Introduction of innovative materials for sub-10nm contact realization
As part of the FAMES project and the European ChipACT initiative, which aim to ensure France’s and Europe’s sovereignty and competitiveness in the field of electronic nano-components, CEA-LETI has launched the design of new FD-SOI chips. Among the various modules being developed, the fabrication of electrical contacts is one of the most critical modules in the success of advanced node development.
For sub-10 nm node, the contact realization is facing a lot of challenges like punchthrough (due to low etch selectivity during contact etching), voids during metal deposition, self-alignment, and parasitic capacitance. New breakthrough approach has recently been proposed consisting in the deposition of new dielectric films with chemical gradient. This thesis focuses on the development (deposition an etching processes) of new gradient compounds incorporated into SiO2 to address the current issues.
Advanced electrode materials by ALD for ionic devices
This work aims to develop Advanced ultrathin cunductive layers (<10nm) by ALD (Atomic Layer Deposition)for électrodes use(resistivity 100). The other challenge aims to reduce the ALD-based electrode layer thickness less than 5nm while still maintaining the advanced electric properties (resistivity in the mOhm range).
This work covers multiple aspects including inter alia ALD process, ALD precursors, Elementary characterization of intrinsec properties (physico-chemical, morphological and electrochemical) as well as integration on short loop 3D devices.
Development of a new numerical scheme, based on T-coercivity, for discretizing the Navier-Stokes equations.
In the TrioCFD code, the discretization of the Navier-Stokes equations leads to a three-step algorithm (see Chorin'67, Temam'68): velocity prediction, pressure solution, velocity correction. If an implicit time discretization scheme is to be used, the pressure solution step is particularly costly. Thus, most simulations are performed using an explicit time scheme, for which the time step depends on the mesh size, which can be very restrictive. We would like to develop an implicit time discretization scheme using a stabilized formulation of the Navier-Stokes problem based on explicit T-coercivity (see Ciarlet-Jamelot'25). It would then be possible to solve an implicit scheme directly without a correction step, which could significantly improve the performance of the calculations. This would also allow the use of the P1-P0 finite element pair, which is frugal in terms of degrees of freedom but unstable for a classical formulation.
Development of a modeling tool for corrosion in porous media
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In a context where material durability is essential for the safety of infrastructures and the promotion of a sustainable energy transition, mastering corrosion phenomena represents a major challenge for key sectors such as decarbonized energy transport through buried pipelines and civil engineering (hydrogen, nuclear, underground infrastructures). The CORPORE project addresses this issue by proposing the development of advanced numerical simulation models to study corrosion in porous media using COMSOL Multiphysics.
The main scientific and technological objective is to establish an integrated multiphysics modeling approach for the electrochemical and transport mechanisms within porous materials: studying the coupled influence of chemistry, pore network properties, and material–environment interactions on the initiation and propagation of corrosion.
This approach will help optimize anticorrosion protection strategies, reduce maintenance costs, and extend the service life of structures. From a state-of-the-art perspective, most current models focus on homogeneous media and compartmentalized approaches. Our project stands out by integrating a multi-scale mechanistic modeling framework combined with the use of archaeological data for long-term validation.
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Investigation of polytopal methods apllied to CFD and optimized on GPU architecture
This research proposal focuses on the study and implementation of polytopal methods for solving the equations of fluid mechanics. These methods aim to handle the most general meshes possible, overcoming geometric constraints or those inherited from CAD operations such as extrusions or assemblies that introduce non-conformities. This work also falls within the scope of high-performance computing, addressing the increase in computational resources and, in particular, the development of massively parallel computing on GPUs.
The objective of this thesis is to build upon existing polytopal methods already implemented in the TRUST software, specifically the Compatible Discrete Operator (CDO) and Discontinuous Galerkin (DG) methods. The study will be extended to include convection operators and will investigate other methods from the literature, such as Hybrid High Order (HHO), Hybridizable Discontinuous Galerkin (HDG), and Virtual Element Method (VEM).
The main goals are to evaluate:
1. The numerical behavior of these different methods on the Stokes/Navier-Stokes equations;
2. The adaptability of these methods to heterogeneous architectures such as GPUs.
Robust multi-material topological optimization under manufacturability constraints applied to the design of superconducting magnets for high-field MRI
MRI scanners are invaluable tools for medicine and research, whose operation is based on exploiting the properties of atomic nuclei immersed in a very intense static magnetic field. In almost all MRI scanners, this field is generated by a superconducting electromagnet.
