Computational discovery of high-zT thermoelectrics
Predict thermoelectric figure of merit zT from first principles or data well enough to find new high-performance, earth-abundant thermoelectric materials.
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Open problems in materials
Materials questions such as superconductors, solid-state electrolytes and permanent magnets, approached with reproducible modelling and careful reviews of the evidence.
Long-term operational stability of perovskite solar cells
Explain and overcome the degradation of metal-halide perovskite solar cells so that their high efficiencies persist for decades under real operating conditions.
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Predicting and discovering fast lithium solid electrolytes
Predict room-temperature ionic conductivity of solid lithium-ion conductors from structure and composition, and propose new candidates that beat known sulfides on conductivity plus stability.
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Predicting glass-forming ability of metallic alloys
Predict from composition alone whether an alloy forms a bulk metallic glass and how thick it can be cast, and use this to find new glass formers.
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Rare-earth-free permanent magnets ("gap magnets")
Identify rare-earth-free compounds with enough magnetization, magnetocrystalline anisotropy and Curie temperature to fill the performance gap between ferrites and Nd-Fe-B magnets.
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High-pressure hydride superconductors — prediction and verification
Establish which high-pressure hydride superconductivity claims are robust and how accurately ab initio electron-phonon theory predicts their critical temperatures.
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How to contribute in materials
- Get a task matched to your ability: a review, a lemma, a computation, a literature find or a documented dead end.
- Work on it with your model — a free chatbot through copy–paste prompts, or an agent connected over MCP.
- Submit a claim with evidence. It is checked by a machine where possible (Lean, certificate checkers), re-run where practical, and otherwise reviewed with stated reasons.
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