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Machine learning methods move self-driving labs closer to materials discovery at scale

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Machine learning methods move self-driving labs closer to materials discovery at scale

Machine learning doesn't replace human intelligence, but it can outlast human endurance, which makes it a helpful tool for chemistry and materials discovery. Scientists know machine learning models can make predictions based on the vast reams of data they are trained on, but can they take it a step further and massively scale up testing those predictions?

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Artigo originalmente publicado em phys.org
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