Episode 17 of Quantum Computing Business with Fexingo dives into how quantum computing is accelerating materials design and discovery. Lucas and Luna explore a specific case: BMW's use of quantum simulations to develop next-generation battery cathodes. The episode covers the technical challenge of modeling electron behavior in complex materials, the shift from noisy intermediate-scale quantum (NISQ) to error-corrected machines, and the business implications for automotive, aerospace, and chemical industries. They discuss the role of hybrid classical-quantum algorithms, the economics of replacing physical R&D with simulation, and why materials science may be the killer app for quantum computing before large-scale error correction arrives. Listeners learn why companies like Volkswagen, Airbus, and Microsoft are investing in quantum materials workflows today, and how early adopters are already seeing a 10x speedup in certain screening tasks. The episode closes with a reflection on the timeline for industrial-scale quantum materials design and what it means for supply chains and product innovation.

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