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ディーブ 冴

ディーブ 冴 (DIEB, Sae) 0000-0002-8111-2009

Address
305-0044 茨城県つくば市並木1-1 [アクセス]

[論文] | [書籍] | [会議録] | [口頭発表] | [その他の文献] | [公開特許出願]

論文 TSV

2023
  1. Sae Dieb, Yoshiaki Toda, Keitaro Sodeyama, Masahiko Demura. Machine learning-assisted determination of material chemical compositions: a study case on Ni-base superalloy. Science and Technology of Advanced Materials: Methods. 3 [1] (2023) 2278321 10.1080/27660400.2023.2278321 Open Access
  2. Vickey Nandal, Sae Dieb, Dmitry S. Bulgarevich, Toshio Osada, Toshiyuki Koyama, Satoshi Minamoto, Masahiko Demura. Artificial intelligence inspired design of non-isothermal aging for γ–γ′ two-phase, Ni–Al alloys. Scientific Reports. 13 [1] (2023) 12660 10.1038/s41598-023-39589-2 Open Access
  3. Zhilong Song, Qionghua Zhou, Shuaihua Lu, Sae Dieb, Chongyi Ling, Jinlan Wang. Adaptive Design of Alloys for CO2 Activation and Methanation via Reinforcement Learning Monte Carlo Tree Search Algorithm. The Journal of Physical Chemistry Letters. 14 [14] (2023) 3594-3601 10.1021/acs.jpclett.3c00242
2022
  1. Jiawei Lai, A. Bolyachkin, N. Terada, S. Dieb, Xin Tang, T. Ohkubo, H. Sepehri-Amin, K. Hono. Machine learning assisted development of Fe2P-type magnetocaloric compounds for cryogenic applications. Acta Materialia. 232 (2022) 117942 10.1016/j.actamat.2022.117942
2021
  1. Luca Foppiano, Sae Dieb, Akira Suzuki, Pedro Baptista de Castro, Suguru Iwasaki, Azusa Uzuki, Miren Garbine Esparza Echevarria, Yan Meng, Kensei Terashima, Laurent Romary, Yoshihiko Takano, Masashi Ishii. SuperMat: construction of a linked annotated dataset from superconductors-related publications. Science and Technology of Advanced Materials: Methods. 1 [1] (2021) 34-44 10.1080/27660400.2021.1918396 Open Access
  2. Sae Dieb, Kou Amano, Kosuke Tanabe, Daitetsu Sato, Masashi Ishii, Mikiko Tanifuji. Creating research topic map for NIMS SAMURAI database using natural language processing approach. Science and Technology of Advanced Materials: Methods. 1 [1] (2021) 2-11 10.1080/27660400.2021.1899426 Open Access
2020
  1. Sae Dieb, Zhilong Song, Wan-Jian Yin, Masashi Ishii. Optimization of depth-graded multilayer structure for x-ray optics using machine learning. Journal of Applied Physics. 128 [7] (2020) 074901 10.1063/5.0012351
  2. Thaer M. Dieb, Masashi Ishii. Machine-learning-assisted design of depth-graded multilayer X-ray structure. Proceedings of SPIE - The International Society for Optical Engineering. (2020) 112870C 10.1117/12.2544507
2019
  1. Thaer M. Dieb, Shenghong Ju, Junichiro Shiomi, Koji Tsuda. Monte Carlo tree search for materials design and discovery. MRS Communications. 9 [02] (2019) 532-536 10.1557/mrc.2019.40 Open Access
2018
  1. Thaer M. Dieb, Zhufeng Hou, Koji Tsuda. Structure prediction of boron-doped graphene by machine learning. The Journal of Chemical Physics. 148 [24] (2018) 241716 10.1063/1.5018065 Open Access
2017
  1. Thaer M. Dieb, Shenghong Ju, Kazuki Yoshizoe, Zhufeng Hou, Junichiro Shiomi, Koji Tsuda. MDTS: automatic complex materials design using Monte Carlo tree search. Science and Technology of Advanced Materials. 18 [1] (2017) 498-503 10.1080/14686996.2017.1344083 Open Access

