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説明:

We investigated segregant development for FePt high-density magnetic recording media using LLMs and identified new fluoride-based materials. By increasing the temperature of the softmax function to select probable vocabularies, we successfully incorporated the prior knowledge involved in LLM training into the material selection process (exploratory generation) and identified LaF3 as an optimal material. Meanwhile, we independently conducted sputtering deposition of FePt-LaF3 nanogranular samples and verified whether the LLM could reproduce the results. The inhomogeneity in the surface chemical composition of FePt-LaF3 in the non-equilibrium state of sputtering were also reproduced by the LLM, leading to the identification of AlF3 as an alternative segregant. Phenomena that can occur in physical experiments are almost accurately reproduced by LLM, demonstrating the usefulness of LLM predictions in material development.

権利情報:

• Creative Commons BY Attribution 4.0 International
  

キーワード: large language model, exploratory generation, FePt nanogranular film, fluoride segregant, LaF3, AlF3

刊行年月日: 2026-12-31

出版者: Informa UK Limited

掲載誌:

• Science and Technology of Advanced Materials: Methods (ISSN: 27660400) vol. 6 issue. 1 2613512

研究助成金:

• Ministry of Education, Culture, Sports, Science and Technology JPMXP1122715503
• Council for Science, Technology and Innovation JPJ012308

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1080/27660400.2026.2613512

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更新時刻: 2026-04-21 13:35:17 +0900

MDRでの公開時刻: 2026-04-21 18:26:11 +0900