Contribution of metal-semiconductor interfaces to the operation of the latest generation of infrared photodiodes
This thesis concerns the field of cooled infrared detectors used for astrophysical applications. In this field, the DPFT/SMTP (Infrared Laboratory) of CEA-LETI-MINATEC works closely with Lynred, a world leader in the production of high-performance infrared focal planes. In this context, the infrared laboratory is developing new generations of infrared detectors to meet the needs of future products.
One of the current development axes concerns the quality of the p-type semiconductor metal interface. These developments are driven by the increase in the operating temperature of the detectors, as well as by the very strong performance requirements for space applications.
The challenge of this thesis is to contribute to a better understanding of the chemical species present at the interface of interest as a function of different surface treatment types and to link them to the electrical properties of the contact made.
The candidate will join the infrared laboratory, which includes the entire detector production process. He/she will produce these samples using the technological means available in the LETI clean room, in collaboration with experts in the field. He/she will also have access to the necessary characterization tools (SIMS, XPS, AFM…) available on the nano-characterization platform (PFNC) or in the CEA clean room. Finally, he/she will be involved in the electro-optical characterization of the material, in collaboration with the Cooled Infrared Imaging Laboratory (LIR), which specializes in fine material characterization.
Development of deposit/etch processes for SADP integration to FD10 node
Developement of new technologic nodes involves both a pattern dimension shrink and a pattern density increase. For the last years, development of multi-Patterning strategies with in particular Spacer Patterning (also called SADP) has signifcantly increased. This approach is based on a sacrificial pattern on which a material is depsosited with a conformal configuration to be etched and thus to define spacers used as masks to pattern the sublayer after sacrificial pattern removals. One of the main challenges of this intergration is the material choice in terms of compatibility (thermal budget, selectivity, etc.). Using SiCo(N)-based materials could be a favourable alternative to standard dielectrics (SiO2, SiN). Another challenge is to achieve only one population after SADP : to prevent microloading effects, etching process with an atomic controlwill be developped (ex. pulsing, ALE, etc.). Environmental footprint should be considered during these process developments.
The purpose of this thesis is to set an integration flow with SiCO(N)-based materials, to developp these materials and to determine associated etching strategies.
To lead your research activity, you would be able to benefit privileged environment offered by CEA-Leti with state of the art tool for process development and for material characterization
Tool supported model completion with support for design pattern application
Generative AI and large language models (LLMs), such Copilot and ChatGPT can complete code based on initial fragments written by a developer. They are integrated in software development environments such as VS code. Many papers analyse the advantages and limitations of these approaches for code generation, see for instance Besides some deficiencies, the produced code is often correct and the results that are getting increasingly better.
However, a surprisingly small amount of work has been done in the context of completion software models (for instance based on UML). The paper concludes that while the performance of the current LLMs for software modeling is still limited (in contrast to code generation), there is a need that (in contrast to code generation) we should adapt our model-based engineering practices to these new assistants and integrate these into MBSE methods and tools.
The integration of design-patterns is a complementary part of this work. Originally coming from building architecture, the term design patterns has been adopted in the software domain to capture a proven solution for a given problem along with its advantages and disadvantages. A bit later, the term anti-pattern has been proposed to identify patterns that are known not to work or having severe disadvantages. Thus, when proposing a completion, then assistant could explicitly reference an existing design pattern with its implications. The completion proposal can be based either on identified model fragments (including modeled requirements) or an explicit pattern selection. This thesis will explore the state-of-the-art of model completion with AI and design patterns and associated tool support. Up to now, little work is available on pattern formalization and the use in model tools. It will propose to identify the modelers intention, based on partial models. The task could be rule-based but should also explore machine-learning approaches. Implement a completion proposal in the context of a design tool, notably Papyrus SW designer. The solution will be evaluated.
Scatterometry measurement of the exposure focal length of photolithography tools
Since the late 2000s with the advent of 45nm CMOS nodes, the control of critical dimensions (CD) of the structures in the photolithography stage has become critical to the reliability of printed circuit boards. Optical photolithography remains the most economical and widespread technique for high volume production in the semiconductor industry. For this type of equipment, manufacturers have focused on increasing the numerical aperture of the exposure lens, reducing sources of optical aberrations and on metrology to ensure efficient monitoring of their machines. These developments were possible at the expense of the depth of field of the exposure. To avoid altering the images transferred to the photosensitive resins, and ultimately have a device failure, it is essential to give a value as accurate and precise as possible of this size. To meet the growing needs of process control and lithography tools required by the most advanced technologies, metrology techniques based on analysis of reflected signals are massively used. Although this methodology is well suited to current CMOS technologies (CMOS14nm and earlier), it is unlikely to address more advanced technologies, so other techniques must emerge, such as techniques based on the analysis of the diffracted signal (scatterometry).
