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08_機械学習ポテンシャルによる溶融鉄構造再現性の検討
https://sangitan.repo.nii.ac.jp/records/18
https://sangitan.repo.nii.ac.jp/records/18662c637a-a04c-4680-82b6-d98d7fb97531
名前 / ファイル | ライセンス | アクション |
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vol55_08_研究ノート_森 英喜_p49-51 (485.9 kB)
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Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
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公開日 | 2022-03-10 | |||||
タイトル | ||||||
タイトル | 08_機械学習ポテンシャルによる溶融鉄構造再現性の検討 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Consideration of Transferability of Molten Iron of Machine Learning Potentials | |||||
言語 | ||||||
言語 | jpn | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | 研究ノート | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Machine Learning potential | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | first principles calculation | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | molten iron | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | departmental bulletin paper | |||||
著者 |
森, 英喜
× 森, 英喜× 奥村, 雅彦× 板倉, 充洋 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | The inter-atomic potential based on artificial neural network (ANN) is very promising tool for atomic modeling. Using high quality training set constructed by First principles calculation based on Density functional theory (DFT), ANN potential would become sophisticated replica of DFT. However, the transferability of ANN potential depends on the DFT training dataset. In this study, we perform molecular dynamics (MD) calculations for molten iron, which is not directly included in the training data. We also examine the results to discuss the applicability of the constructed potential. | |||||
書誌情報 |
産業技術短期大学誌 en : BULLETIN OF COLLEGE OF INDUSTRIAL TECHNOLOGY 巻 55, 号 1, p. 49-51, 発行日 2022-03-10 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0916-3727 |