Linking structure and process in dendritic growth using persistent homology with energy analysis
We present a material analysis method that links structure and process in dendritic growth using explainable machine learning approaches. We employed persistent homology (PH) to quantitatively characterize the morphology of dendritic microstructures. By using interpretable machine learning with ener...
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Science and Technology of Advanced Materials: Methods |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/27660400.2025.2475735 |
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| author | Misato Tone Shunsuke Sato Sotaro Kunii Ippei Obayashi Yasuaki Hiraoka Yui Ogawa Hirokazu Fukidome Alexandre Lira Foggiatto Chiharu Mitsumata Ryunosuke Nagaoka Arpita Varadwaj Iwao Matsuda Masato Kotsugi |
| author_facet | Misato Tone Shunsuke Sato Sotaro Kunii Ippei Obayashi Yasuaki Hiraoka Yui Ogawa Hirokazu Fukidome Alexandre Lira Foggiatto Chiharu Mitsumata Ryunosuke Nagaoka Arpita Varadwaj Iwao Matsuda Masato Kotsugi |
| author_sort | Misato Tone |
| collection | DOAJ |
| description | We present a material analysis method that links structure and process in dendritic growth using explainable machine learning approaches. We employed persistent homology (PH) to quantitatively characterize the morphology of dendritic microstructures. By using interpretable machine learning with energy analysis, we established a robust relationship between structural features and Gibbs free energy. Through a detailed analysis of how Gibbs free energy evolves with morphological changes in dendrites, we uncovered specific conditions that influence the branching of dendritic structures. Moreover, energy gradient analysis based on morphological feature provides a deeper understanding of the branching mechanisms and offers a pathway to optimize thin-film growth processes. Integrating topology and free energy enables the optimization of a range of materials from fundamental research to practical applications. |
| format | Article |
| id | doaj-art-2631fe871a0448e9a20a91bf0809bf73 |
| institution | Kabale University |
| issn | 2766-0400 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Science and Technology of Advanced Materials: Methods |
| spelling | doaj-art-2631fe871a0448e9a20a91bf0809bf732025-08-20T03:51:29ZengTaylor & Francis GroupScience and Technology of Advanced Materials: Methods2766-04002025-12-015110.1080/27660400.2025.2475735Linking structure and process in dendritic growth using persistent homology with energy analysisMisato Tone0Shunsuke Sato1Sotaro Kunii2Ippei Obayashi3Yasuaki Hiraoka4Yui Ogawa5Hirokazu Fukidome6Alexandre Lira Foggiatto7Chiharu Mitsumata8Ryunosuke Nagaoka9Arpita Varadwaj10Iwao Matsuda11Masato Kotsugi12Department of Material Science and Technology, Tokyo University of Science, Tokyo, JapanDepartment of Material Science and Technology, Tokyo University of Science, Tokyo, JapanDepartment of Material Science and Technology, Tokyo University of Science, Tokyo, JapanCenter for Artificial Intelligence and Mathematical Data Science, Okayama University, Kita-ku, Okayama, JapanKyoto University Institute for Advanced Study, Kyoto University, Sakyo-ku, Kyoto, JapanNTT Basic Research Laboratories, NTT Corporation, Atsugi, Kanagawa, JapanResearch Institute of Electrical Communication, Tohoku University, Sendai, Miyagi, JapanDepartment of Material Science and Technology, Tokyo University of Science, Tokyo, JapanDepartment of Material Science and Technology, Tokyo University of Science, Tokyo, JapanDepartment of Material Science and Technology, Tokyo University of Science, Tokyo, JapanDepartment of Material Science and Technology, Tokyo University of Science, Tokyo, JapanInstitute for Solid State Physics, The University of Tokyo, Kashiwa, Chiba, JapanDepartment of Material Science and Technology, Tokyo University of Science, Tokyo, JapanWe present a material analysis method that links structure and process in dendritic growth using explainable machine learning approaches. We employed persistent homology (PH) to quantitatively characterize the morphology of dendritic microstructures. By using interpretable machine learning with energy analysis, we established a robust relationship between structural features and Gibbs free energy. Through a detailed analysis of how Gibbs free energy evolves with morphological changes in dendrites, we uncovered specific conditions that influence the branching of dendritic structures. Moreover, energy gradient analysis based on morphological feature provides a deeper understanding of the branching mechanisms and offers a pathway to optimize thin-film growth processes. Integrating topology and free energy enables the optimization of a range of materials from fundamental research to practical applications.https://www.tandfonline.com/doi/10.1080/27660400.2025.2475735Persistent homologyfree energy analysisstructure-to-property linkagedendrite growth |
| spellingShingle | Misato Tone Shunsuke Sato Sotaro Kunii Ippei Obayashi Yasuaki Hiraoka Yui Ogawa Hirokazu Fukidome Alexandre Lira Foggiatto Chiharu Mitsumata Ryunosuke Nagaoka Arpita Varadwaj Iwao Matsuda Masato Kotsugi Linking structure and process in dendritic growth using persistent homology with energy analysis Science and Technology of Advanced Materials: Methods Persistent homology free energy analysis structure-to-property linkage dendrite growth |
| title | Linking structure and process in dendritic growth using persistent homology with energy analysis |
| title_full | Linking structure and process in dendritic growth using persistent homology with energy analysis |
| title_fullStr | Linking structure and process in dendritic growth using persistent homology with energy analysis |
| title_full_unstemmed | Linking structure and process in dendritic growth using persistent homology with energy analysis |
| title_short | Linking structure and process in dendritic growth using persistent homology with energy analysis |
| title_sort | linking structure and process in dendritic growth using persistent homology with energy analysis |
| topic | Persistent homology free energy analysis structure-to-property linkage dendrite growth |
| url | https://www.tandfonline.com/doi/10.1080/27660400.2025.2475735 |
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