Data science for heterogeneous materials
In order to predict the functional properties of heterogeneous materials through numerical simulation, reliable data on the spatial arrangement and properties of the constitutive phases is needed. A variety of experimental tools is commonly used at the laboratory to characterize spatially the physical and chemical properties of materials, generating "hyperspectral" datasets. A path to progress towards an improved undestanding of phenomena is the combination of the various imaging techniques using the methods of data science. The objectives of this post-doc is to enrich material knowledge by developping tools to discover correlations in the datasets (for exemple between chemical composition and mechanical behavior), and to increase reliability and confidence in this data by combining techniques and physical constraints. These tools will be applied to datasets of interest regarding cementitious materials and corrosion product layers from archaeological artifacts.
Study of a transient regime of helium dispersion to simulate an accidental release of hydrogen from a fuel cell.
CEA and industrial partners want to improve their knowledge, models and risk mitigation means for the conséquences of an accidental release of hydrogen from a H2 Fuel Cell. The dispersion of helium as a replacement for hydrogen takes place in a private garage and the transient state will be studied. Different scenarios of release are considered: from a cubic idealized fuel cell, then with different aspect ratios and finally with varying main dimension. The goal is to study some scaling effects. For the first case, we will measure helium concentration with katarometres and possibly velocity fields with PIV methods. Then mitigation processes will be tested. At last comparisons with models and numerical simulations will be performed.
Development of a cell analysis algorithm for phase microscopy imaging
At CEA-Leti we have validated a video-lens-free microscopy platform by performing thousands of hours of real-time imaging observing varied cell types and culture conditions (e.g.: primary cells, human stem cells, fibroblasts, endothelial cells, epithelial cells, 2D/3D cell culture, etc.). And we have developed different algorithms to study major cell functions, i.e. cell adhesion and spreading, cell division, cell division orientation, and cell death.
The research project is to extend the analysis of the datasets produced by lens-free video microscopy. The objective is to study a real-time cell tracking algorithm to follow every single cell and to plot different cell fate events as a function of time. To this aim, researches will be carried on segmentation and tracking algorithms that should outperform today’s state-of-the-art methodology in the field. In particular, the algorithms should yield good performances in terms of biological measures and practical usability. This will allow us to outperform today’s state-of-the-art methodology which are optimized for the intrinsic performances of the cell tracking and cell segmentation algorithms but fails at extracting important biological features (cell cycle duration, cell lineages, etc.). To this aim the recruited person should be able to develop a method that either take prior information into account using learning strategies (single vector machine, deep learning, etc.) or analyze cells in a global spatiotemporal video. We are looking people who have completed a PhD in image processing, with skills in the field of microscopy applied to biology.
FDSOI technology scaling beyond 10nm node
FDSOI (Fully-Depleted Silicon On Insulator) is acknowledged as a promising technology to meet the requirements of emerging mobile, Internet Of Things (IOT), and RF applications for scaled technological nodes [1]. Leti is a pioneer in FDSOI technology, enabling innovative solutions to support industrial partners.
Scaling of FDSOI technology beyond 10nm node offers solid perspectives in terms of SoC and RF technologies improvement. Though from a technological point of view, it becomes challenging because of thin channel thickness scaling limitation around 5nm to maintain both good mobility and variability. Thus, introduction of innovative technological boosters such as strain modules, alternative gate process, parasitics optimization, according to design rules and applications, become mandatory [2].
The viability of these new concepts should be validated first by TCAD simulations and then implemented on our 300mm FDSOI platform.
This subject is in line with the recent LETI strategy announcement and investments to develop new technological prototypes for innovative technology beyond 28nm [3].
The candidate will be in charge to perform TCAD simulations, to define experiment and to manage them until the electrical characterization. The TCAD simulations will be performed in close collaboration with the TCAD team. The integration will be done in the LETI clean room in collaboration with the process and integration team. Candidate with out-of-the-BOX thinking, autonomy, and ability to work in team is mandatory.
[1] 22nm FDSOI technology for emerging mobile, Internet-of-Things, and RF applications, R. Carter et al, IEEE IEDM 2016.
[2] UTBB FDSOI scaling enablers for the 10nm node, L. Grenouillet et al, IEEE S3S 2013.
[3]https://www.usinenouvelle.com/article/le-leti-investit-120-millions-d-euros-dans-sa-salle-blanche-pour-preparer-les-prochaines-innovations-dans-les-puces.
Analysis of low abundance 144Ce and 106Ru isotopes by mass spectrometry
The aim of this project is to develop the high precision analysis of 144Ce and 106Ru by mass spectrometry in irradiated samples for the qualification of neutronic calculation codes. These two isotopes are present at low abundances in the samples of interest and display significant isobaric interferences with 144Nd and 106Pd respectively. To complete this project, the candidate will carry out the appropriate analytical developments in conventional laboratory on inactive samples. Then the procedure will be transposed in the active laboratory for validation with the analysis of real samples. In the case of 144Ce, the implementation of a coupling between high performance liquid chromatography (HPLC) and ICPMS-MC, combined with the isotope dilution technique for the precise determination of atomic contents is envisaged. For 106Ru, the 101Ru concentration will first be determined by ICPMS-Q and the 101Ru/106Ru ratio will be determined by HPLC/ICPMS-Q or HPLC/ICPMS-MC coupling to remove the 106Pd/106Ru interference.
