Accelerating material design with the generative toolkit for scientific discovery
Abstract With the growing availability of data within various scientific domains, generative models hold enormous potential to accelerate scientific discovery. They harness powerful representations learned from datasets to speed up the formulation of novel hypotheses with the potential to impact mat...
Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-05-01
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Series: | npj Computational Materials |
Online Access: | https://doi.org/10.1038/s41524-023-01028-1 |