| 研究課題/領域番号 |
21K14675
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| 研究種目 |
若手研究
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| 配分区分 | 基金 |
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| 審査区分 |
小区分35010:高分子化学関連
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| 研究機関 | 統計数理研究所 |
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研究代表者 |
Wu Stephen 統計数理研究所, データ科学研究系, 准教授 (70804186)
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| 研究期間 (年度) |
2021-04-01 – 2024-03-31
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| 研究課題ステータス |
交付 (2022年度)
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| 配分額 *注記 |
4,550千円 (直接経費: 3,500千円、間接経費: 1,050千円)
2023年度: 1,950千円 (直接経費: 1,500千円、間接経費: 450千円)
2022年度: 1,300千円 (直接経費: 1,000千円、間接経費: 300千円)
2021年度: 1,300千円 (直接経費: 1,000千円、間接経費: 300千円)
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| キーワード | polymer informatics / generative models / open source software / ensemble learning / virtual library |
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| 研究開始時の研究の概要 |
I propose to generate collections of polymer candidates with machine learning that will be openly available in a single user-friendly platform, and will serve as a handy starting point for polymer scientists to tackle various design problems of functional polymers along with their expert knowledge.
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| 研究実績の概要 |
In 2022, multiple types of polymer generators have been prepared under the all-in-one materials informatics platform, XenonPy. (1) language-model-based generators, NGrams, for 21 classes of polymers have been successfully trained; (2) reaction-based polymer candidate generator has been developed; (3) polymer generator based on rule-based virtual synthesis is going to be implemented. On top of the on-going expansion of the polymer generator library, application of our polymer informatics has been test on the design of new liquid crystalline polymers. Five new liquid crystalline polymers have been discovered. One of them further demonstrated a relatively high thermal conductivity, showing potential to be tested for industrial use. Our results are currently under preparation for publications. Seven presentations have been given around the world for this year's research achievement, and more will be given in the following year. Also, the development of our XenonPy platform has motivated new collaboration opportunities with the industrial companies. Last but not least, our work has been served as a foundation for another polymer informatics project, called RadonPy, which aims at producing the largest open calculation database for polymers.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
As the world recovered from the COVID incident, collaborative work is almost fully recovered as we originally planned. I have also been able to join many conferences and give talks to promote our research outcomes, as well as making connections to other researchers in the same field. This creates a lot of new opportunities to further develop my research.
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| 今後の研究の推進方策 |
The polymer generators have been successfully trained and being tested on new polymer discovery. The final step of this project is to implement the developed technology on our open materials informatics platform to allow researchers to easily access these useful tools. More demonstrative studies will be conducted to promote the new design strategy based on polymer informatics technology that we have developed.
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