Growth of 2D Ferromagnetic Chalcogenide Materials for Spintronics
Chalcogenide materials, particularly Ge-Sb-Te (GST) alloys, are essential for phase-change memory (PCMs).
Although high-performance, these memories consume a great deal of energy, which
is driving the search for alternative solutions. GST alloys offer unique opportunities in the field of spin-orbitronics as spin-charge conversion materials or as sources of spin-polarized current. Two-dimensional ferromagnetic alloys such as Fe-Ge-Te or Ge-Mn-Te offer promising avenues as sources of spin current for new types of more efficient memory devices. For efficient spin injection, we are seeking a material that not only exhibits a high Curie temperature (TC) and significant spin polarization, but is also fully compatible with existing silicon-based CMOS technology.
The aim of this thesis is to develop and master, on an industrial scale on 300 mm Si substrates, the van der Waals epitaxial growth of 2D ferromagnetic films based on Fe-Ge (Ga)Te2 (n=3, 5) or Ge_(1-x)Mn_xTe, for example to integrate them in situ with spin-charge conversion chalcogenide layers such as ferroelectric layers (a-GeTe(111)) or topological insulators (Bi_(2-x)Sb2Te3).
Development of Machine Learning algorithm to optimize the control of absorption machines
The Thermal and Solar Technologies Laboratory (L2TS) and the Energy Systems for Territories Laboratory (LSET), located at the CEA LITEN site in Le Bourget-de-Lac, are offering a cross-disciplinary PhD thesis combining thermodynamics and optimization using Artificial Intelligence.
Specifically, this doctoral research project involves developing a machine learning algorithm to optimize the control of absorption machines. These machines are thermodynamic cycles able to produce heat or cold from an intermediate heat input; thus, offering potential valorization of industrial waste heat or renewable energies, such as solar thermal. Heat exchange is made possible by the absorption and desorption reactions of a gaseous refrigerant in a fluid. Specifically, the NH3-H2O mixture will be used. The dynamic operation of these cycles is extremely complex because the operational variables, physical parameters, and hydrodynamic aspects are highly intertwined. Thus, the use of a neural network is particularly relevant for establishing an adaptive control strategy for these machines.
The thesis will have a theoretical aspect, involving the study and selection of the most suitable algorithm to address the problem, and an experimental aspect of validation on a prototype absorption machine. The project will also involve the design of a controller for implementation.
Architecture of small animal single photon emission tomograph.
Medical imaging, a source of major innovations, presents remarkable potential for meeting new challenges with the growing demand for precision medicine, which requires cutting-edge diagnostic and therapeutic approaches personalized for each patient.
In this context, CEA-Leti proposes a PhD internship to develop a dedicated preclinical SPECT (Single Photon Emission Tomography) imager that will provide the performance (spectral information, high resolution, and high sensitivity) needed by researchers developing new radiopharmaceuticals.
The laboratory has a recognized expertise on CZT (Cadmium Zinc Telluride) semiconductor imagers enabling better spatial and energy resolution than scintillators used by most systems. They open new opportunities for emission imaging like easier Compton imaging, multi-isotope imaging and better contrast.
The candidate will have to handle the following tasks:
1. Study the state of the art of small animal SPECT imagers to participate with the team to the choice of system specification and choice of a draft architecture.
2. Simulate this architecture by using Monte-Carlo codes and optimize free parameters.
3. Design and manufacture the prototype system, with the help of the team including system engineers.
4. Test and validate the imaging capabilities, using reconstruction algorithms provided by the team.
The PhD will be conducted inside an instrumentation laboratory with access to acquisition electronics, detectors, motorized mechanics, gamma-ray sources and processing/simulation software. The candidate will also work in collaboration with a clinical and preclinical centre (at Orsay’s hospital) for conducting imaging test on phantoms and animals.
Accelerated development of Zn-MnO2 technology for long-term storage through simulation-data hybridization
The massive deployment of renewable energies is driving increasing demand for stationary energy storage, whose specific characteristics (cost, safety, durability) differ radically from those of electric mobility. Faced with the limitations of Li-ion batteries (fire risks, criticality of lithium and cobalt, production costs), aqueous zinc-manganese (Zn-MnO2) technology is emerging as a disruptive alternative. Based on abundant, non-toxic, and inherently safe materials, it offers unique potential for long-term storage with a low environmental impact.
