Integrated Computational Materials Engineering​

Goal and Vision

The Integrated Computational Materials Engineering ICME research programme is aimed at integrating all available simulation tools into multiscale modelling strategies, capable of simulating the processing and behaviour of engineering materials. In this way, new materials can be designed, tested and optimised before manufacture in the laboratory. The programme’s focus is on materials engineering, i.e. understanding how material microstructures develop during processing virtual processing, the relationship between microstructure and behaviour virtual testing, and how to optimise materials for a given application virtual design. Moreover, experiments are also an integral part of the research programme for model calibration and validation at different length and time scales. The expertise of the 

programme’s researchers covers a wide range of simulation techniques at different scales electronic, atomistic, mesoscopic and continuum and is supported by high-performance computer clusters with GPUs.

Main research lines

  • Virtual material discovery for functional applications using artificial intelligence, DFT, cluster expansion and atomistic approaches combined with AI.
  • Virtual processing: Integration of modelling tools (atomistic, computational thermodynamics and kinetics, phase-field and cellular automata) as well as machine learning strategies to analyse microstructure formation and evolution during processing.
  • Virtual testing of metallic alloys: Development of microstructural-based constitutive models to predict the mechanical behaviour of single crystals. Simulation of the mechanical response of polycrystalline metals by means of FFT and FEM-based homogenisation.
  • Virtual testing of composites: Implementation of the constitute models in finite element codes to simulate the mechanical behaviour of structural components.
  • Smart manufacturing: Multiphysics models of autoclave and out-of-autoclave curing of composite materials accounting for porosity evolution during the process. Simulation-based smart manufacturing processes. Sensoring and process control.
  • These approaches are applied to several materials, in particular:
    • Metallic alloys for engineering and biological applications.
    • Multifunctional composite materials and structures.
    • Materials for catalysis.
  • First-principles calculations.
  • Molecular mechanics and molecular dynamics.
  • Dislocation dynamics.
  • Object and lattice Kinetic Monte Carlo.
  • Computational thermodynamics and kinetics.
  • Phase-field modelling of Multiphysics problems.
  • Finite Element solvers for Multiphysics problems.
  • Fast Fourier based solvers for Multiphysics problems.
  • High-velocity impact mechanics.
  • Coupled problems in thermos-chemo-mechanics.
  • Bottom-up approaches scale bridging.
  • Development of modular multi-scale tools.
  • High-throughput screen integration.
  • Concurrent models.
  • Mean-field homogenisation.
  • Computational homogenisation including FEM and Fast Fourier Transform – FFT-based solvers.
  • Surrogate models of micromechanical models based on AI.
  • Multiscale modelling – from atoms to macroscopic processes – of microstructure formation and evolution during solidification (e.g. casting, welding, additive manufacturing) and solid-state thermal processing of metallic alloys.
  • Strategies based on convolutional neural networks, graph neural networks, transformer encoders, generative adversarial networks, variational auto-encoders, etc. to establish processing-microstructure-properties of materials.
  • Advanced model calibration methods.
  • Design and discovery of new materials through automated laboratories, integrated digital workflows and artificial intelligence algorithms.
  • Material informatics for large material dataset analysis.
  • Modelling and simulation of H2 embrittlement in metallic tanks and pipes.
  • Study of H2 diffusion mechanisms in metals.
  • Discovery of new catalysts for H2 production and fuel cells.
  • Discovery of new catalysts for CO2 reduction reaction.
  • Modelling and simulation of multiscale transport phenomena application to advanced materials for batteries.
  • Virtual design and testing of mechanical metamaterials and architectured metamaterials.
  • Simulation of the additive manufacturing process in metals including macroscopic simulation of the thermomechanical process by multiphysics finite element models, microstructure evolution through phase field and prediction of mechanical response using polycrystalline homogenisation.
  • Modelling and simulation of elastic waves and sound propagation in complex additive-manufactured media.
  • Exploring new physical phenomena in the wave-based and elastostatic context.
  • Discovery of porous materials for energy applications. CO2 capture and methane storage.
  • Design of ionic liquids.
  • Materials discovery: structures with high H2 working capacity and H2 adsorption-desorption performance.
  • Design of Metal-Organic Frameworks (MOFs) for separation of gases for anaesthesia Xe/Kr.

RESEARCH GROUPS

Acoustic and Mechanical Metamaterials

Modelling and Simulation of Materials Processing

Bio / Chemo / Mechanics of Materials

Multiscale Materials Modelling

Computational Solid Mechanics

RobotMat: Accelerated Materials Discovery