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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Matéria produzida com curadoria editorial assistida por IA, a partir de pauta de
phys.org.
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