Researcher (M/F) in Experimental crystal plasticity using HR-EBSD and HR-DIC

Job Description

Missions

Combining in-situ SEM mechanical testing with High-Resolution Digital Image Correlation (HR-DIC) and HR-EBSD techniques represents a state-of-the-art and highly effective approach for capturing local plasticity mechanisms [1-3]. This integrated methodology has rapidly developed in recent years and is increasingly becoming the standard for investigating deformation processes at the microscale [4]. The present postdoctoral study aims to develop this methodology into a fully automated platform for the acquisition of open data on microplasticity mechanisms in materials exhibiting gradients in microstructure and properties. The objective is twofold: first, provide fruitful data to calibrate physics-based crystal plasticity models and inform them with key parameters (e.g., activated slip systems, statistically stored dislocations and geometrically necessary dislocations from the combined information provided by in-plane kinematic fields and crystal lattice rotations), secondly, gain a better understanding of the mechanisms leading to strain localization which has a determinative role in influencing the suitability of a given material for an intended structural application. To conduct this study, a nickel-based superalloy (Inconel 718) will be used as a model material because of its broad industrial applicability and its remarkable metallurgical modularity, enabling the elaboration of specimens with gradients of microstructural states (from solid solution to precipitation hardened) directly influencing its strain localization.

REFERENCES:
[1] Harte A., Atkinson A., Preuss M. & Quinta da Fonseca J., (2020). A statistical study of the relationship between plastic strain and lattice misorientation on the surface of a deformed Ni-based superalloy. Acta Materialia, 195, 555-570, doi: 10.1016/j.actamat.2020.05.029.
[2] Charpagne, M. A., Stinville, J. C., Callahan, P. G., Texier, D., Chen, Z., Villechaise, P., ... & Pollock, T. M, (2020). Automated and quantitative analysis of plastic strain localization via multi-modal data recombination. Materials Characterization, 163, 110245.
[3] Charpagne, M. A., Hestroffer, J. M., Polonsky, A. T., Echlin, M. P., Texier, D., Valle, V., ... & Stinville, J. C, (2021). Slip localization in Inconel 718: A three-dimensional and statistical perspective. Acta Materialia, 215, 117037.
[4] TANIST platform: www.royce.ac.uk/equipment-and-facilities/tescan-and-newtec-in-situ-testing-tanist/
[5] Lenthe W.C., Germain L., Chini M. R., Gey N. & De Graef M., (2020). Spherical indexing of overlap EBSD patterns for orientation-related phases – Application to titanium. Acta Materialia, 188, 579-590, doi: 10.1016/j.actamat.2020.02.025.
[6] Robertson A.E., Kelly C., Buzzy M. & Kalidindi S. R., (2023). Local-global decompositions for conditional microstructure generation. Acta Materialia, 118966, doi: 10.1016/j.actamat.2023.118966.

Activity

The postdoctoral research will notably involve:
• Preparation of INCONEL 718 specimens having a gradient of precipitation along the tensile direction (1), chemically-graded specimens for controlled gradients in Nb and/or Al content (2), and pre-deformed samples (3).
• Development and selection of nanospeckle patterns non-intrusive for HR-EBSD measurements (thin-film remolding, nanoparticle deposition, surface texturation).
• Optimization of both correlation algorithms to speed up HR-DIC (which is essenstial for working on evolving markers of microstructure during in-situ testing) and diffraction signal analysis to speed up HR-EBSD (using pattern matching methods coupled with Hough transform [5]).
• Statistical analysis of discrete microplasticity events from HR-DIC/HR-EBSD maps to measure the strain partitioning with respect to lattice orientation, chemical composition, metallurgical state, and distance to grain or twin boundary.
• Extrapolation of 2D surface measurements (HR-DIC/HR-EBSD) towards 3D microstructure information using generative AI techniques [6], as required as input for simulations and to inform on microplasticity in the volume.

Your Profil

Skills

• PhD in Materials Science, Mechanical Engineering or a related field
• Knowledge of crystal defects (grain boundaries, dislocations, slip bands, precipitates, etc.)
• Experience in materials characterization techniques
• Programming skills (Python, MATLAB, C++, or similar)
• Familiarity with machine learning approaches would be a plus
• Good written and verbal communication skills in English
• Ability to work independently and as part of a multidisciplinary team

Your Work Environment

This is a fully funded postdoctoral position for 18 months (3143 € (gross) per month) supported by the PEPR DIADEM program, starting from July 2026. The postdoctoral candidate will be recruited in the framework of the AMMETIS (AI-assisted Simulations of Microstructure driven Mechanical properties from high Throughput and multiscale analysIS) project which is based on an effective collaboration between LEM3, ICA, PIMM and CEA. The postdoctoral candidate will be mainly located at ICA in Toulouse, while making several stays at LEM3 in Metz. He will be involved in the AMMETIS'team composed of experienced researchers from CNRS, UL, Arts et métiers, IMT and CEA, as well as several PhD students and post-doctoral researchers, working on high-throughput material characterization and micromechanical modelling, both assisted by AI. The postdoctoral candidate will have access to state-of-the-art research facilities and computational resources. He will be offered the opportunity to participate in in international conferences, workshops, and training events.

Constraints and risks

Nothing to add

Compensation and benefits

Compensation

Between 3041,58 and 4668,21€ depending on experience

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

The research professions