Lila Sciences' AI-run lab screens 2,942 catalysts and finds iridium- and ruthenium-free palladium oxides for green hydrogen
On 25 Sept 2026 Lila Sciences reported that its AI-directed autonomous lab proposed, synthesized and screened 2,942 oxide catalysts (53 material systems, 26 elements) for the acidic oxygen evolution reaction used in PEM water electrolysis. It identified six palladium-based families on or near the activity–stability Pareto front. The best performed comparably to ruthenium over 1,000+ hours of stability tests. The results are in a preprint (arXiv 2609.30133) and have not been peer-reviewed.
Key facts
- 2,942 catalysts across 53 material systems and 26 elements; 6 Pd-based families on or near the Pareto front (e.g. InMnPdOx, NiTaPdOx)
- Lead composition performed comparably to ruthenium in activity after 1,000+ hours of stability testing (company claim)
- Palladium had been widely considered a dead end for acidic OER
- Bayesian models combined with language models chose experiments; humans handled safety review and some manual sample transfers; Lila claims ~17x faster screening and >90% less human time per sample
- Preprint: Jenewein et al., 21 authors, all Lila Sciences, submitted 24 Sept 2026
- Company context: Flagship Pioneering spin-out; $550M raised by Oct 2025 (incl. NVentures), valuation >$1.3B; Bloomberg (3 June 2026) reported talks to raise ~$2B at ~$8.5B pre-money
Science result
- Field
- materials / electrocatalysis
- Problem
- Iridium/ruthenium-free anode catalysts for acidic oxygen evolution (PEM water electrolysis)
- Result
- AI-guided high-throughput campaign found six Pd-oxide catalyst families; the best is comparable to Ru with 1,000+ h stability.
- AI system
- Lila Sciences autonomous lab (Bayesian optimisation + LLMs)
- Human role
- AI-directed experiment selection with humans for safety review and partial sample handling
- Verification
- Preprint only (arXiv 2609.30133); not peer-reviewed
- Status
- pending
What happened
Lila's autonomous materials lab ran closed-loop campaigns in which AI models proposed oxide compositions. Robotic sputtering and electrochemical stations made and tested them, and the results fed back into the models. The AI pushed into palladium compositions that experts had largely written off and found stable, active catalysts without iridium or ruthenium.
Why it matters
It is one of the first concrete, data-backed discovery claims from the heavily funded "scientific superintelligence" startups. It addresses a real bottleneck for gigawatt-scale green hydrogen, where iridium supply is scarce. It is still a company preprint and needs peer review and industrial-scale testing.
Changelog
- 2026-09-29: created
Related events
- Periodic Labs launches with a $300M seed round to build AI scientists with autonomous labs ★★★
- GNoME predicts 2.2 million new crystals, 380,000 stable, but novelty and usefulness are disputed ★★★★
Sources (6)
- officialLila: How an AI-run lab cracked open green hydrogen's catalyst problem
- paperarXiv 2609.30133: AI-guided high-throughput discovery of Ir- and Ru-free palladium-oxide catalysts
- pressUnite.AI: Lila Sciences' AI lab uncovers palladium catalysts for green hydrogen
- pressBloomberg: Lila Sciences said in talks for funds at $8.5B valuation
- officialLila: $350M Series A announcement
- pressMIT Technology Review: AI materials-discovery startups (Dec 2025)
id: 2026-09-25-lila-ai-lab-palladium-oer-catalysts · updated 2026-09-29 · open in the interactive timeline