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DOE ARPA-E Funding to Pair AI and Machine Learning with Autonomous Self-Driving Laboratories for Accelerated Catalyst and Chemicals Development is sponsored by U.S. Department of Energy, Advanced Research Projects Agency-Energy (ARPA-E). ARPA-E is funding projects that couple advances in AI and machine learning with high-throughput experimentation and self-driving autonomous laboratories to dramatically accelerate industrial catalyst development for fuels and chemicals.
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**San Diego, CA** — The U.S. Department of Energy’s (DOE) Advanced Research Projects Agency-Energy (ARPA-E) today announced $34 million for 12 projects to pair artificial intelligence (AI) with self-driving laboratories to dramatically accelerate industrial catalyst development for fuels and chemicals production.
The agency’s Catalytic Application Testing for Accelerated Learning Chemistries via High-throughput Experimentation and Modeling Efficiently (CATALCHEM-E) program advances the Trump Administration's goal to harness AI and advanced computing to strengthen U.S. energy and industrial leadership. CATALCHEM-E aims to compress catalyst development timelines from roughly a decade to about one year.
Projects will seek to integrate machine learning, AI-guided design, and high-throughput experimentation platforms into continuous, automated discovery workflows. The program targets 10x faster progress in designing and validating industrially relevant catalysts such as those that convert oil and gas feedstocks into widely used fuels and commodity chemicals.
“America is upgrading its industrial base to reclaim our global leadership, and commodities like industrial catalysts play a foundational role in this effort,” said **ARPA-E Director Conner Prochaska**. “CATALCHEM-E’s goal is to harness the power of AI paired with self-driving labs to slash the development timeline for these critical building blocks from a decade to a year.
This will empower American refineries, factories, and industrial plants to strengthen manufacturing, energy independence, and national security. ” Identifying viable catalysts traditionally involves computational screening and extensive lab validation, a process complicated by the vast materials design space encompassing nanoscale metal compounds/alloys, bulk porous materials, and specific operating conditions.
CATALCHEM-E will instead build systems that rapidly iterate between AI-guided prediction, synthesis, and testing, evaluating in weeks what previously required years.
The program is part of ARPA-E’s expanding portfolio of AI-enabled initiatives and supports DOE’s broader efforts to embed advanced computing and automation across the nation’s energy innovation ecosystem, accelerating the path from laboratory breakthroughs to commercial deployment.
Selected projects include: * **University of Wisconsin-Madison (Madison, WI)**will develop catalysts to convert ethanol into alcohol for fuels and specialty chemicals. The project will combine AI models with automated lab tools and industrial-scale catalyst testing.
The team will also explore integrating the technology into standard laboratory information management systems, to make the design workflow widely accessible to a range of commercial entities. _(Award amount: $2. 84 million)_ * **Ames National Laboratory (Ames, IA)** will deliver precious-metal-free catalysts for hydrocarbon processing reactions to reduce energy use and boost domestic manufacturing.
The project uses advanced AI models coupled with robotic synthesis platforms and multiscale validation from atomistic simulations to pilot-scale testing. _(Award amount: $2. 52 million)_ * **North Carolina State University (Raleigh, NC)**aims to discover catalysts for converting biomass and other waste liquids into hydrogen-rich syngas, a critical industrial feedstock.
The project integrates innovations in AI for self-driving labs, automated synthesis, proxy screening, and transport modeling to ensure new catalysts can be industrially scaled. _(Award amount: $2. 99 million)_ You can read the full list of selected projects here and learn more about the CATALCHEM-E program here.
_Selection for award negotiations is not a commitment by DOE to issue an award or provide funding. Before funding is issued, DOE and the applicants will undergo a negotiation process, and DOE may cancel negotiations and rescind the selection for any reason during that time. _
According to the current listing, eligibility includes: Open to U. S. universities, national labs, small and large businesses, and research institutions; cost share required (at least 20% Phase 1, at least 50% Phase 2). Confirm the full requirements in the official notice before applying.
The current listing shows phase 1 awards up to approximately $2 million (with at least 20% cost share); Phase 2 down-select awards up to approximately $8 million (with at least 50% cost share). Letters of Intent due April 21, 2026; full applications in the May-July 2026 window. Verify award ceilings, matching requirements, and allowable costs in the official notice.
DOE ARPA-E Funding to Pair AI and Machine Learning with Autonomous Self-Driving Laboratories for Accelerated Catalyst and Chemicals Development is funded by U.S. Department of Energy, Advanced Research Projects Agency-Energy (ARPA-E). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
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