Study of new photodiode architecture for IR imagers
In the field of high-performance infrared detection, CEA-LETI plays a leading role in the development of the HgCdTe material, which today offers such performance that it is integrated into the James Webb Space Telescope (JWST) and allows the observation and study of deep space with unparalleled precision to date. However, we believe that it is still possible to make a significant step forward in terms of detection performance. Indeed, it seems that a fully depleted structure, called a PiN photodiode, could further reduce the dark current (and thus reduce noise and gain sensitivity at low photonic flux) compared to the non-fully depleted structures currently used. This architecture would represent the ultimate photodiode and would allow either a further increase in performance at a given operating temperature or a significant increase in the operating temperature of the detector, with the potential to open new fields of application by greatly simplifying cryogenics.
Your role in this thesis work will be to contribute to the development of the ultimate photodiode for very high-performance infrared detection, characterize and simulate the PiN photodiodes in HgCdTe technology manufactured on our photonic platform.
Candidate Profile:
You hold a Master's degree in optoelectronics and/or semiconductor material physics and are passionate about applied research.
The main technical skills required are: semiconductor component physics, optoelectronics, data processing, numerical simulations, interest in experimental work to carry out characterizations in a cryogenic environment but also theoretical work to carry out numerical simulations.
The PhD student will be integrated into a multidisciplinary team ranging from the growth of II-VI materials to electro-optical characterization, including microelectronics manufacturing processes in clean rooms and the packaging issues of such objects operating at low temperature.
3D interferometric imaging system with reception module in integrated optics
3D sensing by capturing depth images, is a key function in numerous emerging applications such as augmented reality, robotics and telemedicine. The laboratory has developed an innovative 3D sensing micro-optical prototype, using a frequency modulated Lidar technology with simultaneous illumination of the whole scene. The next step is the miniaturization of the setup with integrated optics. A first PhD is ongoing in the laboratory, focusing on the integration of the illumination module.
The proposed PhD will target the definition of an integrated optics architecture for the reception module. The main objective is to realize the beam recombination with integrated optics, using waveguides and grating couplers, to enable the heterodyne mixing of light back-scattered by the scene with the local oscillator. The candidate will design these integrated optical components in connection with the refractive optical system, simulate the propagation of the beams and interference using Lumericaland Zemaxsoftwares, contribute to device realization in clean room, perform the optical characterization of the components, and experimentally validate the proof of concept of depth imaging with the miniaturized prototype.
Depending on the progress of the developments, the PhD will include the development of a module combining the illumination and reception functions in a single component. Several patents, publications and presentations in international conferences are expected in the framework of this PhD.
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.
Development of micro-optic strcture for uncooled infrared imaging sensor
In this thesis, we aim to incorporate a low-resolution angular sorting function capable of discerning the primary direction of incident infrared flux. This information is crucial for enhancing image processing algorithms, thereby facilitating faster automatic focusing, improved image segmentation, and more accurate depth estimation.
To achieve this functionality, a micro-optics network at pixel level must be designed and realised. At present, we are considering two competitive approaches: refractive microlenses and meta-surfaces. As a PhD student, your responsibilities will include:
?- Establishing the preliminary specifications for these microlenses
?- Designing the micro-optics using numerical simulation and predicting their performance
?- Overseeing the manufacturing of these micro-optics in a clean room environment
?- Characterising the micro-optics on a dedicated laser bench and performing a proof of concept by coupling them with an infrared imager
You will be fully integrated into the Laboratory of Thermal and THz Imaging of the CEA Leti which develops, realizes, and characterizes imaging technologies based on micro-bolometers.
Design and integration of microlasers within a silicon photonics platform
For about ten years, the continuous increase in internet traffic has pushed the electrical interconnections of data centers to their limits in terms of bandwidth, density, and consumption. By replacing these electrical links with optical fibers and integrating all the necessary optical functions on a chip to create transmitters-receivers (transceivers), silicon photonics represents a unique opportunity to address these issues. The integration of a light source within a photonic chip is an essential building block for the development of this technology. While many demonstrations rely on the use of external lasers or bonded laser chips, it is the direct heterogeneous fabrication of a laser within the photonic chip that would allow the desired level of performance while limiting costs.
The objective of this thesis is to provide an innovative solution for the management of very short-distance communications (inter-chip, intra-chip) by realizing, on silicon, III-V membrane microlaserswith buried heterostructures. This type of microlasermeets the numerous challenges of very short-distance links thanks to an efficiency/integrabilitycompromise superior to the state of the art of datacomlasers while being compatible with CMOS fabrication lines.
Based on the work carried out during a previous thesis, the PhD student will be responsible for (i) designing the microlasersusing the available digital simulation tools in the laboratory, then (ii) manufacturing these microlasersby relying on the technological platforms of CEA-LETI, and finally (iii) electro-optically characterizing the components. This thesis work will be carried out in collaboration between CEA-LETI and LTM/CNRS and will constitute a strategic brick necessary for future generations of photonic transceivers.