書籍 TSV

会議録 TSV

2018
  1. JU Shenghong, DIEB, Sae, TSUDA, Koji, SHIOMI, Junichiro. Optimizing Interface/Surface Roughness for Thermal Transport. Machine Learning for Molecules and Materials NIPS 2018 Workshop. (2018) 9999-1-9999-7
  2. JU Shenghong, DIEB, Sae, TSUDA, Koji, SHIOMI, Junichiro. Designing Nanostructures for Heat Transport via Materials Informatics.. The 16th International Heat Transfer Conference. (2018) 9999-1-9999-8
  3. DIEB, Sae, OKA, Hiroyuki, ISHII, Masashi. Linking polymer names abbreviation to their definition in related scientific documents. Third International Workshop on SCIentific DOCument Analysis (SCIDOCA2018). (2018) 9999-1-9999-6

口頭発表 TSV

2023
  1. NANDAL, Vickey, DIEB, Sae, BULGAREVICH, Dmitry, OSADA, Toshio, KOYAMA Toshiyuki, MINAMOTO, Satoshi, DEMURA, Masahiko. Critical Assessment of AI-Founded Non-Isothermal Aging Treatment Schedules for Improving 0.2% Proof Stress in Binary Ni-Al Alloys. MRM2023/IUMRS-ICA2023 Materials Innovation for Sustainable Development Goals. 2023
  2. Yoshihiro Chida, DIEB Sae, SODEYAMA Keitaro, Hiraku Masui, Arata Umehara, Naoto Todoroki, Toshimasa Wadayama. 白金－ハイエントロピー合金単結晶表面系の酸素還元反応特性：機械学習による合成条件検討. 第64回電池討論会. 2023
  3. NANDAL, Vickey, DIEB, Sae, BULGAREVICH, Dmitry, OSADA, Toshio, Toshiyuki Koyama, MINAMOTO, Satoshi, DEMURA, Masahiko. Utilizing Artificial Intelligence and Expert Knowledge to Optimize Non-Isothermal Aging Heat Treatment for Enhancing 0.2% Proof Stress in γ – γ' Binary Ni-Al Alloys. 14th ISAJ Symposium (Integrated Science for a Sustainable Society). 2023
  4. DIEB, Sae, FOPPIANO, Luca, SODEYAMA, Keitaro, Tanifuji Mikiko. Creating a Visual Topic Map for Battery Researchers using a Large Global Open Dataset. 244 ECS meeting. 2023
  5. NANDAL, Vickey, DIEB, Sae, BULGAREVICH, Dmitry, OSADA, Toshio, KOYAMA Toshiyuki, MINAMOTO, Satoshi, DEMURA, Masahiko. Optimizing Heat Treatment Routes for Ni-Based Alloys Using Monte Carlo Tree Search. Materials Science & Technology (MS&T23) Technical Meeting and Exhibition. 2023
  6. DIEB, Sae, FOPPIANO, Luca, SODEYAMA, Keitaro, Tanifuji Mikiko. Visual Topic Mapping for Battery Related Research using a Global Open Catalog. The 84th JSAP fall meeting 2023　2023年第84回応用物理学会秋季学術講演会. 2023
  7. NANDAL, Vickey, DIEB, Sae, BULGAREVICH, Dmitry, OSADA, Toshio, KOYAMA Toshiyuki, MINAMOTO, Satoshi, DEMURA, Masahiko. An Evaluation of AI-Discovered Non-Isothermal Aging Treatment Strategies for Enhancing 0.2% Proof Stress in Ni-Al Alloys with γ - γ' Microstructure. Japan Institute of Metals 2023 Autumn Meeting (173rd) 2023年秋期(第173回）講演大会. 2023
  8. Masaru Kato, Colin Tadgell, DIEB Sae, Takahito Hoshi, SODEYAMA Keitaro, Ichizo Yagi. アクティブラーニングによる非白金水素酸化触媒の開発. The 90th Annual Meeting of the Electrochemical Society in Japan　電気化学会第90回大会. 2023
  9. DIEB, Sae. Creating a visual research topic map for SAMURAI catalogue and an introduction to Materials Data Platform (DICE) at the National Institute for Materials Science (NIMS), Japan. VIVO Talks. 2023 招待講演
  10. NANDAL, Vickey, DIEB, Sae, BULGAREVICH, Dmitry, OSADA, Toshio, KOYAMA Toshiyuki, MINAMOTO, Satoshi, DEMURA, Masahiko. Machine Learning Technique for Predicting the Optimized Heat Treatment Schedules in Ni-based Superalloys. International Conference on Advances in Structural Alloys and Their Manufacturing (ASATM) 2023. 2023
