DeviceAlchemy.ai
AI-Driven Electronic Materials & Device Innovation
Discover better material stacks for next-generation electronics
Science-aware AI predicts optimal hetero-integrated material stacks and explains why they work.
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Discover better material stacks for next-generation electronics
Science-aware AI predicts optimal hetero-integrated material stacks and explains why they work.
Traditional stack optimization means months of literature review and lab iteration. We compress that into physically-grounded recommendations that narrow your search space and get you to a validated stack faster. Four AI agents work together as a unified AI operating system (OS), from prediction to fabrication.
Predicts new candidate materials for your target device stack.
Science-aware LLM that explains every prediction with references.
Materials property-aware agent for stack compatibility assessment.
Guides synthesis of the new material stack within conventional fab techniques.
ALCHEMY's prediction model has been applied to real memory device research, resulting in two journal publications.
Disclaimer: The research models used a separate dataset from the live tool at DeviceAlchemy.ai. But all models only use abstract text, not the full article. The live tool uses abstract text from Gold Open Access journals and other open sources with CC BY or similar permissive licenses.
MIRA is a domain-tuned LLM agent that provides physical insight into every ALCHEMY prediction and answers your deepest scientific questions in materials science, condensed matter physics, and electronic devices.
Tell ALCHEMY your device stack, pin known materials, and specify the phenomenon or device operation you care about.
In under 5 seconds, the model ranks new candidates alongside known results for your target stack.
Ask MIRA why a candidate was ranked highly and get a physics-grounded answer — ready to validate in your own process.
We make that science move faster. Create a free account and start a conversation with MIRA in minutes.