However, the industrialization of this technology faces scientific hurdles that limit reversibility and cycle life, notably the formation of zinc dendrites and cathode instability. This doctoral project proposes to overcome these obstacles through a hybrid research strategy combining multiphysics modeling and artificial intelligence.
Initially, a finite element model will be developed and experimentally validated to characterize degradation mechanisms (current density hotspots, concentration gradients). Subsequently, this model will serve as a data generator to train machine learning algorithms. These surrogate models will enable the rapid exploration of a vast design space to identify the most resilient architectures. The ultimate goal is to accelerate the eco-design of high-performance Zn-MnO2 batteries that meet the imperatives of energy sovereignty and the circular economy.
Development and characterization of a low-silver metallization for photovoltaic cells with high-efficiency passivated contacts
In order to decarbonize energy production and meet climate plan objectives, the production of photovoltaic (PV) modules must increase significantly. To sustain these production levels, the silver content in latest-generation cells must be drastically reduced. Some alternatives incorporate less expensive metals (nickel, aluminum, copper) into screen-printing pastes. These approaches require evaluation in terms of contact formation, electron transport, and reliability. In a TOPCon cell architecture, the electrode must be brought into direct contact with the active layers of the cell via thermal annealing. This step enhances device performance (through a hydrogenation phenomenon) while simultaneously generating potential degradation related to the introduction of metallic species. This is especially critical when using new metals (Ni, Cu, etc.) with higher diffusivities than silver. The objectives of this thesis are manifold: to evaluate the performance of these low-silver alternative pastes once integrated into TOPCon cells; to characterize the impact of the introduction of these metallic species on the lifetime of photogenerated carriers in silicon; and to assess the long-term stability of these metallizations while verifying the absence of cell degradation phenomena under prolonged illumination. If necessary, an alternative metallization technique more suitable for these pastes will be developed. During the PhD, the successful candidate will be required to fabricate, metallize via screen printing, and characterize devices within a cleanroom environment.
Self-healing of radiation-induced defects in silicon solar cells for space
Over the last decades, the development of alternative space photovoltaic (PV) solutions to the III-V premium standard has shifted the focus to silicon solar cells. Indeed, leveraging on existing maturity of terrestrial PV silicon devices and processes offers significant potential for innovation and cost reduction. Many satellites nowadays evolve in Low Earth Orbit, a proton and electron rich environment. Such irradiations induce electrically active defects in the material which affect the PV performances. Interestingly, some of the irradiation-induced defects can be healed upon external factors such as temperature and/or photons flux.
The main goals of this PhD thesis will be to i) understand the bulk & interface electron/proton irradiation-induced degradation mechanisms driving the evolution of the optoelectronic properties of silicon passivated contacts solar cells ii) develop a comprehensive understanding of the self-healing effects in irradiated modern silicon solar cells through experimental studies and modeling iii) identify design / fabrication process routes to control & boost the self-healing capability.
To reach these goals, this PhD work will go through defined steps: bibliography review, solar cells fabrication, material/device ageing under proton & electron irradiations, advanced characterizations and modeling. This PhD work will be conducted at CEA/Liten, on the INES campus (Le Bourget du Lac, FR) with frequent interactions with CNES (Toulouse, FR) facilities.
Sustainable development of digital circuits and systems: Taking planetary boundaries into account
Technological developments in the electronics sector are experiencing rapid growth, accompanied by increasing interest in accounting for their environmental impacts. However, current approaches remain largely focused on relative impact reductions (energy efficiency, resource optimization), without ensuring compatibility with planetary boundaries. In this context, the concept of absolute sustainability emerges as an essential framework for guiding future developments of electronic systems.
This PhD thesis addresses several major scientific challenges: how can carrying capacities and sharing principles (core concepts of absolute sustainability) be identified for the electronics sector and consistently translated down to the levels of digital systems and integrated circuits? How can planetary boundaries be concretely integrated into the design of systems and circuits?
