Atomic sensors based on metastable 4He
Detection of weak magnetic fields opens the way to new techniques of medical imaging, geophysics and chemistry. Optically pumped magnetometers are currently the most accurate and precise sensors for magnetic fields [1]. Our lab works on optically-pumped magnetometers based on a thermal gas of helium-4 metastables, a spin-one electronic species. Our main achievement in last years has been the design and space qualification of the most recent generation of magnetometers available for spatial exploration, which were launched by ESA Swarm mission [2].
We are now starting a new project in order to explore further applications of magneto-optical effects of metastable helium. Indeed, dichroism and birefringence have been observed on 4He from the very first times of optical pumping [3] but, in strong contrast with alkali [4], the nonlinear regimes which can be reached from the introduction of 1083 nm lasers have been hardly studied. These regimes open new possibilities for realizing not only magnetometers but also other kind of useful sensors which address a broader range of industrial applications.
We are looking for a motivated postdoc candidate willing to work towards a better understanding of these effects but also towards harnessing them for building ultra-precise sensors. The applicant should have a PhD in physics, ideally with a good background in experimental atomic physics and/or laser physics. Our lab is well equipped and staff engineers will be available to assist the post doc on technical aspects related to optics, design of electronics and magnetic materials. The results will be divulgated in form both of journal publications and of patents.
[1] Kominis et al., Nature 422 (2003)
[2] http://smsc.cnes.fr/SWARM
[3] Laloë, Leduc, Minguzzi, Journal de Physique, 30 (1969)
S. Pancharatnam, J. Phys. B: At. Mol. Phys. 1 (1968).
[4] Budker et al., Rev. Mod. Phys. 74 (2002)
Wireless biological sensor using 2D materials (Graphene , Molybdenium disulfide)
The main goal of the post-doctoral position is the fabrication of a biological sensor using 2D materials and that can be remotely addressed thanks to a RF antenna simultaneously fabricated alongside the biosensor.
The post-doctoral associate will be in charge of the fabrication and characterization of the prototype. Starting from well-designed modelling, he/she will first establish a design architecture for the sensor and RF antenna. Once designed and sized, the post-doctoral associate will adapt existing transfer protocol of 2D materials to develop an innovative fabrication process for the sensor. He/she will then fabricate the first prototypes of the sensors. Consecutively he/she will validate first the remote addressing of the sensor via the RF antenna. Secondly he/she will lead biodétection tests to assess the sensitivity of the fabricated sensors. Finally, he/she will try to integrate Transition Metal Di-chalcogenides 2D materials (such as MoS2) to graphene sensors inside a hybrid 2D materials biological sensor. The goal here will be to boost operational sensitivity.
Development of a computational framework dedicated to model order reduction by certified reduced basis method.
Many engineering fields require to solve numerically partial differential equations (PDE) modeling physical phenomenon.
When we focus on a mathematical model that describes the physical behavior of a system based on one or more parametrized PDEs (geometrical or physical parameters), it may be desirable to rapidly and reliably evaluate the output of the model (quantity of interest)
for different parameter values.
The real-time context, needed to perform command-control, and contexts asking many evaluations of model outputs (typically for optimization methods or uncertainty and sensitivity analysis) lend themselves perfectly.
The certified reduced basis method is an intrusive reduction method beacause, unkike non-intrusive methods, the reduction is based on the projection of operators associated to physical model PDEs.
This method allow to obtain rapidly, for a given set of parameter values, an approximation of the evaluation of the model output.
One of the strengths of the method is the "certified" aspect to estimate the approximation error of the model output evaluation.
The goal of the post-doctorate is to develop a computational framework for the certified reduced basis method. This framework should be based on the TRUST platform (https://sourceforge.net/projects/trust-platform/) developed at CEA and will be generic enough to be used to deal with different types of problems (linear or not, stationary or not, coercive or not...)
The framework will be used in the case of a two-fluid mixing model.
Conversational Agent for Medical Serious Games
The LVIC laboratory participates in a research project which aims to develop innovative tools for teaching medical students. The training will be done through serious games of second generation, in which the learner can interact directly with the environment:
- immersed in a 3D environment with a Virtual Reality Head Mounted Display and motion detection,
- with natural and ecological handling of the environment (instruments, patient …),
- and a voice interaction with conversational and emotional avatars.
The multimedia team of LVIC laboratory is involved in the project to develop tools allowing students to interact in natural language with conversational avatars.
In this context, the post-doctoral researcher will be in charge of:
- studying the state of art of conversational agents;
- understanding and mastering the technological components of the laboratory language processing;
- proposing and developing a dialogue system allowing interaction in natural language with conversational avatars of the project.
Application of ontology and knowledge engineering to complex system engineering
Model-Based System Engineering relies on using various formal descriptions of the system to make prediction, analysis, automation, simulation... However, these descriptions are mostly distributed across heterogeneous silos. The analysis and exploitation of the information are confined to their silos and thereby miss the big picture. The crosscutting insights remain hidden.
To overcome this problem, ontologies and knowledge engineering techniques provide desirable solutions that have been acknowledged by academic works. These techniques and paradigm notably help in giving access to a complete digital twin of the system thanks to their federation capabilities, in making sense to the information by embedding it with existing formal knowledge and in exploring and uncovering inconsistencies thanks to reasoning capabilities.
