Analysis and experimental study of capillary structures to mitigate the influence of magnetogravitational forces on liquid helium cooling for future HTS superconducting magnets
As physics requires increasingly higher magnetic fields, CEA is called upon to develop and produce superconducting magnets capable of generating magnetic field of more than 30 T. The windings of these electromagnets are made from superconducting materials whose electrical resistance is extremely low at cryogenic temperatures (a few Kelvins). This enables them to carry high currents (>10 kA) while dissipating a minimum of heat by Joule effect. Cooling at these low temperatures is achieved using liquid helium. But helium is diamagnetic. Magnetic fields will therefore induce volumetric forces that add to or oppose gravity within the helium. These magneto-gravity forces disrupt the convective phenomena required to cool the superconducting magnet. This can lead to a rise in their temperature and a loss of their superconducting state, which is essential for their proper operation. In order to circumvent this phenomenon, a new cooling system never used in cryomagnetism will be studied. This cooling system will be developed using heat pipes whose operation is based on capillary forces that are theoretically independent of the magneto-gravity forces induced by strong magnetic fields. These capillary structures can take several forms (microchannels, foam, mesh, etc.). In the framework of the thesis these different structures will be studied theoretically and then experimentally, both with and without magnetic forces, in order to determine the most suitable structures for the future superconducting magnets.
Development of highly reactive bio-based polyhydroxyurethanes for the substitution of isocyanates in polyurethanes
Polyurethanes are thermosetting materials with significant environmental impacts. They are primarily synthesized from isocyanates, which are highly hazardous substances (toxic, sensitizing, and some even classified as CMR - Carcinogenic, Mutagenic, or Reprotoxic) and are subject to REACH restrictions. In this context, polyhydroxyurethanes (PHUs) offer several advantages: (i) they are more easily bio-based compared to conventional PUs, (ii) their synthesis does not involve isocyanates, but (iii) instead allows for CO2 sequestration. However, the precursors used in the synthesis of PHUs (cyclic carbonates and amines) exhibit much lower reactivity than isocyanates, resulting in curing times that are currently incompatible with the temperatures and production rates required for this type of material.
Several research directions have been proposed to optimize PHU curing kinetics, focusing on the identification of (i) new cyclic carbonate and amine precursors chemically substituted at the a or ß positions of the reactive group, and (ii) new high-performance catalysts capable of activating both types of precursors used in synthesis.
In this context, the PhD candidate will be tasked with synthesizing new cyclic carbonate and amine precursors and studying their reactivity to identify the most favorable conditions for the synthesis of highly reactive PHUs. The results obtained during this work will then be analyzed using symbolic Artificial Intelligence models developed at CEA.
This PhD project is part of the PHURIOUS project, funded by the PEPR DIADEM program, which aims to integrate high-throughput synthesis and characterization techniques in polymer chemistry with digital tools, including DFT calculations, molecular dynamics simulations AI approaches.
AI-assisted generation of Instruction Set Simulators
The simulation tools for digital architectures rely on various types of models with different levels of abstraction to meet the requirements of hardware/software co-design and co-validation. Among these models, higher-level ones enable rapid functional validation of software on target architectures.
Developing these functional models often involves a manual process, which is both tedious and error-prone. When low-level RTL (Register Transfer Level) descriptions are available, they serve as a foundation for deriving higher-level models, such as functional ones. Preliminary work at CEA has resulted in an initial prototype based on MLIR (Multi-Level Intermediate Representation), demonstrating promising results in generating instruction execution functions from RTL descriptions.
The goal of this thesis is to further explore these initial efforts and subsequently automate the extraction of architectural states, leveraging the latest advancements in machine learning for EDA. The expected result is a comprehensive workflow for the automatic generation of functional simulators (a.k.a Instruction Set Simulators) from RTL, ensuring by construction the semantic consistency between the two abstraction levels.
Development of a multi-criteria comparison tool for electrochemical stationary storage systems
Use of stationary storage systems is now essential to keep pace with changes in the electricity grid and the growing integration of intermittent renewable energies such as solar and wind power. The choice of a storage solution is based on a number of criteria, including performance, lifetime, environmental impact, safety, regulatory constraints and, of course, economics.
