Thermal Conductivity with IMPACTTM
Using Integrated Materials Processing and Computational Techniques (IMPACT™) - our advanced data and modelling platform, we have mapped ten years of thermal conductivity testing to build a predictive tool that estimates thermal conductivity from material density. Where historic measurements include hot and cold face data (often four measurements at different face temperatures) and recorded density, IMPACT™ turns those results into actionable insights for materials selection, optimisation, and formulation.
What we offer
- Predictive thermal conductivity from density
A data-driven map allows you to estimate thermal conductivity for a material given its density, even when the exact formulation is unknown, such as when we know the material type only, e.g. vermiculite - Uncertainty you can plan around
Predictions for lower-density samples carry lower uncertainty (~1-5%); for higher-density materials uncertainty is typically up to ~10%, reflecting the relative volume of historic data available - BS 1902 panel method underpinning
The model is trained on measurements generated by the BS 1902 panel method, providing a consistent methodological baseline - Faster development routes
We can use the predictions to reduce the number of experimental iterations and focus lab effort where it adds the most value.
Typical use cases
- New formulation development - rapidly screen density targets to meet thermal performance requirements before committing to full test campaigns
- Customer self-development support - if you are developing your own formulations, our predictions help you prioritize candidates and compress development timelines
- Performance benchmarking - compare anticipated conductivity across material types and densities using a common reference approach
How it works
Data foundation
- IMPACT™ machine learning model trained on ten years of thermal conductivity measurements with hot and cold faces (commonly four face-temperature measurements)
- Associated material density
- Material type
Modelling & mapping (IMPACT™)
- IMPACT™ analyses, cleans, and harmonizes results from BS 1902 panel method tests
- The platform generates a density / thermal conductivity map including thermal conductivity temperature dependence with confidence intervals that reflect historical data coverage
Prediction & decision support
- Provide a target density (or a density range) and material type to obtain predicted thermal conductivity and uncertainty bounds
- Use outputs to guide density targets, batch adjustments, and test plans
Want even greater accuracy?
If microstructural information (e.g., porosity, pore size distribution, grain size, phase content) is supplied, IMPACT™ can further tighten uncertainty and improve accuracy of prediction for specific materials.
Materials & components
- Insulation and refractory materials
- Porous ceramics and composites used in high-temperature or energy-efficiency applications
- Development-grade and production materials where density is controlled as part of process optimization
Deliverables
- Density / thermal conductivity map for the relevant material class and temperature range
- Predicted values with confidence intervals at your target densities
- Concise technical note summarizing assumptions, uncertainty, and recommended validation tests
- Optional: Design-of-experiments plan to close knowledge gaps and de‑risk scale-up
Why Lucideon
- Depth of data - a unique, curated 10‑year dataset of thermal conductivity testing provides a strong empirical basis for prediction
- IMPACT™ platform - purpose‑built for materials informatics, enabling rapid model updates as new data becomes available
- Practical application - we combine modelling with hands‑on test capability and materials science expertise, so you get answers you can use, not just numbers
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