In a recent study, scientists integrated machine learning with DFT calculations to map the C-H dissociation process on single-atom alloy surfaces. Their extensive database offers valuable insights into methane decomposition and efficient hydrogen production. Researchers like Weiqiao Deng demonstrate how precise catalyst design can reshape energy solutions.
Q&A
- What is DFT?
- How does machine learning improve catalyst design?
- Why is methane decomposition important for hydrogen production?