| 研究課題/領域番号 |
23K04890
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| 研究種目 |
基盤研究(C)
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| 配分区分 | 基金 |
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| 応募区分 | 一般 |
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| 審査区分 |
小区分36010:無機物質および無機材料化学関連
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| 研究機関 | 広島大学 |
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研究代表者 |
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| 研究期間 (年度) |
2023-04-01 – 2026-03-31
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| 研究課題ステータス |
交付 (2023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)
2025年度: 650千円 (直接経費: 500千円、間接経費: 150千円)
2024年度: 260千円 (直接経費: 200千円、間接経費: 60千円)
2023年度: 3,640千円 (直接経費: 2,800千円、間接経費: 840千円)
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| キーワード | ESDA / Density of states / DFT method / Machine learning / Support effect / Heterogeneous catalysis / DOS decomposition / Universal Descriptor / Heterogenous Catalysts / DFT calculations |
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| 研究開始時の研究の概要 |
Without a detailed understanding of the electronic states of the catalysts’ active sites and the orbitals of the adsorbates involved in the interaction/reaction, it is unlikely to improve the existing catalysts, explore new possible catalytic materials, and design superior catalysts. Thus, this proposal aims to develop and apply my new concept, the electronic structure decomposition approach (ESDA), to explains the nature of the chemical bond between an adsorbate and a catalyst and that can be used to explore the materials' space to discover new and more functionalized catalysts.
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| 研究実績の概要 |
Over the last year, my research has focused on introducing and promoting the efficacy of the Electronic Structure Decomposition Approach (ESDA).
-Conference Presentations: ESDA has been promoted via presentations at local and international conferences, where it was praised as ingenious by peers.
-Publications: I published a paper: “Predicting CO Interaction and Activation on Inhomogeneous Ru Nanoparticles Using Density Functional Theory Calculations and Machine Learning Models” in the Journal of Physical Chemistry C, a highly reputable journal.
Additionally, I have finished writing a new paper, soon to be submitted to ACS Nano, exploring ESDA's capabilities and applications.
-Research Impact: ESDA is being tested for various systems involving different catalyst materials and adsorbates.
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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
A lot of effort and time are being dedicated to making this research great.
Several peers have accepted the ESDA and have called the approach "genius."
I am currently writing a second paper to be submitted to a high-impact journal.
Lastly, the ESDA is being expanded to confirm its universality for different catalytic systems by changing the catalyst and the adsorbate.
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| 今後の研究の推進方策 |
The methodology of this research is being expanded and applied to various systems consisting of different catalysts and adsorbates.
We are focusing on the universal application of ESDA.
Challenges encountered include optimizing the methodology for diverse systems and integrating more complex machine learning algorithms.
To address these, we will collaborate with experts in related fields and acquire updated computational resources to enhance our analysis capabilities.
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