Development and application of TERS/TEPL technique for advanced characterization of materials
TERS/TEPL (Tip-Enhanced Raman Spectroscopy and Tip-Enhanced Photoluminescence) are powerful analytical techniques developed for nanoscale material characterization. The recent acquisition of a unique and versatile TERS/TEPL equipment at PFNC (Nano-characterization Platform) of CEA LETI opens up new horizons for materials characterization. This tool combines Raman spectroscopy, photoluminescence, and scanning probe microscopy. It features multi-wavelength capabilities (from UV to NIR), allowing a wide range of applications and providing unparalleled insights into the composition, structure, and mechanical/electrical properties of materials at nanoscale resolution. The current project aims to develop and accelerate the implementation of the TERS/TEPL techniques at PFNC to fully exploit its potential in diverse ongoing projects at CEA-Grenoble (LETI/LITEN/IRIG) and with its partners.
Immunotargeting of based-organic nanoparticles for clinical applications
The project aims to tailor-make based-organic nanocarrier enabling to target antibodies to increase the efficacy of therapy (more particularly mantle cell lymphoma) for clinical applications. Our group has developed a unique delivery system based on lipid nanoparticles for imaging and therapeutic purposes since the last 6 years. Based on this technology, the candidate will:
- optimize the targeting of specific ligands into organic nanoparticles (bioconjugate chemistry)
- optimize the encapsulation of drugs in the immunotargeted nanoparticles
- assess the physico-chemical characterization of all nanoparticles
- evaluate the binding affinity of doped and targeted nanoparticles
Droplets motion through modulation of surface energy gradient
Droplet motion through electro-wetting is nowadays largely studied and used in several systems and applications. In order to be useful, this technique needs an electrical field to monitor the droplet. For this post-doctoral fellowship, the main objective is to define an alternative method to the using of the electro-wetting technique in order to generate a droplet motion. The elaboration of surfaces with energy gradients conceived by thin film deposition or by laser ablation will be realized inside this study. The main difficulty is related to the patterns realization in order to obtain the appropriate hydrophilic/hydrophobic resolution. Apart from these “classical” techniques, an innovative method will be studied here by using switchable molecules. These molecules could modify the contact angle between a surface and a droplet, when acting on the potential of hydrogen (pH) or the wall temperature. For all the defined surfaces, the post-doctoral fellow will also analyze the coupling effect between the surface energy gradient and a thermal energy gradient on the droplet motion dynamics.
Batteries recycling :Development and understanding of a new deactivation concept of lithium ion domestic batteries
Domestic lithium ion batteries gather all batteries used in electronic devices, mobile phone, and tooling applications. By 2030, the domestic lithium-ion battery market will increase up to 30%. With the new European recycling regulation and the emergency to find greener and safer recycling process, it is today necessary to develop new deactivation process of domestic lithium ion batteries.
The process has to address several lithium ion chemistries, be continuous, safe, controllable and low cost.
To develop this new concept, the first step will be to define the most appropriate chemical systems. Then these chemical systems will be tested in a dedicated experimental laboratory setup using chemistry and electrochemistry, allowing the simulation of real conditions of domestic batteries deactivation.
The third step will be to characterize, understand and validate the electrochemical and physico chemical mechanisms. The last step will be to participate to the validation of the deactivation concept on a real object (a lap top battery) in representative conditions (on the abuse tests plateform of CEA).
Unsupervised Few-Shot Detection of Signal Anomalies
Our laboratory, located at Digiteo in CEA Saclay, is looking for a postdoc candidate working on the subject of anomaly detection in manufacturing processes, for a duration of 18 months starting from Feburary 2022. This postdoc is part of HIASCI (Hybridation des IA et de la Simulation pour le Contrôle Industriel), a CEA LIST project in an internal collaboration which aims at building a platform of AI methods and tools for manufacturing applications, ranging from quality control to process monitoring. Our laboratory contributes to HIASCI by developping efficient methods of anomaly detection in acoustic or vibrational signals, operating with small amounts of training data. In this context, the detection of signal anomalies (DSA) consists of extracting from data the information about the physical process of manufacturing, which is in general too complex to be fully understood. Moreover, real data of abnormal states are relatively scarce and often expensive to collect. For these reasons we privilege a data-driven approach under the framework of Few-Shot Learning (FSL).
Lensfree Cytometry for High-troughput biological analysis
The new lensfree imaging is against the foot of the recent developments in microscopy that focuses today on super-resolution achievements. Instead lensfree imaging offers several advantages: field of view (FOV) can cover several cm2, resolution in the range of 0.5µm to 3µm, mostly compact sizes and ease of use. The technique is based on holography online as invented by Gabor [1]. A biological object is illuminated by a coherent light, micrometric structures of the object diffract and the light interferes with the incident wave. The amplitude of the interference is recorded by a CMOS sensor and the image is reconstructed thanks to inverse-problem approaches. Albeit the method exists since 1970, the recent development of large field, small pixel size digital sensors helped realize the full potential of this method only since 2010.