The main objective of the thesis is to move from a logic of relative environmental impact reduction toward designs that are compatible with planetary boundaries. It aims to define socio-technical scenarios to identify sharing principles, to conduct the first absolute life cycle assessment of a digital system, and to propose the first design of a circuit based on absolute limits, paving the way for sustainable development in electronics.
Enhancing Faradaic Efficiency in Protonic Ceramic Electrolysis Cells (PCCELs) through Electrolyte and Electrode–Electrolyte Interface Engineering
Proton conducting ceramic electrolysis cells (PCCELs), an advanced variant of solid oxide electrolysis cells (SOECs), enable the direct production of hydrogen through steam electrolysis using proton-conducting electrolytes. Unlike conventional SOECs, which rely on oxygen ion (O²?) conductors, PCCELs operate at lower temperatures (~400–600?°C vs. 750–850?°C for SOECs) due to their higher proton conductivity. This lower operating temperature helps reduce material degradation and overall system costs. While SOEC technology has reached industrial maturity, with large-scale deployment projects underway, the development of PCCELs remains limited by several scientific challenges. These include the difficulty of densifying electrolytes (such as BaCeO3–BaZrO3) without barium volatilization during high-temperature sintering; the proton transport limitations posed by grain boundaries; and the poor control of electrode–electrolyte interfaces. This thesis aims to improve the faradaic efficiency of PCCELs by optimizing the microstructure of the electrolyte and engineering high-quality interfaces through targeted surface treatments. The methodology includes cell fabrication, interface engineering, and electrochemical evaluation. The ultimate goal is to establish robust and scalable processing protocols that enable PCCELs to achieve faradaic efficiencies above 95%, compatible with industrial-scale deployment.
Controlling the composition and microstructure to achieve high magnetic performance in 1–12 rare earth-poor magnets
Permanent magnets based on rare earth elements (REEs), particularly neodymium-iron-boron (Nd-Fe-B) magnets, are strategically important for the development of more efficient motors and generators (electric vehicles, wind turbines). However, REEs, particularly Nd, are critical materials, with a high risk of supply disruption in the coming years. The growing demand for high-performance magnets requires the development of new types of magnets with reduce RE content. Iron-rich compounds, such as Sm-Fe12 (commonly known as phase 1-12), have very interesting intrinsic magnetic properties and are considered the best alternative to NdFeB magnets, allowing for a TR saving of around 35% by weight. However, achieving sufficient magnetic performance (remanence > 1 T and coercivity > 800 kA/m) depends on obtaining a suitable microstructure and remains the main challenge in the development of Sm-Fe12 magnets.
The aim of the thesis is therefore to improve the magnetic performance of this new family of magnets, in particular by controlling the composition and distribution of phases at grain boundaries. The doctoral work will combine an advanced experimental approach (development of Sm-Fe12 alloys, characterization of equilibrium phases, magnet manufacturing, magnetic characterization) with knowledge of phase diagrams to define compositions and optimal manufacturing conditions to achieve the targeted magnetic performances.
Model-Driven DevOps for Cloud Orchestration : Bridging Design-Time and Runtime Guarantees
Model-Driven Engineering (MDE) has traditionally relied on a clear separation between design and runtime, but this boundary no longer holds in today's cloud-native and edge environments, where infrastructures are heterogeneous, dynamic, and continuously evolving. Assumptions validated at design time may become invalid during execution, and modern orchestration platforms such as Kubernetes or OpenStack, while effective, remain weakly connected to architectural modeling environments. This results in a structural gap between architectural specification and actual operational behavior. To bridge this gap, this thesis proposes to develop a formal modeling framework for placement constraints across heterogeneous orchestration platforms, ensuring continuity between design-time validation and runtime guarantees. This framework would elevate placement constraints — resource locality, affinity, network latency, security isolation, and quality-of-service objectives — to first-class modeling constructs. At design time, it would enable static feasibility analysis and automated generation of deployment artifacts; at runtime, it would ensure continuous compliance monitoring and adaptive reconfiguration in response to violations. Expected contributions include a formal modeling language, bidirectional transformations between design-time models and runtime representations, and integration with Papyrus-based tooling. The ultimate goal is to ensure that architectural intent remains consistent and verifiable throughout the entire system lifecycle, from initial design through to production operation.