The objective of this work will be to propose an approach that gives access to a complete digital twin federated with knowledge engineering technologies. The opportunities and limits of the approach will be evaluated on industrial use cases.
Cluster dynamic simulations of materials under irradiation
Alloys used in nuclear applications are subjected to neutron irradiation, which introduces large amounts of vacancy and interstitial defects. Over time, these defects migrate, recombine and agglomerate with minor alloying elements to form small clusters. This affects the mechanical properties of ferritic steels and weakens them. In this context, the microstuctural evolution is to be simulated using the rate equation cluster dynamic method. However, this approach becomes ineffecient when several minor alloying elements need being taken into account. The difficulty comes from the huge number of cluster variables to describe. The project aims at optimizing the code efficiency on a distributed parallel architecture by implementing parallelized vector and matrix functions from SUNDIALS library. This library is used to integrate the ordinary differential equation describing the reactions between clusters. Another aspect of the work is more theoretical and involves reformulating the non-linear root-finding problem by taking advantage of the reversibility of most chemical reactions. This property should facilitates the implementation of direct and gradients iterative sparse solvers for symmetric definite positive matrices, such as the multi-frontal Cholesky factorization and the conjugate gradient methods, respectively. One avenue of research will consists of combining direct and iterative solvers, using the former as a preconditioner of the latter.
New reference radiation field for radioprotection in the range of Cs-137 et Co-60 using an electrostatic electron accelerator
During the last years, LNHB has started and realized a research program in order to produce a reference photon radiation field for the radioprotection needs at high energies (~6 MeV) using its medical electron accelerator Saturne 43. For this purpose, a target and its appropriate flattering-attenuating filter have been designed by LNHB in order to produce the required photon field.
Nowadays there is no existing device able to produce radiation fields from an accelerator in the Cs-137 and Co-60 equivalent energy range. In order to achieve this, one needs the technology to construct and properly use absolute dosemeters for photons (cavity ionization chambers), to determine the right target-filter assembly allowing the production of the required photon field and to accurately calculate the conversion factors from air-kerma to operational quantity which is the dose-equivalent using the spectral distribution at the calibration position.
The candidate will participate in the construction of cavity ionization chambers needed for the characterization in terms of dose-equivalent of radiation field obtained from the electron accelerator and to the on-site measurements. He(She) will also be in charge with Monte-Carlo simulations in order to optimize the target-filter assembly used to produce the reference photon field from an electrostatic accelerator.
Software and hardware combined acceleration solution for operations research algorithms
The purpose of the study is to prepare the next generation of OR solvers. We will study the hardware acceleration possibility based on FPGA to run some or all of the OR algorithm. The blocks for which such a solution is not effective can be parallelized and executed on a standard computing platform. Thus, the proposed runtime correspond to a standard computing platform integrating FPGA. To access to this platform we require a set of tools. These tools should provide features such as (a) analysis and pre-compiling an input or problem or sub-problem of OR, (b) HW / SW partitioning and dedicated logic optimization and finally (c) generating an software executable and a bitstream.
The first step will be to find OR algorithms that are well suited for hardware acceleration. We then propose a HW / SW partitioning methodologies for different classes of algorithms.
The results will be implemented to lead to a compilation prototype starting from an OR instance and generating a software executable and a bitstream. Theses results will be implemented and executed on a computing platform integrating FPGA to evaluate the performance gain and the impact on the energy consumption of the proposed solution.
Simulation of PEMFC flooding phenomena
The proton exchange membrane fuel cell (PEMFC) is now considered as a relevant solution for carbon-free electrical energy production, for both transport and stationary applications. The management of the fluids inside these cells has a significant impact on their performance and their durability. Flooding phenomena due to the accumulation of liquid water are known to impact the operation of the cells, causing performance drops and also damages that can be irreversible. With the use of thinner channels in ever more compact stacks, these phenomena are becoming more and more frequent. The objective of this post-doc is to progress in the understanding of flooding in PEMFCs. The work will consist in analyzing the link between the operating conditions, the design of the channels and the materials used in the cell. It will be based on a two-phase flow modeling approach at different scales, from the local scale at the channel-rib level, up to, via an upscaling approach, the level of the complete cell. The study will also be based on numerous experimental results obtained at the CEA or in the literature.
High entropy alloys determination (predictive thermodynamics and Machine learning) and their fast elaboration by Spark Plasma Sintering
The proposed work aims to create an integrated system combining a computational thermodynamic algorithm (CALPHAD-type (calculation of phase diagrams)) with a multi-objective algorithm (genetic, Gaussian or other) together with data mining techniques in order to select and optimize compositions of High entropy alloys in a 6-element system: Fe-Ni-Co-Cr-Al-Mo.
Associated with computational methods, fast fabrication and characterization methods of samples (hardness, density, grain size) will support the selection process. Optimization and validation of the alloy’s composition will be oriented towards two industrial use cases: structural alloys (replacement of Ni-based alloys) and corrosion protection against melted salts (nuclear application)