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 characterization of defects generated by technological processes for high-performance infrared imaging
This thesis falls within the field of cooled infrared detectors. The CEA-LETI-MINATEC Infrared Laboratory specializes in the design and manufacture of infrared camera prototypes used in defense, astronomy, environmental monitoring, and satellite meteorology.
In this context of high-performance imaging, it is crucial to ensure optimal detector quality. However, manufacturing processes can introduce defects that can degrade sensor performance. Understanding and controlling these defects is essential to increase reliability and optimize processes.
The objective of the thesis is to identify and precisely characterize these defects using cutting-edge techniques, rarely combined, such as Laue microdiffraction and FIB-SEM nanotomography, enabling structural analysis at different scales. By linking the nature and origin of defects to manufacturing processes and quantifying their impact on performance, the doctoral student will contribute directly to improving the reliability and efficiency of next-generation infrared sensors.
The doctoral student will join a team covering the entire detector manufacturing chain and will actively participate in the development (LETI clean room) and structural characterization (CEA-Grenoble platform, advanced techniques) of samples. He/she will also be involved in electro-optical characterization in partnership with the Cooled Infrared Imaging Laboratory (LIR), which specializes in detailed analysis of active materials at cryogenic temperatures.
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.
Superconducting silicide contacts on hyperdoped silicon by nanosecond pulsed-laser annealing
In the race towards building a quantum computer, there is a deep interest in fabricating devices based on the robust and scalable silicon FD-SOI technology. One example is the Josephson Field Effect Transistor (JoFET) whose operability relies on the high transparency of the interface between the superconducting source/drain regions and the semiconducting channel. Such transparency could be improved by doping the source/drain regions, and hence lowering the Schottky barrier height at the superconductor/semiconductor interfaces.
This PhD aims at developing highly transparent superconducting silicide contacts on a 300 mm production line using Nanosecond Pulsed Laser Annealing (NPLA). NPLA will play a key role for reaching extremely high doping concentrations in silicon [1,2], then forming the superconducting silicides (CoSi2, V3Si) with minimal thermal budget and related dopant deactivation. A particular focus will be devoted on the stresses during silicide formation and their impact on the superconducting critical temperature. Also, the distribution of dopants will be assessed by Atom Probe Tomography (APT), an advanced 3D imaging technique capable of imaging the distribution of dopants at the atomic scale [3]. Finally, electrical measurements on fabricated junctions and transistors will be carried out at low temperature (< 1 K) in order to evaluate the transparency of the superconducting contacts.
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
Modeling of Wall Condensation Phenomena and Liquid Film Interactions
In this thesis, we focus on modeling mass and energy transfer associated with wall condensation in a turbulent flow of a vapor–noncondensable gas mixture. The flow is two-phase and turbulent, where forced, mixed, and natural convection modes may occur. The framework of this work relies on the RANS approach applied to the compressible Navier–Stokes equations, in which wall condensation is described using semi-analytical wall functions developed in a previous doctoral study cite{iziquel2023}. These functions account for the different convection modes as well as suction and species interdiffusion effects, but neglect the presence of a liquid film.
In the literature, the influence of film formation and flow on mass and heat transfer is often neglected, since it is generally assumed that, in the presence of noncondensable gases, the resistance of the gaseous layer to vapor diffusion is much greater than the thermal resistance of the liquid film.
The objective of this thesis is to improve the prediction of heat and mass transfer by investigating, beyond the thermal resistance of the condensate, the dynamic effect of the liquid and its interaction with the gaseous diffusion layer during wall condensation. The study will first consider laminar film flow, and then attempt to extend the analysis to the turbulent regime.
In the gas phase, the wall-function model developed in cite{iziquel2023} for a binary mixture of vapor and a single noncondensable gas will be extended to mixtures of vapor and $n>1$ noncondensable gases (N2, H2, …), in order to address hydrogen risk issues.
