Instrumental development on the Jeol NeoARM TEM for rapid and low-dose mapping of EELS and strain fields

The primary objective of our Post-Doctoral Researcher position is to focus on instrumental development for the NeoARM 200F. Collaborating closely with a research software engineer already familiar with TEM automation, the team will be tasked with the automation of alignment, interface, and data stream processing for the filter and various detectors to enable cutting-edge and valuable applications. The first part of the project will focus on the rapid, precise, low-dose mapping of material strain at the nanometer scale. To achieve this, we are utilizing Nanomegas ASTAR along with other universal scan generators to acquire scanning precession electron diffraction (SPED) data. CEA has a well-established expertise in strain mapping in TEM [e.g., D. Cooper et al., Micron 80 (2016) 145]. Currently, there is a strong desire to advance the boundaries of this technique to generate real-time, high-quality results. Following the complete integration of the NeoARM for strain analysis, we will assess the advantages provided by components such as the TimePix3 detector and energy filtering for diffraction patterns. Simultaneously, the techniques developed for the SPED datasets will be extended other applications such as orientation/phase or electric field mapping. The second part of the project will focus on the TimePix3 detector for electron energy-loss spectroscopy (EELS). In frame-based acquisition mode, the performance of STEM-EELS using the TimePix3 detector will be assessed and highlighted (e.g., simultaneous EELS/EDX tomography). New strategies to enhance the EELS signal-to-noise ratio for direct electron cameras will also be explored. The exploitation of the TimePix3 in event-based mode, including EELS/EDX co-incidence and low-dose, high-speed imaging will also enter into the project as appropriate.

Crystalline materials for the selective extraction of monovalent metal cations: understanding the link between the crystalline structure and the selectivity

The selective extraction of monovalent metal cations from aqueous solutions have complex compositions is a key step in many energy-related fields. In this work, specific adsorbents for Cs, to decontaminate effluents produced by the nuclear industry, and for Li, to extract this strategic metal for the development of batteries, will be studied. Due to their modularity in terms of porosity and structure, crystalline oxides (as zeolites) are promising for the selective extraction of such cations. With a view to understand the role of their microstructure on their sorption/desorption performances and mechanisms, identify the selective sorption sites within these crystal structures is crucial.
For that purpose, the objective of this research work is, on the one hand, to synthesize crystal structures allowing the selective sorption of Cs or Li. Then, by using fine characterization techniques at the atomic scale as well as structures reconstruction effort, we will identify the location of selective sorption sites within these materials and, in this way, better understand their sorption mechanisms and properties.
For this post-doctoral position, we are looking for a PhD in material science with strong skills in synthesis and characterization of crystalline materials by X-ray diffraction. Experience in the study of crystalline oxides, such as zeolites, would be an advantage.

Development of innovative metal contacts for 2D-material field-effect-transistors

Further scaling of Si-based devices below 10nm gate length is becoming challenging due to the control of thin channel thickness. For gate length smaller than 10nm, sub-5nm thick Si channel is required. However, the process-induced Si consumption and the reduction of carrier mobility in ultrathin Si layer can limit the channel thickness scaling. Today, the main contenders that allow the extension of the roadmap to ultra-scaled devices are 2D materials, particularly the semiconducting transition metal dichalcogenides (TMD). Due to their unique atomically layered structure, they offer improved immunity to short-channel-effects in comparison to usual Si-based field-effect-transistors (FETs). This makes them very attractive for the application of more-Moore electronics.
However, the scalability of MOSFET device and the introduction of new material make source and drain contact a major issue. If many efforts have been made, in the past years, to reduce Fermi level pinning and Schottky barrier height, for many, these approaches are not industrially scalable. The main objective of this work is then to propose an in-depth understanding of electrical contact characteristics (based on different material) to identify the lowest contact resistance. The processes involved, offering an optimal contact resistance, must be compatible with wafer-scale processing for an integration in our 200/300mm advanced CMOS platform. The post-doc will in-depth study mechanisms enabling the formation of small contact resistances (between MoS2 and metal). It will have to identify the most promising contact material and to develop the associated deposition processes (ALD/PVD). Finally, electrical characterization of contact will be performed to qualify both material and interfaces enabling optimal operation of future 2D FETs

Calculation of the thermal conductivity of UO2 fuel and the influence of irradiation defects

