Hybrid Quantum-Classical Algorithms for Fuel Cell Optimization
Hydrogen fuel cells represent one of the most exciting technologies available for producing clean energy for onsite combined heat and power delivery, portable electronics, and electric vehicles. In the transportation sector specifically, several commercial vehicles powered by hydrogen have hit the market in the last several years, on top of a growing number of city buses and cargo trucks running on fuel cells. However, high cost due to the use of the precious metal platinum remains a barrier to their widespread adoption. In an effort to design materials that could replace this expensive platinum, we will investigate a combination of classical and quantum computing methods to model fuel cells at the atomic level. This modeling is an exciting application of quantum computers, which in theory can model the electronic structure of materials with much greater fidelity and efficiency than classical computers. In practice, quantum computers are still too small and noisy to simulate chemistry at meaningful scale.