AlGaN/GaN HEMTs transfert for enhanced electrical and thermal performances
Due to their large critical electric field and high electron mobility, gallium nitride (GaN) based devices emerge as credible candidates for power electronic applications. In order to face the large market needs and benefit from available silicon manufacturing facilities, the current trend is to fabricate those devices, such as aluminum gallium nitride (AlGaN)/GaN high electron mobility transistors (HEMTs), directly on (111) silicon substrates. However, this pursuit of economic sustainability negatively affects device performances mainly because of self-heating effect inherent to silicon substrate use. New substrates with better thermal properties than silicon are desirable to improve thermal dissipation and enlarge the operating range at high performance.
A Ph.D. student in the lab. has developed a method to replace the original silicon material with copper, starting from AlGaN/GaN HEMTs fabricated on silicon substrates. He has demonstrated the interest of the postponement of a GaN power HEMT on a copper metal base with respect to self heating without degrading the voltage resistance of the component. But there are still many points to study to improve the power components.
Post-doc objectives : We propose to understand what is the best integration to eliminate self-heating and increase the voltage resistance of the initial AlGaN/GaN HEMT. The impact of the component transfer on the quality of the 2D gas will be analyzed.
The same approach can be made if necessary on RF components.
Different stacks will be made by the post-doc and he will be in charge of the electrical and thermal characterizations. Understanding the role of each part of the structure will be critical in choosing the final stack.
This process will also be brought in larger dimensions.
This post-doc will work if necessary in collaboration with different thesis students on power components.
Nano-silicon/graphene composites for high energy density lithium-ion batteries
This postdoctoral fellowship is part of the Graphene Flagship Core 2 H2020 european project (2018-2020) on the energy storage applications of graphene. In lithium-ion batteries, graphene associated to nanostructured silicon in a proper composite helps increase the energy capacity. Indeed graphene wraps silicon, reducing its reactivity with electrolyte and the formation of the SEI passivation layer. It also maintains a high electrical conductivity within the electrode.
The study will compare two technologies: graphene-silicon nanoparticles and graphene-silicon nanowires. The former composite, already explored in the above mentioned project, will be optimized in the present study. The latter is a new kind of composite, using a large scale silicon nanowire synthesis process recently patented in the lab. The postdoc will work within two laboratories: a technological research lab (LITEN) with expertise in batteries for transportation, and a fundamental research lab (INAC) with expertise in nanomaterial synthesis.
The postdoc will synthesize silicon nanowires for his/her composites at INAC. Following LITEN know-how, she/he will be in charge of composite formulation, battery fabrication and electrochemical cycling. He/she will systematically compare the electrochemical behavior of the nanoparticle and nanowire based silicon-graphene composites. Comparison will extend to the mechanism of capacity fading and SEI formation, thanks to the characterization means available at CEA Grenoble and in the European consortium: X-ray diffraction, electronic microscopy, XPS, FTIR, NMR spectroscopies. She/he will report her/his work within the international consortium (Cambride UK, Genova Italy, Graz Austria) meetings.
A 2-year post-doctoral position is open.
PhD in materials science is requested. Experience in nanocharacterization, nanochemistry and/or electrochemistry is welcome.
Applications are expected before May 31st, 2018.
Design for reliability for digital circuits
Flash memories are a key enabler for high-temperature applications such as data acquisition and engine control in aerospace, automotive and drilling industries. Unfortunately, the retention time of flash memories is very sensitive to high temperatures. Even at relatively moderated temperatures, flash memories may be affected by retention-related problems especially if they are set to store more than one bit per cell. This impact can be mitigated by periodically refreshing the stored data. The problem is that, in the presence of a variable operating temperature that could be due to variable environmental and workload conditions, a fixed data-refresh frequency may become disproportionately large with a subsequent impact on response time and cycling endurance.
The first objective of this project is to implement a data-refresh method based on a specially designed counter that is able to (a) track the evolution of the temperature and its impact on the data retention time of Flash memory blocks, (b) trigger warnings against potential retention time hazards and (c) provide timestamps.
The second objective is to find the distribution law that gives the evolution of the number of data retention errors in time. The goal is to implement a methodology able to infer the remaining retention time of flash memory pages based on their data retention age, i.e., the elapsed time since data was stored, and the number of retention and non-retention errors.
The publication of the scientific results in high-ranked conferences and journals is major project objective.
Physisorption of chemical species on sensitive surfaces during transfer in controlled mini-environment in microelectronics industry
A characterization platform based on the connection concept between process and characterization tools through the use of a transfer box under vacuum was implemented allowing a quasi in-situ characterization of substrates (wafers) of the microelectronics. Currently, this transfer concept based simply on static vacuum inside a carrier box is satisfactory regarding the residual O or C on the surface of especially sensitive materials (Ge, Ta, Sb, Ti…) and the MOCVD layers growth on GST or III/V surfaces. Its optimization for more stringent applications (molecular bonding, epitaxy…) in terms of contamination surface prevention requires studies the understanding of the physico-chemical evolution of the surfaces.
The proposed work will be focused on physico chemical studies of the evolution and molecular contamination of surfaces during transfers and will take place in clean room. XPS, TD-GCMS and MS coupled to the carrier itself (to be implemented) will be used to address the sources (wall, seals, gaseous environment…) of the adsorbed chemical species implied and to determine the physisorption mechanisms on the substrates. The studied surfaces will be sensitive to the contaminants in such a way than the box environment impact will be extracted and studied parameters will be the nature of polymer seal used, the carrier box thermal conditioning, the vacuum level, the use of low pressure gaseous environment in the carrier (gas nature, pressure level…).