Laser Fault Injection Applied to Reverse Engineering of Memories
Memories play a critical role for the security of cyber-physical systems. They manage sensitive data such as cryptographic keys and proprietary codes. With the increasing threat of hardware attacks, understanding and manipulating memory organization has become essential. The thesis aims to explore the application of laser attack techniques, specifically Thermal Laser Stimulation (TLS) and laser perturbation, to reverse engineer memory systems. The primary objective is to develop methods for extracting or modifying memory content, with a particular focus on validating TLS on FDSOI 22nm technology. Additionally, the thesis seeks to use laser perturbation for reconstructing memory architecture, analyzing error-correcting codes, and designing countermeasures. The research will leverage the infrastructures available at CEA (e.g.,https://github.com/CEA-Leti/secbench), as well as the expertise of the laboratory members.
Scalability of the Network Digital Twin in Complex Communication Networks
Communication networks are experiencing an exponential growth both in terms of deployment of network infrastructures (particularly observed in the gradual and sustained evolution towards 6G networks), but also in terms of machines, covering a wide range of devices ranging from Cloud servers to lightweight embedded IoT components (e.g. System on Chip: SoC), and including mobile terminals such as smartphones.
This ecosystem also encompasses a variety of software components ranging from applications (e.g. A/V streaming) to the protocols from different communication network layers. Furthermore, such an ecosystem is intrinsically dynamic because of the following features:
- Change in network topology: due, for example, to hardware/software failures, user mobility, operator network resource management policies, etc.
- Change in the usage/consumption ratio of network resources (bandwidth, memory, CPU, battery, etc.). This is due to user needs and operator network resource management policies, etc.
To ensure effective supervision or management, whether fine-grained or with an abstract view, of communication networks, various network management services/platforms, such as SNMP, CMIP, LWM2M, CoMI, SDN, have been proposed and documented in the networking literature and standard bodies. Furthermore, the adoption of such management platforms has seen broad acceptance and utilization within the network operators, service providers, and the industry, where the said management platforms often incorporate advanced features, including automated control loops (e.g. rule-based, expert-system-based, ML-based), further enhancing their capability to optimize the performance of the network management operations.
Despite the extensive exploration and exploitation of these network management platforms, they do not guarantee an effective (re)configuration without intrinsic risks/errors, which can cause serious outage to network applications and services. This is particularly true when the objective of the network (re)configuration is to ensure real-time optimization of the network, analysis/ tests in operational mode (what- if analysis), planning updates/modernizations/extensions of the communication network, etc. For such (re)configuration objectives, a new network management paradigm has to be designed.
In the recent years, the communication network research community started exploring the adoption of the digital twin concept for the networking context (Network Digital Twin: NDT). The objective behind this adoption is to help for the management of the communication network for various purposes, including those mentioned in the previous paragraph.
The NDT is a digital twin of the real/physical communication network (Physical Twin Network: PTN), making it possible to manipulate a digital copy of the real communication network, without risk. This allow in particular for visualizing/predicting the evolution (or the behavior, the state) of the real network, if this or that network configuration is to be applied. Beyond this aspect, the NDT and the PTN network exchange information via one or more communication interfaces with the aim of maintaining synchronized states between the NDT and the PTN.
Nonetheless, setting up a network digital twin (NDT) is not a simple task. Indeed, frequent and real-time PTN-NDT synchronization poses a scalability problem when dealing with complex networks, where each network information is likely to be reported at the NDT level (e.g. a very large number of network entities, very dynamic topologies, large volume of information per node/per network link).
Various scientific contributions have attempted to address the question of the network digital twin (NDT). The state-of-the-art contributions focus on establishing scenarios, requirements, and architecture for the NDT. Nevertheless, the literature does not tackle the scalability problem of the NDT.
The objective of this PhD thesis is to address the scalability problem of network digital twins by exploring new machine learning models for network information selection and prediction.
Analysis of solid oxide cell degradation by transmission electron microscopy and atomic probe tomography
Nowadays, high-temperature electrolysis is considered as one of the most promising technology for producing green hydrogen. The electrolysis reaction takes place in a Solid Oxide Cell (SOC) composed of an oxygen electrode (made of LSCF or PrOx) and a hydrogen electrode (made of Ni-YSZ) separated by an electrolyte (made of YSZ). To accompany industrialization f SOCs, the durability still needs to be improved. The main performance losses are due to the degradation of the two electrodes. In order to propose an improvement, it is essential to gain a precise understanding of electrode degradation mechanisms. In this thesis, we thus propose to apply high-resolution transmission electron microscopy and atom probe tomography (SAT) to study electrode degradation after aging under current. On the one hand, advanced electron microscopy techniques coupled with energy dispersive X-ray spectroscopy (EDX) and electron energy loss spectroscopy (EELS) will be applied. In addition, analyses carried out on a SAT will provide three-dimensional information particularly suited to the complex structure of the electrodes.
This work should provide a better understanding of the degradation mechanisms of high-temperature electrolysis cells. Recommendations for their manufacture can then be made to improve their lifespan.