The validation of the implemented models will be carried out using results from separate-effect (SET) and coupled-effect (CET) experiments available in the literature (Huhtiniemi cite{huhti89}, COPAIN, ISP47-MISTRA, ISP47-TOSQAN, RIVA). Comparisons at the CFD scale, using wall functions for condensation neglecting the film, will be performed on benchmark cases from the literature and condensation experiments (COPAIN) to assess the impact of this assumption as well as the improvement provided by the new model in terms of accuracy and computational cost.
Design of asynchronous algorithms for solving the neutron transport equation on massively parallel and heterogeneous architectures
This PhD thesis work aims at designing an efficient solver for the solution to the neutron transport equation in Cartesian and hexagonal geometries for heterogeneous and massively parallel architectures. This goal can be achieved with the design of optimal algorithms with parallel and asynchronous programming models.
The industrial framework for this work is in solving the Boltzmann equation associated to the transportof neutrons in a nuclear reactor core. At present, more and more modern simulation codes employ an upwind discontinuous Galerkin finite element scheme for Cartesian and hexagonal meshes of the required domain.This work extends previous research which have been carried out recently to explore the solving step ondistributed computing architectures which we have not yet tackled in our context. It will require the cou-pling of algorithmic and numerical strategies along with programming model which allows an asynchronousparallelism framework to solve the transport equation efficiently.
This research work will be part of the numerical simulation of nuclear reactors. These multiphysics computations are very expensive as they require time-dependent neutron transport calculations for the severe power excursions for instance. The strategy proposed in this research endeavour will decrease thecomputational burden and time for a given accuracy, and coupled to a massively parallel and asynchronousmodel, may define an efficient neutronic solver for multiphysics applications.
Through this PhD research work, the candidate will be able to apply for research vacancies in highperformance numerical simulation for complex physical problems.
One-sided communication mechanisms for data decomposition in Monte Carlo particle transport applications
In the context of a Monte Carlo calculation for the evolution of a PWR (pressurized water reactor) core, it is necessary to compute a very large number of neutron-nucleus reaction rates, involving a data volume that can exceed the memory capacity of a compute node on current supercomputers. Within the Tripoli-5 framework, distributed memory architectures have been identified as targets for high-performance computing deployment. To leverage such architectures, data decomposition approaches must be used, particularly for reaction rates. However, with a classical parallelization method, processes have no particular affinity for the rates they host locally; on the contrary, each rate receives contributions uniformly from all processes. Access to decomposed data can be costly when it requires intensive use of communications. Nevertheless, one-sided communication mechanisms, such as MPI RMA (Message Passing Interface, Remote Memory Access), make these accesses easier both in terms of expression and performance.
The objective of this thesis is to propose a method for partial data decomposition relying on one-sided communication mechanisms to access remotely stored data, such as reaction rates. Such an approach will significantly reduce the volume of data stored in memory on each compute node without causing a significant degradation in performance.
Optimising the enzymatic degradation of polylactic acid (PLA) to produce biohydrogen (BioH2) through photofermentation.
This thesis project presents a novel method of producing biohydrogen (BioH2) through the enzymatic breakdown of polylactic acid (PLA), a bioplastic which is challenging to recycle. The aim is to optimise the hydrolysis of PLA into lactic acid, which can be metabolised directly by purple non-sulfur bacteria (PNSB) to produce BioH2 in anoxic conditions. The work will entail selecting high-performance esterases in collaboration with Génoscope CEA, expressing them in soluble form in model hosts such as E. coli, yeasts and PNSB, and optimising reaction conditions such as pH, temperature and concentration to maximise lactic acid production. The second phase will focus on enhancing photofermentation in a photobioreactor (PBR) with advanced control systems (LED, AI and CFD). Funded by the CEA and PUI Grenoble Alpes, this project is part of a circular economy approach, aiming to develop a scalable process for converting PLA waste into renewable energy in line with the challenges of the energy transition.