Four Labs Find That Experimental Differences Undermine AI Catalyst Predictions

Turning carbon dioxide into usable fuel depends on finding catalysts that stay efficient over time, and AI models were supposed to speed that search. A four-laboratory comparison found that ordinary differences in experimental setup produce training data inconsistent enough to make the models’ recommendations unreliable.