Quantum computing offers a transformative approach to materials simulation, potentially performing quantum-mechanical calculations orders of magnitude faster and more accurately than classical methods on conventional high-performance computers. This unlocks the true computational design of novel materials, paving the way for solutions to global challenges related to sustainability and renewable energies. This capability can revolutionize various fields, enabling, for example, the improvement of catalytic processes and a deeper, atomistic understanding of material degradation. These advancements pave the way for knowledge-based optimization of load, process, and operating conditions in devices like fuel cells, ultimately reducing our reliance on scarce, environmentally harmful, and expensive materials. The focus of the PhD thesis is the development and testing of hybrid quantum-classical workflows and relevant models for simulating industrially relevant materials on a near-term quantum computer.