The laboratory possesses comparative data on these different criteria, via experimental studies and feedback on existing systems. In addition, an initial software tool has been developed to assess environmental impact using LCA (Life Cycle Assessment). The aim of this thesis work is to integrate these different components into a broader comparison tool with a multi-criteria approach, targeting specific case studies and a limited number of storage technologies that have reached sufficient maturity for the available data to be reliable.
High yield strength austenitic stainless steels for nuclear applications: numerical design and experimental study
The PhD thesis is part of a project that aims at designing new austenitic stainless steels grades for nuclear applications, which are specifically suitable to in-service conditions encountered by the components and to the manufacturing process. More precisely, the subject deals with bolt steels achieved by controlled nitriding of powders which are then densified by hot isostatic pressing. Indeed, current bolt steel grades may suffer from stress corrosion cracking, while nitriding allows to increase the chromium content, which is beneficial from that point of view.
The study will start by the definition of specifications and associated criteria, then CALPHAD calculations in the Fe-Cr-Ni-Mo-X-N-C system will be done to define promising compositions. Then, selected compositions will be supplied as powders. The behaviour of powders during nitriding will be studied and modelled. Samples will be nitrided, densified and heat treated. One grade will be then selected and fully characterised: mechanical properties and deformation mechanisms, corrosion behaviour. One important objective is to demonstrate the advantages of the new grade compared to the industrial solution.
Space-time Modulated Electromagnetic Metasurfaces for Multi-functional Energy-Efficient Wireless Systems
Next-generation (XG) wireless systems envision an unprecedented network densification and the efficient use of the near-millimeter-wave (mmW) spectrum. Disruptive concepts are required to minimize the number of antenna systems and their power consumption. Reconfigurable intelligent surfaces (RISs) can provide high-gain beam-forming using simple devices (e.g. p-i-n diodes) to control their scattering properties of their unit-cells. However, the efficiency of an RIS and the wireless functions it can simultaneously realize, are bound by its inherent linearity and reciprocity.
Space-time modulated metasurfaces (STMMs) have recently emerged as a beam-forming solution overcoming fundamental limits of linear time-invariant systems. Leveraging an additional time-variation of the unit-cell response, with respect to RISs, an STMM can tailor at the same time angular and frequency spectra of the radiated fields, without using multiple active circuits as in current systems.
Most models for the design of STMMs are oversimplified and consider 1-D modulations in quasi-static temporal regime. The impact of spatial discretization and phase quantization is overlooked. The few reported prototypes are often electrically small, with a coarse (half-a-wavelength) period. Most demonstrators operate in reflection, below 17 GHz and enable only a 1-bit phase resolution. Independent far-field beam-steering at several frequencies has been proved in a single scan plane.
This Ph.D. thesis aims at modelling, designing and demonstrating electrically large and multi-functional transmissive STMM antennas with enhanced phase resolution and beam-forming capabilities. Efficient numerical models will enable the computation of the fields scattered by a STMM in far- and near-field regions, for arbitrary spatial and time modulation periods. Holographic and compressive sensing techniques will be proposed to jointly optimize the metasurface phase profile and the time-modulation waveforms, enabling harmonic beam-shaping. A thorough study of the effect of phase resolution, STMM period and time-modulation frequency on the performance, power consumption and complexity of the control electronics will be provided.
A transmissive STMM prototype based on p-i-n diodes and enabling a 2-bit phase resolution will be realized for the first time, building on the group background on space-modulated electronically reconfigurable flat lens antennas. It will work in a frequency range suited to terrestrial and satellite networks (17-31 GHz). Multiple antenna functionalities will be experimentally characterized using the same prototype, such as: (i) simultaneous and non-reciprocal 2-D beam-forming at different harmonics of the time-modulating signals, in either far-field or near-field region; (ii) pattern shaping at the fundamental frequency, using optimized time-sequences to increase the effective phase resolution.
The fundamental and experimental contributions of this research will broaden the physical insight on time-modulated metasurfaces and increase the maturity of this technology for energy-efficient smart antennas with applications to wireless networks and integrated communication and sensing systems. An intense dissemination activity in high-impact scientific journals of electrical engineering and applied physics is expected, given the novelty of the topic and the growing interest it triggers in several communities.
development of capacitive IIIV-Silicon modulators for emerging applications in silicon photonics
The proposed thesis work consists in developing phase modulators based on the integration of IIIV-Silicon hybrid capacitors in silicon waveguides, at a wavelength of 1.55µm to meet the emerging demands of photonics (optical computing on chip, LIDAR). Unlike telecom/datacom applications, which have enabled the emergence of integrated silicon photonics, these new application fields involve circuits that require a very large number of phase modulators. All-silicon modulators based on PN junctions, which have optical losses of several dB and centimeter sizes, are a bottleneck to the emergence of these applications.
