CATALYTIC APPLICATION TESTING FOR ACCELERATED LEARNING CHEMISTRIES VIA HIGH-THROUGHPUT EXPERIMENTATION AND MODELING EFFICIENTLY (CATALCHEM-E)

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Program Overview 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 rational material discovery to synthesis and final reactor testing. These novel workflows will be developed by coupling the latest advancements in artificial intelligence (AI) and machine learning (ML) with high-throughput experimentation (HTE) to verifiably complete 10–15 years of traditional catalysis R&D work within 12–18 months, thus achieving more than a ten-time acceleration in the catalyst development cycle.[1] The program will then use these new tools to discover and optimize catalytic chemistries relevant to ARPA-E’s goals. These new chemistries will ultimately help advance the objective of net-zero carbon emissions by 2050.[2] Innovations developed under the CATALCHEM-E program will involve: ·      Future refinery relevant or other next-generation feedstocks such as hydrogen (H2), nitrogen (N2), oxygen (O2), water (H2O), carbon dioxide (CO2), methane (CH4), ammonia (NH3), methanol (MeOH), ethanol (EtOH), bio-intermediates (CxHyOz), waste plastics, and triglycerides (TAGs); and ·      Products like ethylene (C2=) and propylene (C3=) as low carbon monomers, and sustainable aviation fuel (SAF), diesel, and syngas as distillate range hydrocarbons. [1] Sharon Mitchell, Nina-Luisa Michels, and Javier Pérez-Ramírez, “From Powder to Technical Body: The Undervalued Science of Catalyst Scale Up,” Chemical Society Reviews 42, no. 14 (June 21, 2013): 6094–6112, https://doi.org/10.1039/C3CS60076A . [2] U.S. Department of Energy. “How we’re moving to net-zero by 2050,” (April 2021). https://www.energy.gov/articles/how-were-moving-net-zero-2050 .