principle allows for stable RF performance even at high operating temperatures.
The person hired will participate in the following research: (1) screening of promising substrates from TCAD simulations (e.g. poly-Si, poly-SiC, …), (2) integration of polycrystalline substrates in an SOI process flow at Leti, (3) measurement of RF performances in frequency and temperature at UCL. A particular attention will be placed on understanding the physical phenomena involved through the comparison of experimental and simulation data.
High-performance computing using CMOS technology at cryogenic temperature
Advances in materials, transistor architectures, and lithography technologies have enabled exponential growth in the performance and energy efficiency of integrated circuits. New research directions, including operation at cryogenic temperatures, could lead to further progress. Cryogenic electronics, essential for manipulating qubits at very low temperatures, is rapidly developing. Processors operating at 4.2 K using 1.4 zJ per operation have been proposed, based on superconducting electronics. Another approach involves creating very fast sequential processors using specific technologies and low temperatures, reducing energy dissipation but requiring cooling. At low temperatures, the performance of advanced CMOS transistors increases, allowing operation at lower voltages and higher operating frequencies. This could improve the sequential efficiency of computers and simplify the parallelization of software code. However, materials and component architectures need to be rethought to maximize the benefits of low temperatures. The post-doctoral project aims to determine whether cryogenic temperatures offer sufficient performance gains for CMOS or should be viewed as a catalyst for new high-performance computing technologies. The goal is particularly to assess the increase in processing speed with conventional silicon components at low temperatures, integrating measurements and simulations.
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.