Indonesia, April 22 -- Discovering and characterizing new materials is important for unlocking advances in fields like clean energy, advanced manufacturing, and improved infrastructure. Researchers use machine learning and other computational tools to help them, but the trial-and-error nature of the process creates specific challenges. The research produces large amounts of experimental and computational data, and scientists need tools that can track and store not only the results but also the chain of reasoning behind them. A newly developed system tracks and stores not only the results but also the chain of reasoning behind them, allowing researchers to review the decision making process for a greater transparency and reproducibility in...