Rapid discovery of high-strength, high-temperature materials using high-throughput screening.

Next-generation high-temperature materials discovered through rapid, data-driven workflows.

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Alloy combinations
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Five-component systems
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Partner Institutions
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Target thermal resistance
Refractory elements — high melting point, thermal stability Supplementary elements — density & oxidation resistance

RADISH explores 15 elements across roughly 40 billion possible compositions (1 at.% resolution).

Tap or hover an element to learn its role.

What we’ve been up to…

The RADISH Project

The RADISH workflow brings together computation, rapid experimentation, and machine learning to accelerate the discovery of high-temperature alloys. The process is iterative, allowing each cycle to refine the search and focus on the most promising compositions.

STEP 01

High-Throughput CALPHAD

The process begins with large-scale CALPHAD simulations that screen vast combinations of elements. This step identifies alloy compositions with desirable phase stability, melting temperatures, and density. It narrows billions of possible materials into a small set of high-potential candidates.

STEP 02

Combinatorial Synthesis

Selected compositions are synthesized as material libraries using physical vapor deposition. Each library contains gradual variations in composition, enabling hundreds of alloy variants to be produced in a single experiment. This dramatically increases experimental throughput while maintaining precise control over composition.

STEP 03

High-Throughput Characterization

Each material library is rapidly analyzed using XRF / EDS / ERDA to map chemistry, XRD to determine crystal structure and phases, and nanoindentation and micropillar tests. The result is a comprehensive dataset linking composition, structure, and mechanical performance across an entire library.

STEP 04

Machine Learning

Experimental data feed into machine-learning models trained to recognize structure–property relationships. They identify the most influential chemical and structural features, predict properties of unexplored compositions, and guide the next iteration of CALPHAD screening and synthesis — a feedback loop that accelerates discovery far beyond traditional trial-and-error methods.

STEP 05

Upscaling & Testing

The most promising alloys are produced in bulk using spark plasma sintering (SPS). They then undergo rigorous evaluation: high-temperature XRD, dilatometry, and calorimetry to confirm phase stability; compression and creep testing at elevated temperatures; and oxidation testing to assess environmental resistance. Only alloys that surpass state-of-the-art high-temperature materials progress to the final stage.

FINAL GOAL

Next-Generation Alloys

A new class of high-strength, oxidation-resistant RCCAs capable of operating beyond the limits of today's structural materials — unlocking new possibilities for aerospace, energy, and extreme-environment technologies.

About RADISH

RADISH combines strong scientific collaborations across Poland and abroad to build:

Comprehensive materials database
Predictive AI tools
Rapid discovery methodology

This iterative, high-speed workflow accelerates every stage of materials development.

Development cycle Years Months