Catalysis and Chemical Processing

Catalysts underpin over 80% of industrial chemical processes, yet discovering new catalytic materials still relies heavily on trial-and-error synthesis and incremental modification of known formulations. A single heterogeneous catalyst system involves choices across active metal, oxidation state, support material, particle morphology, promoter elements, and preparation method. This creates a design space so large that empirical exploration can only sample it sparsely. For emerging applications like CO₂ reduction, green hydrogen, and biomass conversion, high-performing catalysts remain undiscovered because experimental throughput cannot match the scale of the search.

Computational screening with density functional theory evaluates adsorption energies on idealized surface facets, but only for candidates researchers think to propose. Descriptor-based models such as d-band center correlations work within known families yet break down for novel multi-metallic or single-atom systems where scaling relations no longer hold. Combinatorial library synthesis covers narrow composition ranges. None of these methods truly generates candidates; each filters from a human-curated starting set.