Innovative dry etching process of exotic materials
The advantageous properties (electro-optical, - acoustic, -mechanical) of new materials such as Sc-doped ALN, LNO, LTO or KNN make them essential to meet the development needs of integrated optics, RF telecommunication and microsystems. The production of patterns with submicron dimensions with a significant etch rate (>100nm/min), a vertical profile and a reduced roughness of the pattern's sidewalls are the main goals of the thesis work so as to satisfy the performance criteria of the devices targeted at the application level.
Stabilisation of Perovskite photovoltaic devices by passivation with Metal-Organic Frameworks type materials
MOFs are a type of porous organic-inorganic hybrid material with interesting properties in terms of the passivation of defects in the perovskite and its stability, particularly versus light. For example:
- Direct effect of MOF components as passivation agents: Metal ions and organic ligands can passivate defects at the MOF/PK interface.
- Downconversion of incident radiation: Certain metals (such as europium) or ligands (with aromatic groups) can absorb high-energy radiation (typically violet/near-UV), then re-emit this energy in the form of lower-energy radiation or transmit it directly in a non-radiative manner to the perovskite by Förster resonance (or FRET). This protects the perovskite from high-energy photons, and therefore a priori improves light stability, with little energy loss.
The thesis work will focus on
- integrating MOFs into the perovskite layer, either as a surface treatment or as a mixture of suspensions
- Materials studies (in particular advanced studies using XPS and UPS)
- Favrication of single-junction devices and then tandem devices with silicon sub-cells
- Study of lifetime under illumination (continuous, cycling) with associated characterisations (electrical measurements, photoluminescence, etc.).
Elucidation of the Correlation between the Electrochemical Activity of Oxygen Reduction and the Molecular Structure of the Platinum/Ionomer Interface in Proton Exchange Membrane Fuel Cells
This thesis focuses on the Proton Exchange Membrane Fuel Cell (PEMFC), used in the transportation sector to generate electricity and heat from hydrogen and oxygen. Although promising for reducing CO2 emissions through the use of green hydrogen, the PEMFC needs to enhance its performance and durability to compete with combustion engines and batteries. The electrode plays a crucial role, but the molecular complexity of the electrochemical interface between the platinum-based catalyst and the ionomer makes characterization challenging. Currently, the qualitative understanding of this interface is limited, impeding progress and model predictability. The thesis aims to establish a correlation between the molecular structure of the electrochemical interface and the electrochemical kinetics, focusing on platinum oxidation and ionomer adsorption. A unique device developed at CEA allows simultaneous electrochemical and spectroscopic characterizations. The novelty lies in using Atomic Force Microscopy (AFM) coupled with Raman spectroscopy and synchrotron-based micro-infrared spectroscopy as original techniques to obtain crucial information for PEMFC applications.
The technology choice in the eco-design of AI architectures
Electronic systems have a significant environmental impact in terms of resource consumption, greenhouse gas emissions and electronic waste, all of which are experiencing a massive upward trend. A large part of the impact is due to production, and more particularly the manufacturing of integrated circuits, which is becoming more and more complex, energy-intensive and resource-intensive with new technological nodes. The technology used for the implementation of a circuit has direct effects on the environmental costs for production and use, the lifespan of the circuit and the possibilities of several life cycles in a circular economy perspective. The technological choice therefore becomes an essential step in the ecodesign phase of a circuit.
The thesis aims to integrate the exploration of different technologies into an eco-design flow of integreted circuit. The purpose of the work is to define a methodology for a systematic integration of the technological choice into the flow, with identification of the best configuration of the architecture implemented for maximizing the lifespan and taking into account the strategies of circular economy. The architectures targeted by the thesis fall into the field of embedded AI, which is experiencing an upward deployment trend and involves major societal challenges. The thesis will constitute a first step in research towards sustainable embedded AI.
Design of 4D printable and biocompatible polysaccharide hydrogels for biomedical applications.
The 3D printing of stimuli-responsive materials is called “4D printing” and is of great interest for the development of innovative medical devices (dynamic synthetic tissues, soft robotic actuators, controlled drug release systems etc.). Reported examples of these printable smart materials are programmed to autonomously change their shape in response to specific stimuli (e.g. temperature, light, magnetic field, pH, etc.) but are almost exclusively based on synthetic polymers.
To transpose this concept to biomedical application, this PhD project aims at designing 3D printable, biocompatible and stimuli-responsive polysaccharide hydrogels. In particular, the targeted hydrogels will be able to deform under two different stimuli: (i) a temperature variation or (ii) the application of a near-infrared (NIR) beam for the material activation without deterioration of biological tissues. These will be achieved by combining (i) polysaccharide chains functionalized with thermoresponsive groups and (ii) photothermal nanoparticles capable of converting NIR light into heat.
This interdisciplinary project is at the interface between Chemistry (polymer chemistry, nanoparticle synthesis), Physical Chemistry (formulation and characterization of hydrogels), Materials Science (3D printing studies, mechanical tests) and Biology (cytocompatibility studies). An additional originality is that the experimental data collected by the PhD candidate will be fed into artificial intelligence tools which, in turn, should provide guidelines to accelerate the discovery of the targeted materials.
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.