The Catalytic Application Testing for Accelerated Learning Chemistries via High-throughput Experimentation and Modeling Efficiently (CATALCHEM-E) program supports the small-scale research and development of hetergeneous catalysts, solid materials that reduce the inherent energy needed to drive industrial-scale chemical reactions responsible for making everyday products and commodities.
Office of NEPA Policy and Compliance
July 13, 2026
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The Catalytic Application Testing for Accelerated Learning Chemistries via High-throughput Experimentation and Modeling Efficiently (CATALCHEM-E) program supports the small-scale research and development of hetergeneous catalysts, solid materials that reduce the inherent energy needed to drive industrial-scale chemical reactions responsible for making everyday products and commodities. Specifically, projects will focus on using artificial intelligence and machine learning (AI/ML) to expedite the discovery of new materials for catalysis, train AI/ML algorithms from existing or new high-throughput experimentation data, and design, create, test, analyze, and validate their models using rapid automated workflows and iterating quickly on the knowledge learned.
If successful, CATALCHEM-E projects would accelerate discovery of new, profitable catalysts for energy and chemical applications such as converting waste plastics or syngas, unlocking new process technology like reactive carbon capture, and enable the production of industrial chemicals and next generation fuels, ultimately reducing dependence on foreign energy, thereby increasing U.S. energy security.