Researchers at the University of Toronto have harnessed artificial intelligence in collaboration with the Canadian Light Source at the University of Saskatchewan to expedite the discovery of a new catalyst for green hydrogen production. The traditional method of using electricity to split water into oxygen and hydrogen gas is energy-intensive and relies on rare, expensive metals, prompting the search for a more efficient and cost-effective catalyst. Led by Jehad Abed, a team developed a computer program that analyzed over 36,000 metal oxide combinations to identify the most promising catalyst. Through virtual simulations and lab experiments, the team confirmed that an alloy of ruthenium, chromium, and titanium in specific proportions outperformed existing catalysts by 20 times in terms of stability and durability. The team utilized the ultra-bright X-rays at the Canadian Light Source and the Advanced Photon Source in Chicago to analyze the catalyst's performance under different conditions. Abed emphasized the AI program's ability to accelerate the discovery process, highlighting its potential to simulate years of testing in a matter of days. Although the AI-recommended alloy showed exceptional promise in the lab, further testing is necessary to ensure its viability in practical applications. The researchers are optimistic that AI-driven approaches will pave the way for more sustainable and efficient green energy solutions, bringing us closer to widespread adoption of renewable resources.