  Catalytic processes are vital in the chemical industry, with
nitrogen-to-ammonia conversion being a major industrial process. Designing
catalysts relies on computational chemistry methods like Density Functional
Theory (DFT), which have limitations in accuracy, especially for complex
materials. Quantum computing advancements offer promise for precise ab-initio
methods. We introduce a hybrid quantum-classical workflow to model chemical
reactions on surfaces, demonstrated on nitrogen activation and dissociation on
small Fe clusters and an iron surface. We decoupled key electronic structures
using CASSCF, translated them into qubits, and estimated energies with quantum
and classical simulations, showing potential for quantum computing in catalysis
research as technology scales up.