2022
  1. DIEB, Sae, SODEYAMA, Keitaro, TANIFUJI, Mikiko. Visualization of Materials Science Topics in Publications of Institutional Repository using Natural Language Processing. 1st International Conference on FAIR Digital Objects. 2022 招待講演
  2. DIEB, Sae, SODEYAMA, Keitaro, TANIFUJI, Mikiko. Creating visual research topic map for materials science publications using natural language processing (NLP). 11th International Workshop on Combinatorial Materials Science and Technology. 2022
  3. NANDAL, Vickey, DIEB, Sae, BULGAREVICH, Dmitry, OSADA, Toshio, KOYAMA Toshiyuki, DEMURA, Masahiko. Non-Isothermal Heat Treatments designed by Artificial Intelligence for Ni/Ni3Al two-phase alloys. 日本金属学会 2022年秋期第171回講演大会. 2022
  4. BOLYACHKIN, Anton, LAI, Jiawei, DENGINA, Ekaterina, TERADA, Noriki, DIEB, Sae, TANG, Xin, OHKUBO, Tadakatsu, SEPEHRI AMIN, Hossein, HONO, Kazuhiro. Machine learning assisted development of Fe2P-type magnetocaloric compounds for cryogenic applications. 日本金属学会 2022年秋期第171回講演大会　JIM Autumn Meeting. 2022
  5. DIEB, Sae, FOPPIANO, Luca, TERASHIMA, Kensei, BAPTISTA DE CASTRO Pedro, TAKANO, Yoshihiko, ISHII, Masashi. Superconductor Research Papers Clustering using Weighted Annotated Information. The 36th Annual Conference of the Japanese Society for Artificial Intelligence https://www.ai-gakkai.or.jp/jsai2022/en. 2022
2021
  1. DIEB Sae, TODA Yoshiaki, DEMURA Masahiko. Optimization of Ni-base Superalloy Compositions using Monte Carlo Tree Search with Expansion Policy. MATERIALS RESEARCH MEETING 2021 (MRM2021). 2021
  2. FOPPIANO Luca, DIEB Sae, BAPTISTA DE CASTRO Pedro, MENG Yan, TERASHIMA Kensei, TAKANO Yoshihiko, ISHII Masashi. Machine readable extraction of chemically modified materials name. 2021年第68回応用物理学会春季学術講演会. 2021
  3. DIEB Sae, FOPPIANO Luca, TERASHIMA Kensei, BAPTISTA DE CASTRO Pedro, Yoshioka Masaharu, TAKANO Yoshihiko, ISHII Masashi. Superconductor Research Papers Clustering using Annotated Information. 2021年 第68回応用物理学会春季学術講演会. 2021
2020
  1. FOPPIANO, Luca, DIEB, Sae, SUZUKI, Akira, BAPTISTA DE CASTRO Pedro, MENG Yan, TERASHIMA, Kensei, TAKANO, Yoshihiko, ISHII, Masashi. Toward full automatic identification of superconducting materials and their properties in original papers: ambitious scope and current status. 第81回応用物理学会秋季学術講演会. 2020
  2. DIEB, Sae, ISHII, Masashi. Enhanced Monte Carlo Tree Search for Materials Design and Discovery. 第81回 応用物理学会秋季学術講演会. 2020
  3. FOPPIANO, Luca, DIEB, Sae, SUZUKI, Akira, BAPTISTA DE CASTRO Pedro, IWASAKI Suguru, MENG Yan, TERASHIMA, Kensei, TAKANO, Yoshihiko, ISHII, Masashi. Automatic construction of an accessible linked dataset from scientific literature for superconducting materials discovery. CONFERENCE ON A FAIR DATA INFRASTRUCTURE FOR MATERIALS GENOMICS. 2020
  4. Song Zhilong, Chen Xiwen, DIEB, Sae, ISHII, Masashi. Design of thermodynamically stable perovskites using machine learning. 第67回 応用物理学会 春季学術講演会. 2020
  5. FOPPIANO, Luca, DIEB, Sae, SUZUKI, Akira, TERASHIMA, Kensei, BAPTISTA DE CASTRO Pedro, IWASAKI, Suguru, TAKANO, Yoshihiko, ISHII, Masashi. SuperMat: Corpus for Extraction of Superconductor Materials Data. JSAP Spring 2020. 2020
