Predicting carbon nanotube forest attributes and mechanical properties using simulated images and deep learning
Abstract Understanding and controlling the self-assembly of vertically oriented carbon nanotube (CNT) forests is essential for realizing their potential in myriad applications. The governing process–structure–property mechanisms are poorly understood, and the processing parameter space is far too va...
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| Auteurs principaux: | , , , , , |
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| Format: | article |
| Langue: | EN |
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Nature Portfolio
2021
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| Accès en ligne: | https://doaj.org/article/7cbc035ed72342a18a4f677e7c46a9ae |
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