Quantum Annealing for Functional Molecular Assemblies
| Project/Area Number |
21K05003
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 32020:Functional solid state chemistry-related
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Project Status |
Completed (Fiscal Year 2023)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2023: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2022: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2021: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | Quantum annealing / Self-assembly / Surface / Molecule / First-principles / Machine learning / Quantum Monte Carlo / Monte Carlo / self-assembly / surface / simulation / quantum annealing / porphryin / phthalocyanine / 量子アニーリング / 分子自己組織化 / 材料設計 / 表面 / 計算材料化学 |
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| Outline of Research at the Start |
This project will develop a computational method based on quantum annealing for predicting how molecules self-assemble on surfaces. This computational method will be designed for future quantum technologies, providing a “基盤” for a future nanomaterials discovery.
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| Outline of Annual Research Achievements |
During FY2022, we created a quantum annealing algorithm for simulating the assembly of surface-adsorbed molecules. During FY2023, we carried on this work as follows: (i) creation of a realistic intermolecular potential for the case of porphyrin molecules adsorbed to a (100) surface, using density functional theory and machine learning; (ii) programming of a quantum Monte Carlo (QMC) algorithm to predict the molecular assembly; (iii) extensive numerical simulations to evaluate QMC performance. It was confirmed that the QMC algorithm performs poorly compared to classical parallel tempering Monte Carlo over a variety of parameter regimes.
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Report
(3 results)
Research Products
(9 results)
