Catalytic Application Testing for Accelerated Learning Chemistries via High-throughput Experimentation and Modeling Efficiently SBIR/STTR (CATALCHEM-E SBIR/STTR)
CATALCHEM-E funds development of integrated AI/ML and high‑throughput experimentation workflows to accelerate heterogeneous catalyst R&D, aiming to compress 10–15 years of work into 12–18 months. Teams will apply these tools to discover and optimize catalysts for reactions using feeds like H2, CO2, methane, bio‑intermediates, and waste plastics to produce low‑carbon monomers and fuels (e.g…
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