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| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.05613 |
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| _version_ | 1866914372922638336 |
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| author | Zhang, Xin Lee, Scott B. Chatterjee, Sudipta Pi, Hanqi Yang, Yi Katmer, Fatmagül Ward, Emily G. Widdowson, Daniel E. Tam, Charles C. Schwarz, Sarah Pollak, Connor J. Moya, Jaime M. Skorupskii, Grigorii Kurlin, Vitaliy A. Wilson, Stephen D. Bernevig, B. Andrei Schoop, Leslie M. |
| author_facet | Zhang, Xin Lee, Scott B. Chatterjee, Sudipta Pi, Hanqi Yang, Yi Katmer, Fatmagül Ward, Emily G. Widdowson, Daniel E. Tam, Charles C. Schwarz, Sarah Pollak, Connor J. Moya, Jaime M. Skorupskii, Grigorii Kurlin, Vitaliy A. Wilson, Stephen D. Bernevig, B. Andrei Schoop, Leslie M. |
| contents | Crystal structures define how matter is organized at the atomic level. In the realm of crystalline inorganic materials, new structure types are rarely found, and most experimentally-realized structural motifs were established decades ago. Considerable efforts are underway to discover new crystalline inorganic compounds, often aided by artificial intelligence (AI). However, thus far, these methods have not yielded convincing new structure types, but rather substitutional variations of existing compounds. Here we introduce a new structure type adopted by the compound GdNiSn4, discovered the old-fashioned way. We test whether current state-of-the-art AI-based material generation models can predict this material in its correct structure and find that they fail to do so. We carefully analyze the new structure and argue that it can be viewed as a stack of two known structure types. We explore electronic and steric factors underlying its stability and propose strategies to improve future AI-guided materials discovery. Furthermore, we report complex magnetic properties in GdNiSn4, highlighting its potential interest for future studies of unconventional magnetism. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_05613 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Identification of an Unreported Structure Type in GdNiSn4 and Its Implications for Materials Prediction Zhang, Xin Lee, Scott B. Chatterjee, Sudipta Pi, Hanqi Yang, Yi Katmer, Fatmagül Ward, Emily G. Widdowson, Daniel E. Tam, Charles C. Schwarz, Sarah Pollak, Connor J. Moya, Jaime M. Skorupskii, Grigorii Kurlin, Vitaliy A. Wilson, Stephen D. Bernevig, B. Andrei Schoop, Leslie M. Materials Science Crystal structures define how matter is organized at the atomic level. In the realm of crystalline inorganic materials, new structure types are rarely found, and most experimentally-realized structural motifs were established decades ago. Considerable efforts are underway to discover new crystalline inorganic compounds, often aided by artificial intelligence (AI). However, thus far, these methods have not yielded convincing new structure types, but rather substitutional variations of existing compounds. Here we introduce a new structure type adopted by the compound GdNiSn4, discovered the old-fashioned way. We test whether current state-of-the-art AI-based material generation models can predict this material in its correct structure and find that they fail to do so. We carefully analyze the new structure and argue that it can be viewed as a stack of two known structure types. We explore electronic and steric factors underlying its stability and propose strategies to improve future AI-guided materials discovery. Furthermore, we report complex magnetic properties in GdNiSn4, highlighting its potential interest for future studies of unconventional magnetism. |
| title | Identification of an Unreported Structure Type in GdNiSn4 and Its Implications for Materials Prediction |
| topic | Materials Science |
| url | https://arxiv.org/abs/2603.05613 |