The design of electromagnets for MRI must meet very demanding requirements in terms of the homogeneity of the field produced. In addition, as the magnetic field becomes more intense, the forces exerted on the electromagnet increase, raising the issue of the mechanical strength of the windings. Finally, the “manufacturability” of the electromagnet imposes constraints on the shapes of acceptable solutions. The design of superconducting electromagnets for MRI therefore requires a meticulous effort to optimize the design, subject to constraints based on magneto-mechanical multiphysics modeling.
A new innovative multiphysics topological optimization methodology has been developed, based on a density method (SIMP) and a finite element code. This has made it possible to produce magnet designs that meet the constraints on the homogeneity of the magnetic field produced and on the mechanical strength of the windings. However, the solutions obtained are not feasible in practice, both in terms of the manufacturability of the coils (cable windings) and their integration with a supporting structure (coils held in place by a steel structure).
The objective of this thesis is to enhance the topological optimization method by formalizing and implementing manufacturing constraints related to the winding method, residual stresses resulting from pre-tensioning the cables during winding, and the presence of a structural material capable of absorbing the forces transmitted by the coils.
development of a NET (Negative Emission Technologie) process combining CO2 capture and hydrogenation into synthetic fuel
Until recently, CO2 capture technologies were developed separately from CO2 utilization technologies, even though coupling the CO2 desorption stage with the chemical transformation of CO2, which is generally exothermic, would yield significant energy savings.
The first coupled solutions have recently been proposed, but they are mainly at moderate temperatures (100-180°C) [1], or even recently close to 225°C [2].
The objective of this doctoral thesis is to study, both experimentally and theoretically, a coupled system in the 250-325°C temperature range that allows via Fischer-Tropsch-type catalytic hydrogenation the direct production of higher value-added products
Reduction of reinforcement in reinforced concrete structures through nonlinear calculations and topological and evolutionary optimizations
Reinforcing steel plays a major role in the behavior of reinforced concrete structures. Nevertheless, significant conservatisms may sometimes be imposed by design codes, raising questions about the feasibility of construction or the viability of the structure (economic, environmental, etc.). It is within this context that the doctoral research takes place. Building on recent developments, the work aims to propose an innovative design approach relying on the use of nonlinear finite element calculations, combined with topological optimization algorithms (defining reinforcement directions and bar cross-sections) and evolutionary optimization algorithms (determining the placement of bars with fixed cross-sections).
The method should, through an iterative process, yield solutions that meet an optimal design configuration. Considering the multiple, potentially conflicting objectives to minimize (such as cost, feasibility, strength, and carbon footprint), the approach will guide the configuration of input parameters based on an analysis of the relevant output results.
Applying the method to complex, practice-based case studies (for example, beam-column junctions) will demonstrate its relevance compared with more conventional design methods. By the end of the thesis, the doctoral candidate will have developed advanced skills in the use and development of state-of-the-art tools, ranging from nonlinear finite element simulation to modern optimization techniques based on artificial intelligence.
High-Fidelity Monte Carlo Simulations of Neutron Noise in Nuclear Power Reactors
Operating nuclear reactors are subject to a variety of perturbations. These can include vibrations of the fuel pins and fuel assemblies due to fluid-structure interactions with the moderator, or even vibrations of the core barrel, baffle, and pressure vessel. All of these perturbations can lead to small periodic fluctuations in the reactor power about the stable average power level. These power fluctuations are referred to as “neutron noise”. Being able to simulate different types of in-core perturbations allows reactor designers and operators to predict how the neutron flux could behave in the presence of such perturbations. In recent years, many different research groups have worked to develop computational models to simulate these sources of neutron noise, and their resulting effects on the neutron flux in the reactor. The primary objective of this PhD thesis will be to bring Monte Carlo neutron noise simulations to the scale of real-world industry calculations of nuclear reactor cores, with a high-fidelity continuous-energy physics representation. As part of this process, the student will add novel neutron noise simulation capabilities to TRIPOLI-5, the next-generation production Monte Carlo particle-transport code jointly developed by CEA and ASNR, with the support of EDF.