Machine Learning and Informatics Accelerate New Material Discoveries

The potential applications for machine learning and informatics seem limitless. From a wide variety of applications in medicine and healthcare to saving the whales, these areas of artificial intelligence are solving problems in new and inherently innovative ways. Most recently, the machine learning-informatics power couple has been improving the process of discovering new materials based on targeted characteristics. An initial alloy experimental dataset with known thermal dissipation and features or materials descriptors serves as input to the inference model. The model is then trained and cross-validated with the initial alloy data. A data set of unexplored alloys defines the total search space of probable candidates. The trained model in is applied to all the alloys to predict their thermal dissipation. The design chooses the ‘best’ four candidates for synthesis and characterization…

Link to Full Article: Machine Learning and Informatics Accelerate New Material Discoveries

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