Where failed assumptions become working systems.
I work at the boundary between materials engineering, computational physics, and experimental discovery.
Most of the work here starts with a question that does not yet have a clean answer.
Sometimes it begins with a failed experiment.
Sometimes with a model that behaves almost correctly.
Sometimes with a material system that does something unexpected.
That uncertainty is usually where the useful work begins.
My work focuses on understanding how materials behave, fail, evolve, and respond under real conditions.
This includes:
- diffusion and transport phenomena
- microstructure evolution
- failure analysis and degradation mechanisms
- experimental characterization
- data-driven materials workflows
- physics-first modelling
- computational tools for scientific discovery
A large part of this work lives somewhere between experiment and simulation.
Build something.
Test it.
Break the assumption.
Learn from what survives.
I am particularly interested in turning physical behaviour into working systems.
Sometimes that means building models.
Sometimes it means rebuilding the experiment.
Sometimes the answer is hidden in the failure itself.
Not everything here is finished.
Some ideas are early prototypes.
Some are working theories.
Some are simply useful dead ends.
That is part of the process.
At the moment, much of the work here revolves around transport physics, diffusion-driven systems, and materials intelligence workflows.
The long-term direction is broader:
connecting experiments, physics, and machine learning into systems that help us understand matter a little better.
Still mostly nominal.