IIIV-Si hybrid capacitors can allow, thanks to the electro-optical properties of IIIV materials, to reduce the size of silicon modulators by an order of magnitude and improve their energy efficiency (reduction of optical losses). First functional modulators have been designed, fabricated and tested. The first step will be to study in details their performance (losses, efficiency, speed, hysteresis) and to understand their limitations, using the available photonic simulation tools and electrical characterization methods (C(V), interface charge density, DLTS, etc.). In particular, this will involve better understanding the impact of the manufacturing process on the electro-optical properties. In a second step, the doctoral student will propose improvements to the designs and manufacturing processes (in collaboration with our microfabrication specialists), and will validate them experimentally using hybrid capacities and modulators integrating these capacities.
improving effiiciency and directivity in color conversion µLEDs with metasurfaces
In the field of augmented reality, the development of full color µLEDs matrices is a critical step towards miniaturizing and simplifying the optical system. Current pixel architectures in microLEDs displays are based on color conversion. Short wavelength emission from a first active material is absorbed by a second active layer to be re-emitted at longer wavelength. In current architectures, re-emission follows a lambertian profile making them unsuitable for AR/VR applications.
Recent work by the Charles Fabry laboratory - Institut d’Optique, as part of E. Bailly's thesis, has demonstrated that combining metasurfaces with color converters can enable shaping the radiation pattern. The primary goal of this thesis is to apply this innovative method by integrating it with blue GaN µLEDs developed at CEA-LETI.
Throughout this thesis, the student will first design the devices using optical simulations, aiming to optimize them for both efficiency and directional angular radiation pattern. Following this, the student will fabricate the devices in the clean room at LETI and perform opto-electrical characterization.
The initial design phase will primarily take place at the Quantum Nanophotonics and Plasmonics team of Charles Fabry laboratory - Institut d’Optique, in Saclay, under the supervision of the thesis director. The student will then move to CEA-LETI in Grenoble for the fabrication, characterization and comparison with simulation results.
The selected student will benefit from the extensive expertise in nano-photonics and simulation at the Charles Fabry laboratory, as well as the technological, simulation, and characterization expertise in µLEDs at CEA-LETI.
The Quantum Nanophotonics and Plasmonics at Institut d’Optique team investigates the physics and engineering of spontaneous light emission (fluorescence, incandescence, electroluminescence), at different scales (quantum regime with single photon and single atoms, collective effects, photon condensates, condensed matter systems…).
The LITE (Emissive Technologies Integration Laboratory) at CEA-LETI focuses on manufacturing microemitting devices (µLED, OLED, LCD) in a silicon microelectronics foundry-type environment. This includes, for example improving µdisplays performances, made above ASICs, while reducing the pixel size, or demonstrating new use cases of these light sources in the field of biomedical optical sensors.
Attention-based Binarized Visual Encoder for LLM-driven Visual Question Answering
In the context of smart image sensors, there is an increasing demand to go beyond simple inferences such as classification or object detection, to add more complex applications enabling a semantic understanding of the scene. Among these applications, Visual Question Answering (VQA) enables AI systems to answer questions by analyzing images. This project aims to develop an efficient VQA system combining a visual encoder based on Binary Neural Networks (BNN) with a compact language model (tiny LLM). Although LLMs are still far from a complete hardware implementation, this project represents a significant step in this direction by using a BNN to analyze the context and relationship between objects of the scene. This encoder processes images with low resource consumption, allowing real-time deployment on edge devices. Attention mechanisms can be taken into consideration to extract the semantic information necessary for scene understanding. The language model used can be stored locally and adjusted jointly with the BNN to generate precise and contextually relevant answers.
This project offers an opportunity for candidates interested in Tiny Deep Learning and LLMs. It proposes a broad field of research for significant contributions and interesting results for concrete applications. The work will consist of developing a robust BNN topology for semantic scene analysis under certain hardware constraints (memory and computation) and integrating and jointly optimizing the BNN encoder with the LLM, while ensuring a coherent and performant VQA system across different types of inquiries.