Fabrication of Au Atomic Junctions Using Artificial Intelligence Implemented on FPGA
Project/Area Number |
18H01471
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Research Category |
Grant-in-Aid for Scientific Research (B)
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Allocation Type | Single-year Grants |
Section | 一般 |
Review Section |
Basic Section 21050:Electric and electronic materials-related
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Research Institution | Tokyo University of Agriculture and Technology |
Principal Investigator |
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Project Period (FY) |
2018-04-01 – 2021-03-31
|
Project Status |
Completed (Fiscal Year 2020)
|
Budget Amount *help |
¥17,420,000 (Direct Cost: ¥13,400,000、Indirect Cost: ¥4,020,000)
Fiscal Year 2020: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2019: ¥5,590,000 (Direct Cost: ¥4,300,000、Indirect Cost: ¥1,290,000)
Fiscal Year 2018: ¥7,540,000 (Direct Cost: ¥5,800,000、Indirect Cost: ¥1,740,000)
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Keywords | 人工知能 / 原子接合 / エレクトロマイグレーション / FPGA / ナノデバイス |
Outline of Final Research Achievements |
Recently, there has been much interest in the possibility of Ising spin model to solve combinatorial optimization problems. The Ising spin model is a statistical mechanics model of magnetism, and hardware implementations analogous to the Ising spin model have also been proposed. Here we showed that Ising machines can be used for the parameters optimization in experiments by direct mappings of parameters selection, which is one of a "combinatorial optimization problem", onto the Ising Hamiltonian. This study addresses a way of parameters optimization in feedback-controlled electromigration (FCE) method. We applied optimum parameters obtained by the ground-state searches of Ising spin model to FCE experiments. Further, we applied the system for fabrication of Au atomic junctions and gaps. Single-electron transistors (SETs) were also fabricated using the method. Korotzkov-Nazarov model exhibited a reasonable fit with SET properties.
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Academic Significance and Societal Importance of the Research Achievements |
本研究では、AIが、人間の経験的な作業に依存することなく実験的な研究活動を自律的・知能的に行うことが可能な独自システムの開発を行った。近年のAIの進歩は目覚ましく、これまで人間が経験的に行ってきた知的作業の代表格である「研究」という活動にAIを利用できるのではないか!?と仮説した。一般に、ナノスケールで発現される量子現象の観測では、実験サンプルの作製から物性測定に至るまで、その実験制御パラメータは非常に膨大となり、長時間の試行錯誤のもと、人間が経験的に当該パラメータを決定していた。この作業をAIが代替できれば、人間よりも遥かに効率的かつ精緻に実験研究の進展が期待できる。
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Report
(4 results)
Research Products
(17 results)
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[Presentation] Electromigration-Induced Structural Modification of Series-Parallel-Connected Au Nanogaps2018
Author(s)
K. Minami, S. Tani, K. Sakai, T. Sato, M. Ito, M. Yagi and J. Shirakashi
Organizer
AVS Pacific Rim Symposium on Surfaces, Coatings and Interfaces (PacSurf 2018), December 2-6, 2018, Waikoloa, HI, USA.
Related Report
Int'l Joint Research
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[Presentation] Single-Electron Tunneling Effects in Electromigrated Coulomb Island between Au Nanogaps2018
Author(s)
S. Tani, M. Ito, M. Yagi, M. Shimada, K. Sakai, K. Minami and J. Shirakashi
Organizer
13th IEEE Nanotechnology Materials and Devices Conference (IEEE NMDC 2018), October 14-17, 2018, Portland, OR, USA.
Related Report
Int'l Joint Research
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