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AI Aids in the Global Hunt for Natural Hydrogen Deposits

Scientists are employing deep learning models to identify surface indicators of subsurface natural hydrogen reservoirs, focusing on semicircular depressions (SCDs) often found near "gold hydrogen" deposits. Utilising global satellite imagery, researchers Sam Herreid and Saurabh Kaushik from the Byrd Polar and Climate Research Center at The Ohio State University have trained an algorithm to pinpoint these elusive SCDs worldwide. Their innovative approach has revealed a greater abundance of these formations, challenging previous assumptions about their scarcity. Despite the promising advancements, distinguishing real hydrogen deposits from other circular land features remains a challenge, emphasising the nascency and need for further research and development in hydrogen exploration technologies.

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