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Researchers at Duke University have demonstrated that incorporating known physics into machine learning algorithms can help the inscrutable black boxes attain new levels of transparency and insight into material properties. In one of the first projects of its kind, researchers constructed a modern machine learning algorithm to determine the properties of a class of engineered materials known as metamaterials and to predict how they interact with electromagnetic fields. Because it first had to consider the metamaterial's known physical constraints, the program was essentially forced to show its work. Not only did the approach allow the algorithm to accurately predict the metamaterial's properties, it did so more efficiently than previous methods while providing new insights. The results appear online the week of May 9 in the journal Advanced Optical Materials.