Bridging language models and computational materials science: A prompt‐driven framework for material property prediction
Abstract Large language models (LLMs) have demonstrated effectiveness in interpreting complex data. However, they encounter challenges in specialized applications, such as predicting material properties, due to limited integration with domain‐specific knowledge. To overcome these challenges, we intr...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley-VCH
2025-06-01
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| Series: | Materials Genome Engineering Advances |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/mgea.70013 |
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