Machine learning models for accurately predicting properties of CsPbCl3 Perovskite quantum dots
Abstract Perovskite Quantum Dots (PQDs) have a promising future for several applications due to their unique properties. This study investigates the effectiveness of Machine Learning (ML) in predicting the size, absorbance (1S abs) and photoluminescence (PL) properties of CsPbCl3 PQDs using synthesi...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-08110-2 |
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