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 |
Granted (Fiscal Year 2022)
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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 | 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 |
Computational methods for predicting the assembly of surface-adsorbed molecules will accelerate breakthroughs in nanotechnology. During FY2022, we developed a quantum annealing method to predict the orientations of porphyrin molecules adsorbed to a gold surface. This system involves realistic, density functional theory-calculated intermolecular and surface-molecule potentials, but is also simple enough to be expressed as an Ising model. It is therefore a relevant target for developing quantum annealing algorithm. With this method, we succeeded to correctly predict the orientations of the molecules within a few minutes of computational time on a laptop, thereby confirming the ability of quantum annealing to be applied to molecular self-assembly phenomena.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
We have succeeded to implement quantum annealing for a realistic molecular system, which was the FY2022 goal of the original proposal. However, since submitting the original proposal, we have also developed a new genetic algorithm method for predicting molecular self-assembly as well. This method looks like it can be combined with quantum annealing to yield a novel classical-quantum prediction algorithm. For this reason, the research plan has changed slightly from the original proposal, although quantum annealing still features as the major element.
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| Strategy for Future Research Activity |
In addition to quantum annealing, we have also developed a novel genetic algorithm for predicting molecular self-assembly called 'evolution under fire' (Adv. Phys. Res. 1, 2022, 2200019). This method is very effective at predicting the positions of the molecules on the surface. On the other hand, quantum annealing looks very effective at predicting the orientations of the molecules for fixed molecule positions.
For FY2023, we will therefore combine both methods, yielding a new type of classical-quantum algorithm. We will characterise the performance of the algorithm in detail, and compare it carefully with an exclusively genetic algorithm approach. To finish the project, we will also explore the possibility of running our algorithm on a real quantum annealer.
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Report
(2 results)
Research Products
(5 results)