Atomistic simulations of the behaviour of nuclear fuel under irradiation can give access to its thermal properties and their evolution with temperature and irradiation. Knowledge of the thermal conductivity of 100% dense oxide can now be obtained by molecular dynamics and the interatomic force constants[1] at the single crystal scale, but the effect of defects induced by irradiation (irradiation loop, cluster of gaps) or even grain boundaries (ceramic before irradiation) remain difficult to evaluate in a coupled way.
The ambition is now to include defects in the supercells and to calculate their effect on the force constants. Depending on the size of the defects considered, we will use either the DFT or an empirical or numerical potential to perform the molecular dynamics. AlmaBTE allows the calculation of phonon scattering by point defects [2] and the calculation of phonon scattering by dislocations and their transmission at an interface have also recently been implemented. Thus, the chaining atomistic calculations/AlmaBTE will make it possible to determine the effect of the polycrystalline microstructure and irradiation defects on the thermal conductivity. At the end of this post-doc, the properties obtained will be used in the existing simulation tools in order to estimate the conductivity of a volume element (additional effect of the microstructure, in particular of the porous network, FFT method), data which will finally be integrated into the simulation of the behavior of the fuel element under irradiation.
The work will be carried out at the Nuclear Fuel Department of the CEA, in a scientific environment characterised by a high level of expertise in materials modelling, in close collaboration with other CEA teams in Grenoble and in the Paris region who are experts in atomistic calculations. The results will be promoted through scientific publications and participation in international congresses.
[1] Bottin, F., Bieder, J., Bouchet, J. A-TDE

Hydrolysis energy distribtution in model glasses using molecular simulation and Machine Learning

The objective of the project is to develop a tool based on molecular simulations combined with Machine Learning to estimate rapidly the distributions of hydrolysis and reformation energies of the chemical bonds on the surface of alumino silicate glasses(SiO2+Al2O3+CaO+Na2O).
The first step will consist in validating the classical force fields used to prepare the hydrated SiO2-Al2O3-Na2O-CaO systems by comparison with ab initio calculations. In particular, metadynamics will be used to compare classical and ab initio elementary hydrolysis mechanisms.
The next step will consist in performing « Potential Mean Force » calculations using the classical force fields to estimate distributions of hydrolysis and reformation energies on large statistics in few glass compositions. Then by using Machine Learning and atomic structural descriptors, we will try to correlate local structural characteristics of the chemical bonds to the hydrolysis and reformation energies. Methods such as Kernel Ridge Regression, Random Forest or Dense Neural Network will be compared.
At the end, a generic tool will be available to rapidly estimate distributions of hydrolysis and reformation energies for a given glass composition.

Automatic machine learning identification of nanoscale features in transmission electron microscopy images

Imaging nanoscale features using transmission electron microscopy (TEM) is key to predicting and assessing the mechanical behaviour of structural materials in nuclear reactors or in the fields of nanotechnology. These features, visible by phase contrast (nanobubbles) or diffraction contrast (dislocation loops or coherent precipitates), are prime candidates for automation. Analysing these micrographs manually is often tedious, time-consuming, non-universal and somehow subjective.

In this project, the objective is to develop a Python-based framework for data treatment of transmission electron microscopy (TEM) images.
Machine Learning approaches will be implemented in order to tackle the following tasks:
- Data collection: The success of any machine learning approach is linked to the database quality. In this project, a huge database is available. Four microscopists are involved in the project and will continuously enrich the database with images containing easily recognizable features.
- Denoising and finding the defect contour both through existing open-access software and in-house developed descriptors. Representative ROI (region-of-Interest) will be generated on images.
- Design of the Convolutional Neural Network (CNN) Architecture and model training: A collective feature map will be generated for the entire images in order to identify some representatives ROI. Each ROI is then overlaid to the original feature map and is passed to the CNN for individual region classifications. Secondly, recent advances in image segmentation will be placed in the core engine of the workflow.
- Model performance metrics: The aim is to reach a compromise between the training time and the detector performance.
The process will be applied to nanometer-sized features formed under irradiation in nuclear oriented materials (Co-free high entropy alloys (HEA), UO2) and precipitates in materials with a technological interest (coherent Cr precipitates in Cu).

Strain driven Group IV photonic devices: applications to light emission and detection

Straining the crystal lattice of a semiconductor is a very powerful tool enabling controlling many properties such as its emission wavelength, its mobility…Modulating and controlling the strain in a reversible fashion and in the multi% range is a forefront challenge. Strain amplification is a rather recent technique allowing accumulating very significant amounts of strain in a micronic constriction, such as a microbridge (up to 4.9% for Ge [1]), which deeply drives the electronic properties of the starting semiconductor. Nevertheless, the architectures of GeSn microlasers under strong deformation and recently demonstrated in the IRIG institute [2] cannot afford modulating on demand the applied strain and thus the emission wavelength within the very same device, the latter being frozen “by design”. The target of this 18 months post doc is to fabricate photonic devices of the MOEMS family (Micro-opto-electromechanical systems) combining the local strain amplification in the semiconductor and actuation features via an external stimulus, with the objectives to go towards: 1-a wide band wavelength tunable laser microsource and 2-new types of photodetectors, both in a Group IV technology (Si, Ge and Ge1-xSnx). The candidate will conduct several tasks at the crossroads between fabrication and optoelectronic characterization:
a-simulation of the mechanical operation of the expected devices using FEM softwares, and calculation of the electronic states of the strained semiconductor
b-fabrication of devices at the Plateforme Technologique Amont (lithography, dry etching, metallization, bonding), based on results of a
c-optical and material characterization of the fabricated devices (PL, photocurrent, microRaman, SEM…) at IRIG-PHELIQS and LETI.
A PhD in the field of semiconductors physics or photonics, as well as skills in microfabrication are required.