  6. FOPPIANO, Luca, DIEB, Sae, SUZUKI, Akira, ISHII, Masashi. Linkable Data Extraction from Scientific Literature for Superconductor Database Construction. AMDS 2020. 2020
  7. DIEB, Sae, ISHII, Masashi. Multilayer Structure Design Using Monte Carlo Tree Search for X-ray Applications. The 7th Asian materials data symposium. 2020
2019
  1. DIEB, Sae. Machine Learning Assisted Design of Depth-Graded X-ray Multilayer Structure. The University of Electro-Communications Seminar. 2019 招待講演
  2. DIEB, Sae. Machine Learning Assisted Materials Design and Discovery. 1st NAIST International Symposium on Data Science. 2019 招待講演
  3. DIEB, Sae, SUZUKI, Akira, FOPPIANO, Luca, ISHII, Masashi. Automatic Collection of Critical Temperature Related Expressions from Tables in Superconductors Development Publications. 80th JSAP fall meeting. 2019
  4. FOPPIANO, Luca, SUZUKI, Akira, DIEB, Sae, ISHII, Masashi, TANIFUJI, Mikiko. Leveraging Segmentation of Physical Units through a Newly Open Source Corpus. JSAP Autumn 2019. 2019
  5. ISHII, Masashi, DIEB, Sae, Machine Learning Assisted Design of Depth-Graded Multilayer X-ray Structure. International Young Researchers Workshop on Synchrotron Radiation Science 2019. 2019
  6. FOPPIANO, Luca, DIEB, Sae, SUZUKI, Akira, ISHII, Masashi. Proposal of Automatic Extraction Framework of Superconductors Related Information from Scientific Literature. IEICE. 2019
  7. DIEB, Sae. Machine Learning Interface/Surface Roughness optimization for Thermal Transport. The 8th Materials research by information integration (Mi2i) forum. 2019
  8. JU Shenghong, DIEB, Sae, SHIOMI, Junichiro, TSUDA, Koji. Surface/Interface Roughness Optimization for Thermal Transport using Monte Carlo Tree Search. International Symposium on Materials Informatics. 2019
2018
  1. DIEB, Sae, JU Shenghong, HOU, Zhufeng, SHIOMI, Junichiro, TSUDA, Koji. Materials Structure Design using Monte Carlo Tree Search with Bayesian rollout. ERATO Minato Discrete Manipulation System Project, Early Summer. 2018
2017
  1. ディーブ モスタファ サエル, Shenghong Ju, Kazuki Yoshizoe, 塩見 淳一郎, 津田 宏治. Materials Design using Tree Search. The 15th International Confernece on Advanced Materials. 2017
  2. 鞠 生宏, ディーブ モスタファ サエル, 美添 一樹, 津田 宏治, 塩見 淳一郎. マテリアルズ・インフォマティクスによるフォノン輸送制御のためのナノ構造設計. 第54回 日本伝熱シンポジウム. 2017
2016
  1. ディーブ モスタファ サエル, 津田 宏治. DAMAS: An Annotation Support Tool for Materials Information. The 5th Asian Materials Data Symposium. 2016
  2. ディーブ モスタファ サエル, Kazuki Yoshizoe, Shenghong Ju, 津田 宏治. Superlattice Structure Design Using Monte Carlo Tree Search. Machine learning meets many particles problems. 2016
  3. ディーブ モスタファ サエル, 津田 宏治, ホー ズーフォン. Potential Energy Prediction of Crystals using Kernel Methods. ERATO Minato Discrete Manipulation System Project, Early Summer. 2016

その他の文献 TSV

2022
  1. DIEB, Sae, SODEYAMA, Keitaro, TANIFUJI, Mikiko. Visualization of Materials Science topics in Publications of Institutional Repository using Natural Language processing. Research Ideas and Outcomes. 8 (2022) e95679
2019
  1. FOPPIANO, Luca, DIEB, Sae, SUZUKI, Akira, ISHII, Masashi. Proposal for Automatic Extraction Framework of Superconductors Related Information from Scientific Literature. IEICE technical report. (2019) 1-5

公開特許出願 TSV

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