Exploring Deep Learning for Metalloporphyrins: Databases, Molecular Representations, and Model Architectures
Metalloporphyrins have been studied as biomimetic catalysts for more than 120 years and have accumulated a large amount of data, which provides a solid foundation for deep learning to discover chemical trends and structure–function relationships. In this study, key components of deep learning of met...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
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| Series: | Catalysts |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4344/12/11/1485 |