[1] A. Gassenq et al, Appl. Phys. Lett.108, 241902 (2016)
[2] J. Chrétien et al, ACS Photonics2019, 6, 10, 2462–2469

Integration of a first principles electronic stopping power in molecular dynamics simulations of collision cascades in semiconductors

In a radiative environment, the effects of atomic displacements can lead to the degradation of the performance of electronic and optoelectronic components. In the semiconductors constituting these components, they create defects at the atomic scale, which modify the number of free carriers and therefore alter the performance of the component.
In order to better understand the physical phenomena at the origin of these degradations, the displacement damage are well reproduced by simulation using classical molecular dynamics method. Nevertheless, a finer understanding of the influence of the electronic structure of the material on the number of defects created during the displacement cascade is necessary to have accurate simulations. For this, a model called electron-phonon EPH has been developed. The objective of this post-doctorate will be to feed this model with ab initio calculations and then to configure it in order to perform molecular dynamics simulations for several semiconductors used in current microelectronic technologies. The results obtained will be allow to better understand and improve the EPH model if necessary.

Lean-Rare Earth Magnetic materials

The energy transition will lead to a very strong growth in the demand for rare earths (RE) over the next decade, especially for the elements (Nd, Pr) and (Dy, Tb). These RE, classified as critical materials, are used almost exclusively to produce NdFeB permanent magnets, and constitute 30% of their mass.
Several recent international studies, aiming to identify new alloys with low RE content and comparable performances to the dense magnetic phase Nd2Fe14B, put hard magnetic compounds of RE-Fe12 type as advantageous substitution solutions, allowing to reduce more that 35% of the amount of RE, while keeping the intrinsic magnetic properties close to those of the Nd2Fe14B composition.
The industrial developments of the RE-Fe12 alloys cannot yet be considered due to the important technological and scientific challenge that remain to be lifted in order to be able to produce dense magnets with resistance to demagnetization sufficient for current applications (coercivity Hc > 800 kA/m).
The aim of the post-doctoral work is to develop Nd-Fe12 based alloys with optimized intrinsic magnetic properties and to master the sintering of the powders in order to obtain dense magnets with coercivity beyond 800 kA/m, to fulfil the requirements of the applications in electric mobility. Two technological and scientific challenges are identified:
- understanding of the role of secondary phases on the coercivity. This will open the way to the implementation of techniques called "grain boundary engineering", well known for the NdFeB magnets to have remarkably improved the resistance to demagnetization.
- mastering the sintering step of these powders at low temperature (< 600°C) in order to avoid the decomposotion of the magnetic phase by grain boundary engineering

Simulation of a porous medium subjected to high speed impacts

The control of the dynamic response of complex materials (foam, ceramic, metal, composite) subjected to intense solicitations (energy deposition, hypervelocity impact) is a major issue for many applications developed and carried out French Atomic Energy Commission (CEA). In this context, CEA CESTA is developing mathematical models to depict the behavior of materials subjected to hypervelocity impacts. Thus, in the context of the ANR ASTRID SNIP (Numerical Simulation of Impacts in Porous Media) in collaboration with the IUSTI (Aix-Marseille Université), studies on the theme of modeling porous materials are conducted. They aim to develop innovative models that are more robust and overcome the theoretical deficits of existing methods (thermodynamic consistency, preservation of the entropy principle). In the context of this post-doc, the candidate will first do a literature review to understand the methods and models developed within IUSTI and CEA CESTA to understand their differences. Secondly, he will study the compatibility between the model developed at IUSTI and the numerical resolution methods used in the hydrodynamics computing code of the CEA CESTA. He will propose adaptations and improvements of this model to take into account all the physical phenomena that we want to capture (plasticity, shear stresses, presence of fluid inclusions, damage) and make its integration into the computation code possible. After a development phase, the validation of all this work will be carried out via comparisons with other existing models, as well as the confrontation with experimental results of impacts from the literature and from CEA database.