Rapid AI-driven catalyst discovery and testing (CATALCHEM-E)
CATALCHEM-E funds development of workflows that combine AI/ML with high-throughput experimentation to cut heterogeneous catalyst R&D timelines from a decade to roughly 12–18 months, moving projects from discovery through synthesis to reactor testing. The program targets catalytic chemistries for low‑carbon feedstocks (CO2, CH4, NH3, bio-intermediates, waste plastics, etc.) to produce produ…
The Catalytic Application Testing for Accelerated Learning Chemistries via High-throughput Experimentation and Modeling Efficiently (CATALCHEM-E) program aims to disrupt and accelerate the design and development cycle for heterogeneous catalyst R&D workflows. The program will span from ratio…
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