Engineers develop a way to streamline solar cell testing, accelerating a process that can be slow and costly

The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year Ph.D. student, a Johns Hopkins team has developed a machine learning method that promises to dramatically speed up this process, paving the way for more efficient and affordable renewable energy solutions.

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