Summary of Crystal Structure Generation Based on Material Properties, by Chao Huang et al.
Crystal Structure Generation Based On Material Properties
by Chao Huang, JiaHui Chen, HongRui Liang, ChunYan Chen, Chen Chen
First submitted to arxiv on: 13 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Materials Science (cond-mat.mtrl-sci)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed Crystal DiT model uses data-driven methods to generate crystal structures based on expected material properties, bridging the gap between material properties and crystal structure generation. By embedding material properties and combining symmetry information predicted by a large language model, the model effectively maps material properties to crystal structures. Experimental verification demonstrates good performance of the proposed method. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Scientists are working hard to discover new materials that meet specific requirements for their crystal structure. While data-driven methods have made progress in generating crystal structures, there is still room for improvement when it comes to mapping material properties to these structures. A new approach called Crystal DiT helps fix this gap by creating crystal structures based on the expected properties of a material. Tests show that this method works well. |
Keywords
» Artificial intelligence » Embedding » Large language model
