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Francois Willot

Research Director

Center · STIM

Discipline(s)
Applied Mathematics, Condensed Matter Physics, Nanosciences, Complex Systems, Solid Mechanics
Topic(s)
Nuclear, Renewable Energy, Sustainable Development

Keywords

Awards & distinctions

  • 2025 Guest Speaker at ECSIA (14th European Congress for Stereology and Image Analysis)

Team

STIM

Biography

François Willot is a researcher specializing in multiscale modeling of heterogeneous materials and numerical simulation of microstructures. His work focuses primarily on analyzing deformation and failure mechanisms in ductile materials, particularly through the study of interactions between porosity, cracks, and crystalline microstructures. He has contributed to the development of innovative methods combining 3D imaging (tomography, electron microscopy), stochastic models, and advanced numerical approaches, such as the Fast Fourier Transform (FFT) and Physics-Informed Neural Networks (PINs). His research also addresses the characterization of composite materials, polycrystals, and porous media, incorporating statistical tools to describe spatial distributions and morphological correlations. The evolution of his work reflects a growing interest in integrating artificial intelligence and model reduction techniques to optimize the prediction of materials’ mechanical and physical properties based on their microstructures.

Publication(s)

Projects

  • 2022-2026 Data-driven Stochastic 3D MIcrostructure modeling for LEarning mechanical properties (SMILE) Lead Investigator Damage localization, leading to brittle or ductile fracture in TiAl polycrystalline alloys is a phenomenon driven by the local stress state within the microstructure. Combined with machine learning methods, established computational models of fracture, based on phase-field and FFT approaches, have the potential to explore microstructure-properties relationships and identify mechanically preferable structures. To do so, mechanical modeling must be supplemented by stochastic microstructure modeling able to capture the wide range of grains morphologies, granulometry distributions and crystal texture encountered in real materials. The Smile project will combine modeling of polycrystals with different mechanical responses, validated on 3D high-resolution images with a phase-field approach to predict the mechanical response up to failure, validated on 4D tomography images. This will allow us to devise a parsimonious method for classifying polycrystalline materials based on mechanical properties.
  • 2024-2026 Accelerated Design of Architectured Materials. ANR project part of the PEPR DIADEM Scientific Director

Teaching

Introduction to Nanomaterials

Lecturer

- General Introduction - Synthesis, Development - Characterization - Molecular-Scale Modeling - Morphological Modeling and the Nano-Macro Transition - Color Applications - Materials Science Applications - Applications in Pollution Control, Nanoporous Materials, and Catalysis - Applications in Energy - Applications in Nanomedicine - Future Outlook, Industrial and Societal Challenges, Risk Analysis, Toxicity.

ATHENS - MP08 - Physics and Mechanics of Random Media

Course Director

Based on a review of advanced experimental techniques for describing microstructure, and on typical results involving fluctuations in the phenomena of plasticity, damage, fracture, and flow in porous media, the basic tools of applied probability and random processes are reviewed. Probabilistic tools for describing random media and models, as well as their simulation, are introduced. The physics and mechanics of random media are first presented from the perspective of approximate solutions to partial differential equations with random coefficients. For example, problems in linear electrostatics in random media are studied using a perturbation expansion of random electric and displacement fields, while the limits of the effective permittivity and elastic moduli are derived from variational principles. This homogenization approach, which can be applied to other physical properties such as the composition of permeability or thermal conductivity, is illustrated by third-order bounds. The use of numerical techniques (such as the finite element method) to estimate the homogenized properties of random media based on Monte Carlo simulations is introduced. The limits and numerical techniques are then extended to nonlinear behaviors, such as the plasticity of polycrystals. Given the importance of reliability issues in a wide range of engineering applications, several statistical failure models (brittle, ductile, fatigue) are developed using a probabilistic approach. Course Structure: One week. Lectures (80%) and hands-on computer training (20%) More information at: http://cmm.ensmp.fr/Enseignement/es-physrandmedia.html

Parallélisme et calculs distribués

Guest Lecturer

Option Ingénierie Digitale des Systèmes Complexes (Mines ParisTech)

Mastère 2 Énergie (PSL)

Mastère Spécialisé "Design des Matériaux et des Structures" (Mines ParisTech)

Mécanique des Matériaux Biosourcés

Formation doctorale "Probabilité et Mécanique", École doctorale Université Paris-Est

Random structures and homohenization

PhD supervision

  • 2025 The impact of internal swelling on the mechanical behavior of concrete: multi-scale analysis and kinetic effects GILBERTAS Florian
  • 2025 Generative artificial intelligence models for metallic alloy microstructures COURTOIS Martin
  • 2023 Characterization of energetic material damage at the microstructural scale ROBIN Camille
  • 2023 Statistical analysis of damage under impact in ductile materials THOUÉNON Corentin
  • 2022 Estimation of mechanical properties of polycrystals using physics-informed machine learning MONTEIRO FERNANDES Lucas
  • 2018 Machine learning reduced models for studying defect harmfulness LAUNAY Hugo
  • 2018 Phase-field prediction of microcracking using FFT method for compressed energetic materials. RABETTE François
  • 2017 Experimental and numerical study of the sensitivity of energetic compositions: influence of the microstructure and role of damage KAESHAMMER Elodie
  • 2016 Numerical study of the harmfulness of defects in welds LACOURT Laurent