Fusion materials must withstand intense neutron irradiation, high temperatures, corrosive environments and complex mechanical loading. We are developing an integrated, multiscale modelling capability that connects material composition and manufacturing history to irradiation-induced microstructure, engineering properties and component reliability.
Our digital workflow combines nuclear data, atomistic simulation, thermodynamics, microstructure modelling, mechanics, uncertainty quantification and physics-informed AI. Initial applications include tungsten-based plasma-facing materials, low-activation vanadium alloys and advanced ceramics for fusion energy systems.
Nuclear Data, Neutronics & Irradiation Damage
We translate reactor radiation environments into physically meaningful inputs for materials simulations. The workflow retains neutron spectra, transmutation histories and primary knock-on atom distributions rather than relying only on scalar damage measures such as dpa.
Core capabilities:
- Neutronics, depletion and transmutation modelling using OpenMC
- Helium and hydrogen production calculations
- Primary knock-on atom and recoil-spectrum calculations
- NRT-dpa, arc-dpa and radiation-damage assessment
- Nuclear-data sensitivity analysis and uncertainty propagation
Atomistic Damage & Defect Evolution
We model the production and long-term evolution of irradiation-induced defects. First-principles and molecular-dynamics simulations provide defect energetics and cascade source terms for our in-house cluster-dynamics models.
Core capabilities:
- First-principles defect and solute calculations
- Interatomic-potential development and validation
- Molecular-dynamics cascade simulations using LAMMPS
- In-house cluster-dynamics and rate-theory modelling
- Simulation of defect clusters, dislocation loops and gas bubbles
Manufacturing, Microstructure & Irradiation Response
We investigate how composition, manufacturing route and initial microstructure influence phase stability and irradiation response. Our models connect manufacturing decisions, including alloy chemistry, heat treatment, grain structure and coating architecture, to microstructural evolution during service.
Core capabilities:
- Computational design of low-activation alloys and advanced ceramics
- CALPHAD thermodynamic and phase-stability modelling
- Precipitation-kinetics and phase-field simulations
- Radiation-induced segregation and precipitation modelling
- Process-structure modelling for additive manufacturing and coatings
Materials Performance & Component Reliability
We translate predicted defect and microstructure populations into mechanical, thermal and functional properties. These microstructure-informed properties are incorporated into component-scale models to assess operating limits, failure mechanisms and design margins.
Core capabilities:
- Irradiation-hardening and constitutive modelling
- Crystal-plasticity finite-element analysis
- Thermal-property degradation modelling
- Swelling, creep, fatigue and fracture assessment
- Abaqus-based component and reliability simulations
Physics-Informed AI, Uncertainty Quantification & Digital Workflow
We are developing a reproducible digital workflow that connects simulations, material states and engineering decisions across length and time scales. It preserves data provenance, model dependencies and uncertainty throughout the modelling chain. Physics-informed AI is used to accelerate mechanistic simulations, calibrate uncertain parameters and guide high-value modelling and validation activities.
Core capabilities
- Bayesian calibration and uncertainty propagation
- Sensitivity analysis and identification of dominant uncertainties
- Reduced-order models and fast simulation surrogates
- Active learning and simulation prioritisation
- Reproducible, multicode workflow orchestration
- Probabilistic operating-window and reliability assessment