At CEA-LETI Health Division, a new microscopic platform based on this principle has been developed. Its applicability for performing high-throughput monitoring of major cell functions such as cell-substrate adhesion, cell spreading, cell division, cell division orientation, cell migration, cell differentiation, and cell death have been demonstrated [2,3]. The new project proposed in this PostDoc is dealing with the development of an innovative lensfree cytometry setup aiming at high-throughput analysis of biological samples, e.g. cell counting, cell sorting, etc. The post-doctoral fellow will develop the instrumentation and methods and will conduct the experimentation and analysis of true biological samples.
Simultaneous Localisation and Mapping with an RGB-D camera based on a direct and sparse method
Recent advances in the methods of locating a device (smartphone, robot) in relation
to its environment make it possible to consider the deployment of augmented reality solutions and autonomous robots. The interest of RGB-D cameras in such a context is notable since it allows to directly acquire the depth map of the perceived scene.
The objective of this post docorate consists in developping a new SLAM (Simultaneous Localisation and Mapping) method relying on a depth sensor.
To reach a solution both robust, accurate and with small CPU/memory comsumption, the depth image will be exploited though a direct and sparse approach. The resulting solution will be then combined with the solution of "RGB SLAM Constrained to a CAD model" developped in our laboratory, resulting finaly in an "RGB-D SLAM Constrained to a CAD model"
Study of the thermo-mechanical strains in the HEMT AlGaN/GaN on silicon
Fabricating the HEMT AlGaN/GaN device is complex and leads to the formation of crystalline defects. These strains, in the GaN layer, leads to crackings in the GaN layer or leads to a delamination at the top interface. Moreover, these mechanical strains conjugated to thermal strains during device working, can lead to a degradation of the electrical performance of the device.
This heterogeneous assembly, involve a complex behaviour. The various materials used, react differently to the thermal-mechanical strains. The requested work is to study and to model the distortion of this structure, in order to evaluate the strains effects on the electrical performance on lateral and vertical devices.
Automatic driving of a finite element software based upon a domain decomposition strategy. Application to ultrasonic non-destructive testing.
One the most important field of activity at the DISC (Department of Imaging and Simulation for Control) of CEA - LIST is to provide a comprehensive set of tools for modeling and simulation for Non-Destructive Testing (NDT). These tools are gathered within the computational platform CIVA. Most of the ultrasound models -- elaborated by the LSMA (research laboratory for Simulation and Modeling in Acoustics) -- are based upon semi-analytical methods. Although very efficient, these methods suffer from a loss of precision as soon as some critical phenomena (e.g. head waves or caustics) or some particular features of the material (e.g. flaws or heterogeneities ) appear in the control experiment. To circumvent these limitations, one of the field of research in the LSMA is to build coupling schemes between semi-analytical and numerical methods. Following this strategy, a computational software based upon high-order finite elements combined with domain decomposition strategies is developped in order to address 3D configurations. The work proposed here focuses on increasing the complexity of the configurations reachable within this coupling strategy. A typical example being the fluid-structure interaction in the case of flaws reaching the bottom of the material to control.
Predictive design of heat management structures
Heat management is a paramount challenge in many cutting edge technologies, including new GaN electronic technology, turbine thermal coatings, resistive memories, or thermoelectrics. Further progress requires the help of accurate modeling tools that can predict the performance of new complex materials integrated in these increasingly demanding novel devices. However, there is currently no general predictive approach to tackle the complex multiscale modeling of heat flow through such nano and micro-structured systems. The state of the art, our predictive approach “ShengBTE.org”, currently covers the electronic and atomistic scales, going directly from them to predict the macroscopic thermal conductivity of homogeneous bulk materials, but it does not tackle a mesoscopic structure. This project will extend this predictive approach into the mesoscale, enabling it to fully describe thermal transport from the electronic ab initio level, through the atomistic one, all the way into the mesoscopic structure level, within a single model. The project is a 6 partner effort with complementary fields of expertise, 3 academic and 3 from industry. The widened approach will be validated against an extensive range of test case scenarios, including carefully designed experimental measurements taken during the project. The project will deliver a professional multiscale software permitting, for the first time, the prediction of heat flux through complex structured materials
of industrial interest. The performance of the modeling tool will be then demonstrated in an industrial setting, to design a new generation of substrates for power electronics based on innovating layered materials. This project is expected to have large impacts in a wide range of industrial applications, particularly in the rapidly evolving field of GaN based power electronics, and in all new technologies where thermal transport is a key issue.