Materials informatics for polymer & composites R&D
Materials informatics is the use of data, machine learning and AI to decide what to make and test next in materials research.
ReUse Labs builds AI co-scientists for polymer, composites and recycled-plastics R&D. Its product, R+D Studio, runs evidence-first materials research on dedicated hardware behind the customer's firewall.
What's known is scattered
Three questions every materials program runs on. Today the answers live in people's memories, old notebooks, and retests nobody wanted.
Materials R&D moves faster when your team can find what's known, trust the evidence, and act with confidence—without repeating dead ends.
Three questions an AI co-scientist answers
What's been tried — and what's comparable?
Search internal experiments and public research with click-through, source-linked evidence — so you don't repeat work.
What should we test next?
Rank next-best experiments by expected payoff and spec likelihood under constraints — cost, time, materials.
Will this plan pass spec?
Forecast spec-to-pass risk early, surface failure modes, and keep an audit-ready trail tied to standards + evidence.
Always evidence first
Your results, tracing the published science "why" behind every research call.
- Capture negative results so failures become reusable knowledge, not lost cost.
- Unify team learning across people, projects, and sites—one shared source of truth.
- Cut through biased literature with source-linked evidence and clear provenance.
- Replace guesswork with decision support: ranked next-best experiments under cost + spec constraints.
Behind your firewall
IP-safe by default. Dedicated hardware inside your facilities.
Built for your lab, not for the demo.
Most AI-for-science tools stop at a bespoke demo: impressive on curated data, stalled when they meet a real lab's notebooks, spec sheets, and failed batches.
R+D Studio starts from your own experiments, failures included, and ties every recommendation to source-linked evidence and the spec you have to pass. The output is a ranked next experiment you can run this week, with an audit trail you can defend.
Who it's for
Materials startups
Every experiment is runway. See what's been tried, rank what to test next, and spot spec risk before you pay for samples.
Academic labs
Turn the literature and your group's past results into testable hypotheses, with every claim linked to its source.
The result
Shorter R&D cycles, fewer redundant experiments, & fewer late-stage certification surprises.
Want to see R+D Studio on your material?