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MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.

The advance opens a path to next-generation devices with unique optical and electronic properties.

Using machine learning, the computational method can provide details of how materials work as catalysts, semiconductors, or battery components.

The molecules, known as acenes, could be useful as organic light-emitting diodes or solar cells, among other possible applications.