How Polaron works
The Polaron platform transforms image data into materials intelligence, connecting process, structure, and performance across R&D and production. By learning directly from real microstructures, Polaron enables faster diagnosis, more reliable decision-making, and scalable design and optimisation.
Characterisation
Turn microscopy images into quantitative insight.
Polaron’s characterisation engine converts raw 2D or 3D images into objective, pixel-accurate representations of material structure. Grains, phases, pores, cracks, binders, and interfaces are identified automatically, without manual thresholding or bespoke scripts.
What was previously subjective becomes measurable, reproducible, and comparable across batches, lines, and sites.
What was previously subjective becomes measurable, reproducible, and comparable across batches, lines, and sites.
01
State-of-the-art image segmentation
02
2D to 3D AI reconstruction
03
Scalable data-driven workflows
04
GPU accelerated simulations
Design
Move materials design in silico.
Polaron learns how processing choices influence microstructure and how microstructure determines performance. Starting from real images, the platform reconstructs representative 3D microstructures and builds a generative design space of manufacturable candidates.
Thousands of structures and process combinations can be explored virtually, balancing performance trade-offs such as energy density, power capability, and durability.
The output is not an abstract ideal, but concrete, implementable structures and process parameters.
Thousands of structures and process combinations can be explored virtually, balancing performance trade-offs such as energy density, power capability, and durability.
The output is not an abstract ideal, but concrete, implementable structures and process parameters.
01
Microstructure prompting to explore design candidates in silico
02
Process models to predict microstructural changes across process space
03
Closed-loop process optimisation to identify optimal recipes
Rigorously validated, production ready.
Validation and Observability
Models are benchmarked against ground truth data where available, with clear metrics for accuracy, uncertainty, and failure modes. Outputs are traceable, inspectable, and designed to work closely with human decision-making. This focus on observability and validation is critical for deployment in high-stakes industrial environments.
Data, Security and Deployment
- Works with standard industrial imaging modalities
- Trains models rapidly on modest, structured datasets
- Supports high-throughput batch processing
- Secure by design with customer data isolated
- Deployable across research and production workflows
Putting the power of AI in the hands of engineers.
All of our models can be trained and evaluated easily through the Polaron platform. Built for materials scientists and engineers.
See the platform in action
Request your personalised demo today.
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